From banking, marketing, insurance, healthcare, manufacturing, and technical jobs, AI-empowered solutions like ChatGPT are impacting major sectors worldwide and have permanently re-routed the trajectory of work as we currently understand it.

While new job creation and the ability to drastically improve productivity capabilities emerge from the unveiling of ChatGPT, so does the potential loss of countless jobs more easily and efficiently completed by this AI-powered chatbot.

In this article, we’ll highlight newly emergent jobs and skills for utilizing this nascent tool, and explore a new frontier of AI jobs and its vast array of potential applications.

We’ll also identify the positions at risk of becoming replaced by ChatGPT, delving into which roles will be most affected and how to manage AI’s impact on the future of work.

The Impact of ChatGPT and AI on new and existing jobs

ChatGPT has impacted various industries, including customer support and service, content generation and marketing, virtual assistants, language translation, research and data analysis, creative writing and storytelling, and personalized learning and education. 

A report by Goldman Sachs shows advances in AI automation can potentially expose approximately 300 million full-time jobs worldwide to redundancy. 

However, the same research suggests these advancements could benefit the macro-economic landscape. Tools utilizing advances in natural language processing, such as ChatGPT, are forecasted to generate a 7% increase in global GDP, translating to nearly $7 trillion over ten years.

ChatGPT’s ability to understand and generate human-like text has reimagined processes, enhanced user experiences, and increased productivity across these sectors.

While certain jobs may be at risk of automation or transformation, new job opportunities may also emerge due to advancements in AI. From automation to content generation, AI systems like ChatGPT are transforming industries and unlocking new avenues of opportunity. 

There’s a spike in demand for professionals with expertise in artificial intelligence who can contribute to AI development, implementation, and optimization. As a result, a range of new job listings has emerged on job recruitment sites seeking candidates with specialized skills as “AI specialists.”

Which Sectors Will be Impacted Most by AI? 

As ChatGPT continues to evolve and be integrated into different industries, its impact will likely expand further, driving innovation and transforming how we work and engage with AI.

Below are a few sectors where ChatGPT significantly impacts new and existing jobs:

AI Assistants and Chatbot Development

The rise of ChatGPT has created a demand for professionals with expertise in developing AI assistants and chatbots. These professionals are responsible for designing, training, and deploying conversational AI models to enhance customer experiences and automate tasks in various industries.

Natural Language Processing (NLP)

ChatGPT relies heavily on NLP techniques to understand and generate human-like text. As a result, there is a growing need for NLP specialists who can develop algorithms, models, and applications that improve language understanding and generation capabilities.

Content Strategy and Management

With ChatGPT’s ability to generate compelling content, content strategists’ and managers’ roles are evolving. These professionals now focus on curating and optimizing AI-generated content, ensuring it aligns with brand messaging and resonates with target audiences.

Data Annotation and Training

ChatGPT requires extensive training data to perform effectively. Data annotators play a crucial role in preparing high-quality datasets by labeling and categorizing text samples used to train and fine-tune AI models like ChatGPT.

Ethical AI Governance

The need for ethical AI governance and policy experts grows as AI becomes more prevalent. These professionals ensure AI systems like ChatGPT adhere to ethical guidelines, address biases, and protect user privacy.

User Experience Design

Creating seamless and intuitive user experiences with AI-powered chatbots and virtual assistants is essential. User experience (UX) designers work closely with AI developers to design conversational interfaces that are user-friendly, efficient, and meet user needs.

Technical Support and Maintenance

AI systems like ChatGPT require ongoing support and maintenance. Technical support professionals specialize in troubleshooting issues, ensuring optimal performance, and implementing updates to enhance the functionality and accuracy of AI models.

AI Research and Development

Developing advanced AI systems like ChatGPT relies on continuous research and innovation. AI researchers and developers are at the forefront of advancing AI capabilities, exploring new algorithms, and pushing the boundaries of what AI can achieve.

Recent reports reveal that OpenAI has launched a platform that allows users to create custom versions of ChatGPT for specific use cases without coding. This can empower individuals and organizations to leverage the tool to enhance productivity.

Jobs Being Automated by ChatGPT and AI

While ChatGPT and LLMs offer tremendous opportunities, they also raise concerns about the potential displacement of certain jobs. 

According to internal documents and sources shared via CNBC, ChatGPT could theoretically qualify for a level-3 software engineer position at Google.

The ability of these models to understand and generate human-like text has the potential to make some jobs obsolete, with a particular impact on professions that heavily rely on language-based tasks.

Customer Support

ChatGPT’s natural language processing capabilities could revolutionize customer support by providing instant responses and assistance. This may reduce the need for manual customer service representatives as AI systems become more adept at addressing customer queries and resolving issues.

Content Generation

Writers and creators may compete with AI-powered systems that generate high-quality articles, blog posts, and creative works. While human creativity and nuance are difficult to replicate, AI models like ChatGPT can produce vast amounts of content quickly, potentially impacting certain sectors of the publishing industry.

Translation Services

With their ability to process and generate text in multiple languages, language models like ChatGPT potentially threaten professional translators. As AI translation systems improve, they may increasingly replace human translators for certain routine translation tasks.

Data Entry and Analysis

AI models have the potential to automate data entry and analysis tasks, reducing the need for manual data entry operators and analysts in some industries. This could lead to increased efficiency but may also result in job displacement.

Managing the Impact of AI Responsibly

Whether it be valid concerns around infactuality, bias, and misuse, the material risks and concerns about the widespread use of AI tools like ChatGPT are too severe to ignore. 

For instance, it has occasionally generated incorrect or misleading information, as it relies on patterns and data from the internet, which may include inaccuracies. 

ChatGPT has also exhibited bias in its responses, reflecting the biases present in its training data. This can perpetuate societal preconceptions and prejudices, potentially reinforcing harmful stereotypes or promoting misinformation.

Contextual understanding can also be a challenge for ChatGPT, leading to responses that may need more coherence or address specific user queries accurately.

However, when implemented responsibly, ChatGPT’s potential applications are endless if developed and deployed thoughtfully and ethically. 

Below are solutions organizations can leverage for responsibility to manage the impact of AI.

1. Policies to support displaced workers: Companies and governments can implement policies and initiatives to help workers whose jobs may be affected by AI automation. This includes providing retraining programs, job placement services, and financial assistance to facilitate the transition into new roles or industries.
2. Companies transparently incorporating AI: Organizations should adopt transparent practices when implementing AI systems. This involves communicating AI technologies’ intended use and potential limitations to users, customers, and stakeholders. Transparency builds trust and accountability, ensuring responsible deployment of AI.
3. Workers learning new skills and adapting: As AI technology evolves, workers need to learn new skills and adapt to changing job requirements continuously. Investing in training and upskilling programs can help employees acquire the necessary capabilities to work alongside AI systems effectively. This approach encourages resiliency and empowers individuals to embrace the opportunities presented by AI.
4. Adequate AI governance: Establishing robust governance frameworks for AI is crucial. This involves developing guidelines, regulations, and ethical standards for responsible AI development and deployment. Clear guidelines should address bias mitigation, data privacy, and algorithmic transparency. Effective governance mechanisms promote ethical and accountable AI practices.

AI & The Future of Work 

Sophisticated AI-driven tools like ChatGPT are reshaping the nature of work, with major sectors experiencing a major shift towards digital transformation. 

Unsurprisingly, AI is at the forefront of this new wave—its potential applications in supporting productivity are all too valuable to ignore.

AI tools are here to stay and will only become more ubiquitous in professional and wider social spaces as AI technology improves and new iterations emerge.

According to Business Insider, AI can replace various job roles. Among those at high risk are coders, computer programmers, software engineers, data analysts, advertising jobs, content creation jobs, technical writing jobs, journalism jobs, paralegals, and legal assistants. 

The impact of ChatGPT and AI on the future of work will continue to raise important questions regarding society’s overall well-being.

It remains to be seen whether the automation of certain tasks will lead to widespread job displacement due to AI advances.

Today, AI has the potential to reimagine industries, facilitate innovation, and heighten efficiency levels across sectors.

In a recent ResumeBuilder survey, 90% of business leaders said ChatGPT experience is a beneficial skill for job seekers, with 48% of companies using ChatGPT reported to have replaced some workers.

With AI augmenting certain roles, it frees up time for innovation. It can potentially increase human productivity in other areas—providing opportunities for individuals to focus on more creative and complex work.

Regardless, organizations on their transformation journey must address ethical considerations and ensure that AI is developed and deployed responsibly to mitigate unintended consequences.

The post ChatGPT Jobs: How AI is Creating New Roles & Making Others Obsolete appeared first on Digital Adoption.

With transformation efforts becoming expedited due to the COVID-19 pandemic, digital adoption strategies were swiftly deployed to address unprecedented challenges never before seen in the business arena.

The role of a director of digital strategy gives businesses the resources needed to address these unforeseen challenges, along with expert solutions for navigating the high-octane digital age.

A digital strategy director’s value lies in their ability to effectively align and optimize digital initiatives with an organization’s overall goals and objectives—and is becoming a clear prerequisite for facilitating today’s transformation climate.

This article will explore what a director of digital strategy is, what their roles and responsibilities are, and the importance of their position in business today. We’ll also reveal their salary intake and the value of securing digital transformation for future-ready firms. 

What is a Director of Digital Strategy? 

A director of digital strategy is a professional responsible for developing and overseeing an organization’s digital initiatives and online presence. 

This role involves crafting strategies to leverage digital technologies, social media, and online platforms to achieve business objectives. The director typically collaborates with various departments to align digital efforts with overall organizational goals, enhance user experience, and oversee digital transformation initiatives.

In an era where digital maturity serves as the end goal for most companies, the race is on for firms to leverage the latest digital solutions that reimagine business models and strategies for success.

A director of digital strategy helps to address this challenge, assisting businesses to adapt and evolve to better tackle shifting consumer expectations and changes to the wider business landscape.

According to Statista, most companies increased their investment in digital and technology initiatives during the pandemic, while 44% hired more full-time equivalent (FTE) employees for digital/tech roles. 

Director of Digital Strategy Job Description

A digital strategy director’s responsibilities include strategizing efforts to amplify an organization’s digital footprint and online presence to better reach its target demographic.

A more detailed description of their job responsibilities is as follows: 

• Review and enhance current digital strategic capabilities while planning and deploying new strategies and digital transformation projects.
• Conduct comprehensive research and deploy metrics that assess customer needs and insights to inform digital initiatives better.
• Establish strong decision-making processes that clearly outline procedures and frameworks to inform prospective project actions up to 18 months in advance.
• Identifying transformation opportunities, business pain points, technology limitations, and improving analysis capabilities of digital data sets
• Conducting a thorough analysis of consumer needs and requirements using large datasets and analytics tools to extract patterns and trends.
• Optimizing an organization’s e-commerce platform migration and resistance could involve migrating its e-commerce infrastructure to platforms such as Magento, WooCommerce, and OpenCart and concurrently redesigning it. 
• Nurture interactions and communication across teams and departments to better understand and align business objectives 
• Create a line of clear communication with IT departments to gain a 360-degree understanding of tech capabilities and how they intersect and bolster business strategies. 

What Skills and Qualifications Should a Director of Digital Strategy Have?

A blend of comprehensive qualifications and honed skills is essential to thrive as a Director of Digital Strategy. 

Academic credentials form the foundation, typically requiring a bachelor’s degree or qualifications in Marketing, Business, Communications, Education, Management, Business Administration, Journalism, Computer Science, and Graduate Studies.

Advanced degrees, such as an MBA, can elevate one’s standing and provide a deeper understanding of strategic business principles.

While educational requirements are necessary for digital director positions, the following skills also serve as essential prerequisites for fulfilling the roles and responsibilities of director of digital strategy:

Leadership experience is paramount

Having held prior roles in digital strategy or related fields demonstrates the capability to guide teams effectively. This entails managing projects, inspiring innovation, fostering collaboration, and driving successful outcomes.

Expertise in digital marketing is a linchpin qualification

Proficiency across various digital channels — from SEO and SEM to social media — is crucial. A nuanced understanding of the digital customer journey is a prerequisite, as well as the ability to adapt strategies to align with changing consumer behaviors.

Enhanced technical proficiency

While not necessarily requiring hands-on coding skills, technical proficiency demands familiarity with web technologies and e-commerce platforms. Collaboration with IT teams necessitates a capacity to make informed technology recommendations and comprehend the technical nuances of digital implementations.

Analytical Proficiency

Analytical skills are a linchpin in today’s data-driven landscape. An adept Director of Digital Strategy can interpret complex data, derive actionable insights, and make informed, data-driven decisions. A background in data analysis, business intelligence, or a related field complements this skill set.

Effective Communication

Communication and stakeholder management are indispensable. Exceptional verbal and written communication skills are crucial, enabling effective conveyance of complex digital strategies to technical and non-technical stakeholders. Collaborative prowess is vital for working seamlessly across cross-functional teams.

Adaptability and Innovation

Adaptability and innovation are also hallmarks of a successful Director of Digital Strategy. The digital arena evolves rapidly, demanding leaders who can keep pace with change and leverage emerging technologies for strategic advantage.

Project Oversight

Ideally backed by relevant certifications, project management skills ensure effective oversight and timely implementation of digital initiatives. This competency is pivotal in steering projects from conception to execution successfully.

Customer-Centric Approach

Finally, a customer-centric approach is non-negotiable. Directors of Digital Strategy must prioritize customer experience, integrating personalization and user-centric design principles into overarching strategies.

A Director of Digital Strategy should possess a blend of educational qualifications, leadership experience, technical proficiency, and a strategic mindset. 

Director of Digital Strategy Salary 

The salaries of digital strategy directors can vary significantly depending on an employer’s specific needs and expectations when it comes to fulfilling the role.

Factors influencing scaling salaries for a director of digital strategy may depend on a candidate’s educational achievements, geographic location, and diverse experiences, skills, and roles in driving digital proficiency.

According to Glassdoor, the median earnings for a Director of Digital Strategy in the U.S. is $213,747 annually, with an average salary of $158,895 annually. However, several factors contribute to the nuanced salary profiles for individuals in this position.

For example, salary figures may change for candidates in geographically significant regions where companies are close to technological development zones, I.e., San Francisco, CA, and Seattle, WA.

Let’s take a closer look: 

Entry-Level Salary Range:

Digital strategy directors with entry-level experience can expect to earn between $79,000 – $122,000 per annum or $59 per hour.

Upward Salary Trend:

As one climbs the ranks in digital strategy, an upward salary trend will reflect the increasing leadership responsibilities within the field.

Glassdoor statistics show a clear progression:

•  Director of Strategy: $263,700 per year
•  Senior Director: $291,803 annually
•  Vice President of Strategy: $318,098 per year

Additional Earnings:

When considering other earning potential, individual commissions, year-end bonuses, and profit sharing can earn Directors of Digital Strategy an additional $54,852 annually.

Securing Digital Transformation for the future-ready business

In the digital transformation era, businesses face a critical choice—embrace change or risk irrelevance. 

A Director of Digital Strategy is one of many cogs helping to facilitate this change successfully, tasked with steering companies through tech complexities and guiding them toward a future of digital proficiency.

Whether orchestrating e-commerce platform migrations or reshaping customer experiences, these directors play a central role in charting the course of transformation—ensuring that every digital move aligns with overarching business goals.

In a world where agility and adaptability are a competitive edge, digital strategy directors ensure businesses adapt and are positioned to prevail over the challenges of tomorrow.

The post Director of Digital Strategy: Job Description, Responsibilities and Salaries Explained appeared first on Digital Adoption.

With the costs of acquiring a user at USD 14,772, it makes sense to optimize your product stickiness strategies to ensure that when products fall into your users’ hands, they stay there, and you learn why they enjoy them. 

One of the most competitive markets is mobile technology applications. According to Statista, the average churn rate (customers stopping using apps) stands at 70% over three months, reaching its highest point at 97.7% for casual games. 

Merely attracting users to try your product isn’t the ultimate goal; ensuring consistent usage requires a well-defined product adoption strategy and excellent customer engagement for the perfect sticky product. 

Product-led growth hinges on cultivating product stickiness, ensuring users consistently return due to the engaging and enjoyable fulfillment of their needs.

While the average person installs eighty mobile apps—they typically use only nine daily. Therefore, you need to ensure that your products become part of every user’s daily nine for them to become sticky.

This article explores the concept of product stickiness and provides insights into crafting sticky products. It covers the definition of product stickiness, strategies for creating such products, methods for measuring product stickiness, and the utilization of data related to product stickiness.

What is product stickiness?

Product stickiness refers to the frequency with which users revisit your product due to its engaging and enjoyable nature in fulfilling their requirements.

Stickiness fuels growth by enhancing customer retention, offering account expansion opportunities, and elevating customer lifetime value. 

The ratio of Daily Active Users to Monthly Active Users (DAUs/MAUs) stands out as one of the pivotal product stickiness metrics employed to gauge the stickiness of your product.

How to make sticky products

Once you have understood product stickiness, it is time to implement it. 

The first step to making your products sticky is to evaluate your product’s usage rate through customer activity data analysis.

Step 1: Evaluate your product’s usage rate

A product stickiness score isn’t a mystical shortcut to make users instantly adore your product overnight. At its essence, it’s simply a metric revealing user engagement by assessing daily and monthly active usage after collecting customer product activity data.

Before delving further, it’s crucial to comprehend your product usage and define daily and monthly active usage:

• Daily Active Users (DAUs): This metric gauges the number of users actively using your product within 24 hours.
• Monthly Active Users (MAUs): This signifies the count of unique users undertaking a significant action in your product within the last 30 days.

You might question, “Can’t I determine my product’s engaged users by measuring DAUs and MAUs?” The answer is both yes and no.

While active user metrics showcase users performing measurable actions daily, weekly, or monthly, without comparing these metrics against your product benchmarks, you can’t gauge your product engagement levels or leverage that data effectively.

Product stickiness reveals your daily active users as a fraction of your monthly active users, providing a more critical perspective on your user base. 

It highlights your most active users, identifies potential churn, and empowers you to:

• Develop tailored promotional campaigns for users with lower stickiness scores prone to churn (for growth engineers).
• Segment users based on stickiness scores, directing re-engagement efforts towards those with low stickiness ratios (for marketers).
• Understand and target your most engaged users, reshaping marketing campaigns to appeal to similar audiences (for marketers).
• Calculate your product’s adoption rate, indicating how likely new users will continue using it.

Your product stickiness ratio transforms MAUs and DAUs from mere information into actionable product adoption metrics. 

This metric empowers product managers and growth engineers to craft a well-rounded product strategy as you begin calculating product stickiness.

Step 2: Identify the most active users

Your product stickiness score unveils which active users exhibit the highest engagement levels, presenting a potent growth strategy as you analyze user behavior. 

Rather than escalating your user acquisition budget and deploying various tactics to win over prospects, it’s more effective to target customers who are inherently inclined to use your product.

This process might feel perplexing at first, but bear with us. Product stickiness highlights your most engaged users. You can explore their use cases and demographics using product analytics, including age, location, acquisition channel, and pricing tier.

Analyzing these data points allows you to foresee the future, identifying customers more likely to respond positively to your marketing campaigns, promotional offers, and ads.

If Salesforce allocates a substantial part of its budget to target early-stage startups, the return on investment would be minimal, with a high likelihood of these new users eventually churning.

In contrast, based on its experience and stickiness rate analysis, Salesforce understands that its ideal customer is a large enterprise with tens or hundreds of Sales Development Representatives (SDRs). 

These users find Salesforce helpful and are more likely to remain committed to the product in the long run. Product stickiness empowers you to discern your ideal users, enabling a focused allocation of marketing and growth resources tailored to them.

Step 3: Uncover methods to enhance your product’s stickiness

Product stickiness is a constructive feedback loop for your product—assessing it unveils recurring patterns within your user base. Closely examining these patterns provides insights into building a superior product or attracting ideal users.

Consider this scenario: If your product stickiness analysis indicates that the most engaged users belong to teams of 11 to 50 individuals, allocating less of your budget to promote your product to solopreneurs and single users might be prudent.

Product stickiness harnesses the power of product analytics, user behavior, and demographic patterns among your ideal users to guide enhancements to your brand, tailor your product, and shape the overall experience. 

The aim is to cater to users who are more likely to develop a genuine affinity for your product.

Step 4: Review and improve product stickiness 

It’s crucial to note that product stickiness alone isn’t a standalone growth strategy. It serves as a qualitative metric, indicating the proportion of highly engaged users. 

The real impact on your product’s growth trajectory stems from how you leverage that data.

To amplify product stickiness, you must test diverse variations of your experiences of customer onboarding with DAP and in-app product messaging. 

Start posing questions like:

• Which onboarding flow yields a higher number of engaged users?
• Does our in-app guidance contribute to enhanced user activation?
• Among re-engagement email campaigns, alerts, and notifications, which effectively reactivates inactive users?
• Which user segment is more prone to churn or evolve into power users?
• Where do friction points emerge in our user flows?

The essence of testing lies in uncovering commonalities among your most active users, crafting campaigns targeting those specific data points, and refining strategies to acquire and retain users efficiently.

DAP design fosters a culture of testing, enabling the creation of multiple versions of product tours, help docs, pop-ups, or automatic localization of content to onboard users in their preferred language.

Step 5: Gather in-app user insights and NPS surveys

While behavior analytics unveils patterns in user interactions with your product, its scope has limits.

Product and behavior analytics showcase how users engage with existing features, offering insights for optimization. However, they fail to reveal which features users desire from scratch or wish to eliminate.

Ensure a seamless process by proactively seeking direct inquiries instead of leaving it to chance, recognizing the indispensability of user feedback.

A DAP facilitates the distribution of open-ended feedback surveys, NPS surveys, and other feedback collection methods. 

These surveys gauge users’ likelihood to recommend your product, accompanied by follow-up responses allowing them to express their reasons for loving or not loving your product.

Seamlessly embed these surveys in pop-ups, with extensive testing options to discern audience preferences and amass valuable product feedback.

In essence, a DAP aids product managers in comprehending user interactions with their products. Yet, this is only half of what the platform offers. 

With a DAP, you can conduct A/B tests on multiple campaigns, design patterns, or UI elements, discerning preferences. 

Doing so empowers your product team to construct a data-driven growth strategy, crafting a sticky and endearing product that users consistently return to.

How do you measure product stickiness?

User count plays a pivotal role in establishing a product’s stickiness ratio, necessitating additional studies even if they seem straightforward to compute.

To calculate the product stickiness ratio, divide daily active users by monthly active users. This measurement is indispensable for assessing the stickiness ratio’s significance.

The product stickiness rate is a crucial product metric, offering insight into the product or service’s value. It depicts the frequency with which customers return to your product or service.

The product stickiness ratio formula empowers the product manager to gauge the necessary improvements over time. It also aids in understanding the substantial differences among user types and their usage patterns.

Even changes in user behavior over a predetermined period can be monitored.

Initially, the total number of users logged in during the last 30 days must be divided by the average daily or weekly login rate to compute the average daily or weekly login rate.

Daily recalculations provide the product stickiness ratio, representing a moving average of the customer retention rate over time.

Determining user retention and attrition solely based on this rate necessitates conducting cohort analysis to segment consumers according to their use cases.

Moreover, if customers use your app sparingly, the stickiness rate may not accurately reflect their engagement. Therefore, additional metrics such as customer lifetime value, churn rate, and retention rate become crucial for a comprehensive product evaluation.

How do you utilize product stickiness data?

The DAU/MAU ratio is a valuable metric for assessing another critical aspect of a product—its health. While the quantity of users, gauged by DAU or MAU, provides information, it fails to convey the quality of your user base.

For product leaders, the stickiness ratio proves instrumental, offering insights into the frequency of user interactions, variations in usage among different user types (personas), and their evolution over time.

IMAGE – PLEASE DELETE

A DAU/MAU ratio of 0.6 indicates that 60% of monthly visitors also engage with the product daily, signifying good product health. 

It’s essential to note that a low DAU/MAU ratio doesn’t necessarily imply unhealthy product conditions, especially in cases involving multiple products.

The ratio may be low due to a combination of infrequent and dedicated users. In such instances, the focus should shift towards strategies to enhance the engagement of deeply involved users.

Remember that experience beats numbers

In the realm of product stickiness, it is imperative to consistently prioritize user experience over relying solely on metrics within your customer success teams. 

While metrics such as DAU/MAU ratios undoubtedly offer valuable insights, the true essence of sustaining user engagement lies in meticulously crafting an immersive and valuable customer journey. Quantitative metrics alone may fall short of capturing the qualitative nuances that underpin user loyalty and retention.

Shift the focus towards creating an experience that resonates deeper, fostering genuine connections between users and your product. The aim is to develop an understanding that encourages long-term user returns and prompts users to advocate for your product within their networks due to the inherent quality of their interactions.

Upon achieving this holistic approach to user experience, the desired usage metrics will naturally and promptly follow suit, reflecting the success of your strategy in cultivating lasting user engagement.

The post What is product stickiness, and how to make sticky products? appeared first on Digital Adoption.

Despite the term’s exciting implications, many researchers argue that these ’emergent abilities’ are often a result of increased computational capability rather than a sudden leap in AI cognition.”

We’re a long way off from the “rise of the machines” that the Terminator films predicted in the 1980s, with armies of robots aggressively taking over the world! 

But as the capabilities of generative AI models move on, some researchers are seeing “sparks” of a deeper intelligence in AI. In other words, we see how AI models can sometimes complete tasks they were not programmed to do.

Researchers use the word emergence to describe these surprising skills. 

When you hear phrases like emergent abilities, emergent properties, or emergent capabilities, we’re talking about the unprogrammed skills of AI. While this is still a very new field, new research is shining a light on AI’s emergent abilities, and AI users are starting to wonder about the potential for this new technology.

This article will look into the new field of emergent AI. It will:

• Explain the meaning of emergent AI abilities;
• Introduce several examples of emergent AI in practice;
• Suggest some future directions for emergent AI.

Emergent AI abilities are important to understand. According to McKinsey, as much as 79% of workers have now been exposed to uses of generative AI. As time goes forward, that majority may need to detect and utilize emergent abilities. 

So, we must do our best to prepare.

What are emergent AI abilities?

An AI Tool has “emergent AI abilities” when it can complete tasks it was not specifically programmed to do. The AI system does its work, and like magic, something new happens. 

Emergent AI abilities may come as a surprise to the developers. Or, researchers might make experimental situations in which AI can seek a way to answer a problem – even though they weren’t told explicitly how to make the answers. 

Emergent AI is clearly an exciting thing. But right now, we don’t know how harmful they might turn out to be. So, Emergent AI is a part of AI risk management.

In 2023, AI’s emergent capabilities are in the news because of fresh research. In an extensive research paper from April, Microsoft researchers found the “sparks” of emergent behavior in ChatGPT. But in the same month, Stanford researchers found that this behavior may actually be a “mirage.”

By the way, the word “emergent” here has a special meaning. Emergent behavior happens when a complex entity does things that its component parts do not. Termite mounds, snowflake formation, and human language can all give examples of emergence.  Emergent AI abilities are the same: the component parts do something new.  

So, you must be careful when you hear the phrase “emergent AI.” Some folks will use it to talk about new and innovative uses of AI. 

For example, “emergent AI” is a key theme for the Gartner 2023 emerging technology hype cycle. To be clear, this article will not discuss emerging AI technologies. We will only talk about emergence in artificial intelligence.

Examples of emergent AI abilities

Here’s a warning, though. 

A casual observer won’t be astonished by the current emergent capabilities of large language models. 

Right now, emergent capabilities of AI won’t suddenly make your profits skyrocket.

All the same, emergent abilities in large AI models are fascinating. Let’s take a look at some classic examples.

• In the 1980s, computer scientist Craig Reynolds introduced the Boids program, a simulation illustrating how bird-like entities can mimic the flocking and formation movements of real birds. This model serves as a compelling example of how intricate collective behavior can emerge from the interplay of straightforward local rules.
• Microsoft’s 2023 research brings forth a range of straightforward examples to help assess emergent behavior. These simple tasks indicate “sparks” of genuine emergence – and perhaps artificial general intelligence. For instance, Microsoft’s research demonstrates that GPT-4 can proficiently infer characters’ mental states and identify cases of miscommunication and misunderstanding, akin to passing the Sally-Anne false belief test. Small milestones like this show the limits and possibilities of generative AI.
• The tech giant Google’s DeepMind subsidiary has unveiled remarkable AI cases. Notably, DeepMind’s AlphaZero, a chess-playing AI showcased in a 2018 article in the journal Science, showcases extraordinary prowess in mastering the game. Furthermore, DeepMind created a team of digital humanoids that learned to play football autonomously. While they comprehend the objective and possess essential tools, they were not specifically programmed to handle the inherent unpredictability of this sport. This underscores the captivating unpredictability of AI’s emergent capabilities.

Some reports of emergent abilities in AI may, however, be exaggerated. For example, CEO Sundar Pichai suggested that Google’s Bard had learned Bengali independently, but fact-checkers later pointed out that the model was initially trained in Bengali. 

Risks of Emergent AI 

Leaders in AI research are alert to the risks of emergent AI capabilities. As Demis Hassabi, the head of DeepMind, reminded us in October 2023, “The next few generations may be when they have extra capabilities like planning and memory and other things … They will be phenomenal for good use cases, but also they will have risks.”

Therefore, artificial intelligence leaders should try to understand the unpredictable abilities that AI could be capable of in the future. 

Let’s take a quick look at some of the major risk areas:

1. Offensive chatbots. Chatbots with machine learning capabilities may sometimes generate inappropriate, offensive, or biased responses due to unpredictable emergent behavior based on user interactions.
2. Reinforcement learning losing its way. In reinforcement learning, AI agents learn by trial and error. Unpredictable emergent behavior might result in unintended actions, such as a robot learning to exploit a system or finding novel ways to complete an unsafe or ethical task.
3. Inconsiderate content generation. AI systems for content generation can sometimes produce content that violates copyright, infringes on privacy, or spreads misinformation, leading to unpredictable consequences.
4. Financial trading instability. High-frequency trading bots can exhibit unpredictable behaviors, leading to market volatility and economic instability if they trigger rapid, unexpected fluctuations.
5. Autonomous drones. Autonomous drones with unpredictable behavior may pose risks in areas like surveillance, privacy invasion, or accidental collisions.

To address the potential negative consequences of unpredictable AI emergent abilities, researchers and developers are working on building more robust, interpretable, and controllable AI systems, and policymakers are considering regulatory frameworks to ensure responsible AI deployment.

Right now, these consequences are just risks; we don’t know if they’ll come true. And, in the future, we may realize that we were worried about nothing. 2023 research from Stanford University researchers suggested that Emergent abilities were just a “mirage”: created because of the way we measure, not because of their actual abilities. 

Should you plan for emergent capabilities today?

For business-level end users, the intricacies of emergent AI abilities need not be a primary concern today. 

Instead, the focus should be on remaining vigilant about the broader risks related to emergence and bias. This is an ideal moment to ensure the proper functioning of your “shadow AI,” implement clear AI policies, and verify the overall health of your software. If issues arise, address them promptly.

Conversely, AI researchers should prioritize acquiring a comprehensive understanding of emergence. They should be adept at recognizing emergent capabilities as they surface and conducting thorough exploration and analysis.

While many aspects of AI emergence remain shrouded in mystery, it’s foreseeable that this domain may soon become the forefront of digital risk management. 

Stay prepared, as the future promises further intriguing developments in AI’s emergent abilities.

The post Emergent AI Abilities: What You Need To Know In 2023 appeared first on Digital Adoption.

Modern consensus-building methods, such as Fist to Five, are instrumental in driving organizational transformation and preparing teams for the future of work. 

Harvard Law School states, “Consensus-building techniques can help parties facing a group decision reach longer-lasting, more harmonious outcomes than resorting to an up-or-down vote.”

In this article, we’ll explore the benefits of Fist to Five and how it can improve group dynamics and decision-making processes. We’ll also look at implementing this technique effectively within your organization.

What is Fist to Five?

Fist to Five is a participatory decision-making technique utilized by groups and teams to gauge the level of consensus or agreement on a particular proposal or idea.

Instead of the simple two-option answer of “yes” or “no,” the increasing scale of options enables a more qualitative form of gauging consensus, with the intensity of agreement increasing with the increase of each finger.

The methodology works by first posing a question or statement, of which respondents then share their level of agreement by holding up a number of fingers. 

A fully closed fist represents the most non-agreeable way of answering, serving as the unequivocal “no,” with a show of five fingers representing the most agreeable answer—or simply a resounding “yes.”

The effectiveness of Fist to Five is more related to facilitating open communication and encouraging participation rather than statistical analysis or collecting numerical data.

Why Is Fist To Five Important? 

With the ongoing digital transformation across sectors, consensus-building methods are vital in facilitating effective decision-making and fostering collaboration.

Navigating the complexities of group decision-making becomes significantly easier with the “Fist to Five” method. 

Let’s explore why it’s important: 

Promotes Engagement

Fist to five encourages active participation in discussions, ensuring everyone’s opinions are heard and valued.

Quick Feedback

It provides a fast and efficient way to gauge the comfort level, understanding, or agreement on a particular topic or decision.

Non-Verbal Communication

For those who are less vocal, it offers a non-threatening way to express their thoughts or feelings.

Encourages Consensus

 It promotes a democratic decision-making process where everyone’s vote counts, fostering a sense of unity and consensus.

Easy to Use

The simplicity of the fist to five method makes it accessible and easy to adopt for any team or group, regardless of their size or diversity.

Versatile Tool

It can be used in various settings – classrooms, corporate meetings, community gatherings, etc., making it a versatile tool for feedback and decision-making.

Boosts Transparency

It encourages openness and transparency by visually displaying the level of agreement or disagreement within a group.

6 stages of Fist to Five:

When teams use simplistic “yes” and “no” voting methods, it leaves little room for conveying often nuanced and complex opinions of team members.

This five-point scale facilitates a more informative way of building consensus, better-enabling leaders to gauge the needs and expectations of their teams.

The Fist to Five Process 

How to Use Fist to Five Voting Strategy in Meetings?

As previously stated, each participant extends their hand, representing their vote, with a closed fist indicating strong opposition (zero) and an open hand with all fingers extended, signifying complete support (five). 

However, if respondents aren’t entirely aware of the scope of the question or the accurate meaning of each vote, it can lead to potential misunderstandings and misinterpretations of the results.

Below, we outline the Fist to Five process in eight simple steps to help facilitate effective decision-making and foster open communication within your team or group.

1. Define the decision

Clearly articulate the decision or problem that needs to be addressed. Ensure that all participants have a common understanding of the issue at hand.

2. Explain the voting scale

Share the Fist to Five voting scale with all participants. Emphasize that a closed fist represents strong opposition (zero), and an open hand with all fingers extended signifies complete support (five).

3. Conduct the vote

Ask participants to extend their hand and cast their vote by showing a number of fingers representing their level of agreement or opposition. Participants should keep their vote hidden until everyone is ready to reveal it simultaneously.

4. Simultaneous reveal

Instruct participants to reveal their votes at the same time. This ensures that individuals aren’t influenced by others and encourages an honest expression of opinion.

5. Facilitate discussion

 Encourage participants to explain their chosen vote and its reasoning. Foster an open and respectful discussion where participants can ask questions, seek clarification, and share perspectives

6. Assess the group sentiment

Evaluate the overall sentiment of the group by observing the distribution of votes. Take note of any extreme positions or areas of consensus.

7. Repeat if necessary

If consensus is not reached or further refinement is needed, conduct additional rounds of voting and discussion. This iterative process allows for exploring alternative options and gathering more feedback.

8. Reach a decision

Based on the discussion and feedback received, work towards reaching a decision that considers all participants’ input. Aim for a solution that garners a reasonable level of agreement and addresses the concerns raised during the process.

What Are The Benefits of Fist to Five?

According to the Office of Personnel Management (OPM), effective teams strive for consensus, which means finding a proposal acceptable enough that all team members can support it, with no member opposing it.

Introducing the Fist to Five methodology into your decision-making process assists in this regard, expediting consensus building along with an array of other remarkable benefits. 

Here’s a glimpse into the advantages that await:

1. Amplified Transparency

 With Fist to Five, transparency takes center stage. Each participant openly displays their level of agreement or dissent on a scale from one to five. This fosters a culture of honesty, ensuring that all viewpoints are acknowledged and respected.

2. Enhanced Collaboration

By encouraging everyone to voice their opinions, Fist to Five cultivates a collaborative environment. Team members engage in active discussions, exchanging ideas and perspectives, leading to comprehensive decision-making incorporating diverse insights.

3. Efficient Consensus-Building

Fist to Five streamlines the consensus-building process by promoting quick assessments of agreement. Rather than prolonged deliberations, this method allows teams to swiftly gauge collective sentiment, saving time and expediting progress.

4. Mitigated Groupthink

The Fist to Five approach safeguards against the pitfalls of groupthink. Encouraging individuals to evaluate their level of support independently mitigates the influence of dominant voices and promotes critical thinking among team members.

5. Inclusive Decision-Making

 Every participant’s opinion holds value in Fist to Five. It ensures that all team members, regardless of seniority or hierarchy, have an equal opportunity to contribute. This inclusivity fosters a sense of ownership and boosts overall morale within the team.

6. Adaptable Flexibility

Fist to Five enables adaptability by allowing participants to signal their readiness for change. The scale clearly indicates individuals’ willingness to embrace new ideas, facilitating agility in decision-making and adapting to evolving circumstances.

How to implement Fist to Five successfully

To successfully implement Fist to Five, certain prerequisites and organizational requirements should be considered. 

Understanding organizational change adoption is vital, as it allows the method to be tailored to specific needs and dynamics. This includes creating an environment where collaboration and consensus-building are encouraged and where the input of all team members is valued.

A unified communication solution also plays a critical role in the successful implementation of Fist to Five. Team members must be aware of the importance of strong consensus building and understand how their active participation can contribute to better decision-making. 

Clear communication channels should be established to facilitate open dialogue and ensure that concerns and ideas are effectively shared and addressed.

In situations where voters’ concerns are unmet, it is essential to have mechanisms to remedy the situation. This may involve revisiting the proposal, engaging in further discussion and negotiation, or exploring alternative solutions that accommodate the team’s needs. 

Additionally, if a deadlock is reached where a consensus cannot be achieved, the option of conducting another vote can be exercised. This allows for a reassessment of the proposal and allows one to consider fresh perspectives and potential alternatives.

This approach values and integrates diverse perspectives, ensuring that decisions are well-rounded, comprehensive, and reflective of the team’s collective wisdom.

Fist to Five – A Qualitative Approach to Consensus Voting

When it comes to consensus voting, the qualitative approach offered by methods like Fist to Five proves to be superior and more advanced compared to quantitative voting methods. 

Traditional quantitative voting methods, based solely on numerical calculations or majority rule, often overlook the diverse range of perspectives and ideas within a team. This can lead to decisions that lack depth, fail to address critical concerns, and hamper the organization’s overall progress. 

In contrast, Fist to Five allows team members to express their level of agreement or disagreement on a spectrum, enabling a more comprehensive understanding of the group’s sentiment and facilitating meaningful discussions.

Smooth team dynamics are essential in any organization, particularly in the era of digital transformation where agility is the key to driving business value. 

By emphasizing the importance of open communication, nuanced perspectives, and effective collaboration, Fist to Five enables teams to make better-informed decisions and cultivate a culture of inclusivity and adaptability.

Fist to Five FAQs

Q: Is 100% consensus necessary in Fist to Five voting?

A: No, 100% consensus is not required in Fist to Five voting. The goal is to reach a general sense of agreement or support within the team rather than requiring unanimous agreement.

Q: Can we use fractional votes in Fist to Five voting?

A: Yes, fractional votes like 3.5 or 4.5 can be used in Fist to Five voting to represent a moderate level of support or opposition, indicating that someone is leaning towards a particular position but not fully committed.

Q: How is the final decision made in Fist to Five voting?

A: The final decision in Fist to Five voting depends on the level of agreement among team members. The facilitator may use the vote tally as input for further discussion or negotiation to strive for a resolution that satisfies most team members.

The post What Is Fist To Five? Benefits, Process & Implementation Techniques appeared first on Digital Adoption.

The plus side is the powerful abilities it grants to organizations for automation and customer success. Still, the downside is generative AI risks, which you must consider before AI digital adoption.

In January 2023, ChatGPT, the generative AI tool, became the most popular IT strategic trend and recorded five million users in the first week of release.

It is essential to ask whether these users and subsequent users of generative AI tools considered the risks before making this tool part of their daily workflow. 

To help you understand the top ten generative AI risks and learn how to stay safe, we will explore the following topics:

• How significant are generative AI risks?
• What are the top 10 generative AI risks?
• How do you stay safe from generative AI risks?
• What use cases show the risks of generative AI?
• How will generative AI impact the business world in the future?

How significant are generative AI risks?

Significant generative AI risks depend on a few factors, but it mainly relates to how the user interacts with the tool, their knowledge, and what data they input. 

When establishing the significance of these risks in your organization, ask yourself these questions:

• How familiar is our organization with the usage terms of the generative AI tool we are considering?
• Do we enter any sensitive employee or customer data into generative AI tools?
• Are we trained on how to use generative AI safely and avoid risks, and have we looked at artificial intelligence statistics so we understand its capabilities?
• Do we have a usage policy on using generative AI and dealing with potential risks?
• What special considerations should we make based on our field, such as ChatGPT insurance or ChatGPT sales?

Consider these questions to establish the significance of the risks of generative AI to your organization. 

What are the top 10 generative AI risks (with examples)?

Generative AI: The Big Risks (and Some of the Best Uses)

There are ten generative AI risks. See these risks below, with examples to illustrate what they look like, allowing you to prepare for them as you encounter them.

1. Data and security leakage

Inputting sensitive third-party or internal company information into ChatGPT integrates it into the chatbot’s data model, exposing it to others with relevant queries. 

Doing so poses the risk of data leakage and could violate an organization’s data retention policies.

Example

Avoid sharing details about an upcoming product, including confidential specifications and marketing strategies, that your team is assisting a customer in launching with ChatGPT. This precaution helps mitigate the potential for data leakage and security breaches.

2. Intellectual property complexities

Deciphering ownership of code or text generated by ChatGPT can be complex. As per the terms of service, the output is the responsibility of the input provider. 

However, complications may arise if the output includes legally protected data from other inputs that may not follow AI compliance practices.

Copyright problems may also emerge if generative AI is used to create written material derived from copyrighted property.

Example

Consider a scenario where a user requests ChatGPT to create marketing material, resulting in an output that includes copyrighted content from external sources. 

These outputs lack proper attribution or permission, posing a potential risk of infringing upon the intellectual property rights of the original content creators. 

Such actions could result in legal consequences and damage the company’s reputation.

3. Limitations on AI development

Some generative AI’s terms of service explicitly forbid developers from using it to build other AI systems. 

Such usage could hinder future AI development initiatives, primarily if the company operates in that domain.

Example

Imagine a company specializing in voice recognition technology aiming to enhance its current system by integrating ChatGPT’s natural language processing capabilities. 

The explicit prohibition in ChatGPT’s terms of service challenges realizing this enhancement within the specified restrictions.

4. Open-source license compliance

Suppose some generative AI utilizes open-source libraries and incorporates that code into products. In that case, there’s potential for violating Open Source Software (OSS) licenses like GPL, leading to legal complications for the organization.

Example

For example, suppose a company employs ChatGPT to generate code for a software product, and the origin of the GPT training data is unclear. In that case, there’s a risk of violating terms in open-source licenses associated with that code. 

This action may result in legal complexities, including accusations of license infringement and the potential for legal action from the open-source community.

5. Confidentiality and liability concerns

Revealing confidential customer or partner information may violate contracts and legal obligations. 

If ChatGPT’s security is compromised, exposing confidential content poses risks, endangering the organization’s reputation and leading to legal liabilities.

Another risk involves staff using ChatGPT without proper training or IT approval employing shadow IT or shadow AI practices. This action makes monitoring and regulating the AI tool’s usage challenging.

Example

Imagine a healthcare organization using ChatGPT for patient inquiries. 

Sharing confidential patient details, like medical records, with ChatGPT may violate legal obligations and infringe on patient privacy rights under laws like HIPAA in the United States.

6. Research bias

AI system biases can stem from various sources, including skewed training data, flawed algorithms, and unconscious human biases. These biases may yield discriminatory or unjust outcomes, harming users and undermining trust in AI solutions. 

AI systems like ChatGPT may manifest inaccurate information due to demographic, confirmation, and sampling biases.

Example

For instance, if historical business data carries gender bias, ChatGPT might inadvertently perpetuate these biases in responses. 

This bias can distort representations of research output and result in low-quality research regarding an enterprise’s recruitment and retention history.

In chatbot applications, ChatGPT may provide inaccurate information to customers.

7. Unclear international law privacy and compliance

Leveraging generative AI’s capabilities, malicious actors can exploit it to craft malware, create content for phishing attacks and scams, and execute cyber assaults with dark web-sourced data. 

Example

For example, ChatGPT could collaborate with bots to generate deceptive fake news articles and misleading content, deceiving readers.

8. Crime-as-a-service (CaaS)

Generative AI could accelerate the creation of no-cost malware, making crime-as-a-service more convenient and profitable. 

Example

For instance, cybercriminals might misuse ChatGPT to generate abundant spam messages, overwhelming email systems and disrupting communication networks.

9. Model vulnerability

Model security is crucial as AI faces vulnerabilities, including adversarial attacks.

Example

Attackers manipulate inputs to yield incorrect outputs, risking significant consequences. Designing and developing secure models is vital to resist such threats.

10. Explainability

AI systems, at times, obscure decision processes, complicating understanding. Transparency absence breeds mistrust, challenging technology credibility.

Example

When you use a chatbot to streamline your customer service but don’t know why ChatGPT leads customers to specific undesirable answers, it makes it difficult to understand how to redirect how this tool guides customers. 

How do you stay safe from generative AI risks?

Follow these strategies to stay safe from generative AI risks. 

To ensure safety using generative AI, follow these five strategies, starting by regularly reviewing the privacy policy and terms of use.

1. Carefully examine generative AI privacy policy and terms of use 

Carefully review ChatGPT’s privacy policy and terms of use before sharing personal information with generative AI tools.

Bookmark these documents for regular reference, as they might change without prior notice.

Refer below for a list of privacy policies and terms of use for the most popular generative AI tools:

• BARD generative AI additional terms of service
• PaLM generative AI additional terms of service 
• Claude terms and conditions
• ChatGPT privacy policy 

2. Deactivate chat history and model training

Safeguard your ChatGPT conversations by turning off chat history and model training in your ChatGPT account.

Opt out of using your data for OpenAI’s model training by clicking the three dots at the bottom, going to Settings > Data controls, and switching off “Chat history & training.”

Remember that even with opting out, your chats are stored on OpenAI’s servers for 30 days, accessible to staff for abuse monitoring.

3. Validate ChatGPT’s responses before considering them as facts

ChatGPT may unintentionally produce inaccurate information, commonly called “hallucination.”

If you plan to depend on ChatGPT’s answers for critical matters, validate its information with authentic citations through thorough research.

What use cases show the risks of generative AI?

It is helpful to examine risk use cases for generative AI to understand how these risks work in practice, as it will help you combat these risks and stay safe. 

Use case 1: Data scientists

Generative AI allows data scientists to produce and share data to train models without risking personal information. 

Risks for this use case

Generative AI introduces data poisoning, deobfuscation, and adversarial machine learning threats. 

The associated risk relates to the reverse-engineered synthetic data generation model, allowing adversaries to identify the source data used.

Use case 2: IT

Programmers use large language models (LLMs), a form of generative AI, to find errors in code and automatically generate documentation. 

Risks for this use case

This step introduces data exfiltration, data leakage, and data integrity threats, while documentation produced can risk revealing important system details that a company wouldn’t usually disclose.

Use case 3: Marketing

AI text generators allow marketers to produce rough copy drafts for campaigns instantaneously. 

Risks for this use case

Doing so introduces data leakage, data exfiltration, and competitive intelligence threats. Risks include public relations/client issues related to the release of text due to poor oversight and governance processes before release.

How will generative AI impact the business world in the future?

Generative AI is a relatively new technology, but it has become popular due to its cutting-edge capabilities, which will evolve quickly. 

Consider how generative AI will impact the future to remain competitive. 

LLM plugin ecosystems will enhance capabilities

Generative AI providers, such as OpenAI, are introducing plugins to enhance the core capabilities of LLMs, tailoring them to specific tasks. 

The plugin ecosystems facilitate AI integration into workflows, streamlining the deployment of AI-based solutions for diverse applications.

Emergence of open-source LLMs

Open-source LLMs are on the rise, offering alternatives to the initial proprietary models from OpenAI and others. 

For CIOs, it means increased control over data and AI operations, but it necessitates heightened expertise in model management, maintenance, governance, and hardware infrastructure.

From generalized models to specialized

The initial surge of generative AI introduced versatile models proficient across various tasks but faced challenges in specific domains. 

As generative AI focuses on specific industries, it will create purpose-specific models, enhancing proficiency in fields like banking, insurance, and HR by aligning with the unique language of these specialized areas.

Stay ahead of generative AI risks with proactive measures

Proactive measures are paramount to stay ahead of generative AI risks. 

These measures involve thorough reviews of privacy policies, deactivating chat history, and verifying responses for accuracy. 

Embracing transparency, avoiding sensitive information input, and understanding model ownership contribute to a robust defense. 

Stay vigilant, navigating the evolving landscape with informed precaution, and you will reduce the negative impact of generative AI risks while reaping their benefits.

The post What Are The Top 10 Generative AI Risks (+ How To Stay Safe)? appeared first on Digital Adoption.

These four values are reflected in the concerns of US adults in 2023, reporting that 74% are concerned that AI will negatively impact personal privacy and 70% are concerned that AI will lead to the spread of disinformation. 

The human-centered approach tries to offset these concerns through user-focused AI digital adoption, implementation, and design, as well as streamlining AI risk management.

To help you understand what human-centric AI is and how to implement it, this article will explore the following topics:

• What is human-centered AI?
• Why is it important today?
• What are the human-centric AI values?
• What are the advantages and disadvantages?
• Industry-specific use cases for human-centric AI
• How to implement human-centered AI into your workflow

What is human-centered AI?

Human-centric AI prioritizes human values, needs, and well-being in the design and application of artificial intelligence. It emphasizes transparency, explainability, fairness, and privacy, ensuring AI tools are beneficial and trustworthy. 

By focusing on user control, safety, and ethical considerations, human-centric AI seeks to avoid harmful consequences and biases. It champions accountability for AI actions and promotes inclusive design that respects diverse perspectives. 

In short, human-centric AI ensures AI technologies serve as beneficial tools for individuals and societies rather than causing harm or unintended consequences.

Why is human-centered AI important today?

Human-centric AI becomes ever more critical as enterprises use generative AI tools like ChatGPT and Google Bard more. 

To remain competitive, businesses must adopt AI, but they should also be mindful of its potential negative effects on their staff. The urgency to adopt AI is highlighted by projections indicating that the AI market value could reach $308 billion by 2026.

The three primary reasons for the significance of human-centric AI are:

1. AI, on its own, lacks the nuances of human creativity and innovation. Directing its output towards human perspectives guarantees its relevance and usefulness.

2. While AI has the potential to supplant human roles, especially in customer service, human-centric AI serves as a vital bridge, preserving the indispensable human connection.

3. Ensuring that AI outputs are beneficial requires consistent human oversight. Human-centric AI refines this interaction, making AI systems more aligned with human needs and comprehension.

What are the human-centered AI values?

Phrases like ‘human-centric AI’ can sound can sound idealistic and may be difficult to realize without clearly defining the underlying values.

Consider the values below to understand human-centric AI.

Fairness and lack of bias

AI system biases can stem from various sources, including skewed training data, flawed algorithms, and unconscious human biases. These biases may yield discriminatory or unjust outcomes, harming users and undermining trust in AI solutions. 

AI systems like ChatGPT may manifest inaccurate information due to demographic, confirmation, and sampling biases.

Security

Inputting sensitive third-party or internal company information into ChatGPT integrates it into the chatbot’s data model, exposing it to others with relevant queries. 

Doing so poses the risk of data leakage and could violate an organization’s data retention policies.

Ethical implementation

The rapid progress and incorporation of generative AI have prompted numerous ethical concerns regarding the new and extensive human-computer interaction, use, and continuous expansion. 

Ethical AI implementation tries to regain human control of digital AI tools by implementing AI by tackling the following issues by prioritizing human values:

• Job displacement.
• Inquiries about research bias.
• Worries about consumer data privacy.
• Consent for data usage in language learning tools.

Reflect on these ethical considerations to ensure the responsible utilization of generative AI tools.

User-focused design

Building AI with the user in mind is crucial for meaningful and seamless integration into daily life. 

User-centric design ensures that AI aligns with human needs, preferences, and behaviors, fostering user acceptance and engagement. 

This approach not only enhances user experience but also maximizes the positive impact of AI on individuals and society as it produces human-centered outcomes by making it easy to create human-centric inputs. 

What are the advantages of human-centric AI?

There are many business benefits to using human-centric AI, as well as it being better for the wellbeing of your staff in the short and long term. 

Informed Decision-Making

Human-centered AI aims not to replace humans but to augment our capabilities through intelligent, human-informed technology using adaptive AI.

Combining NLP machine learning precision with human input and values empowers businesses (specifically, their human assets) to make informed decisions and devise clearer strategies to address challenges.

Reliability and Scalability

Human-centered AI harnesses human thinking abilities, enabling ideas to scale for more extensive data requirements and avoid data silos. 

While AI serves to assist humans, its effectiveness suffers limits without human input and comprehension. 

A human-centric AI approach shares the computational load with technology, utilizing emotional and cognitive input from humans. 

This approach facilitates expanding processes and information on a larger scale without compromising data integrity or escalating human resource expenses.

Enhanced Software and Product Development:

Applying behavioral science principles to technology through human-centered AI allows developers and designers to delve into user behavior and subconscious patterns. 

This action results in creating products and services offering more satisfying, informed, enriching, and, in the case of platforms like Instagram or games, addictively rewarding user experiences.

What are the disadvantages of human-centric AI?

Despite its advantages, human-centric AI still carries some disadvantages that affect all forms of AI. 

Job displacement 

Despite its best attempts, any form of AI, even AI with a human-centric approach, can lead to job losses as this technology can make some roles obsolete. 

Resource intensive

Much like psychology-focused change management models, human-centric AI can involve more time and effort while staff receive training on correctly using it. 

Less emphasis on efficiency

Because human-centric AI focuses on user design and ethics, it does not exist to maximize profits or efficiency. 

Other forms of AI may extract higher revenue, though they may lead to burnout. 

Industry-specific use cases for human-centric AI

Understanding human-centric AI is much easier when you see it utilized in use cases. 

See the examples below to strengthen your understanding of these types of AI that can teach you that using tools that utilize machine learning doesn’t mean your employees have to behave like machines. 

1. Healthcare

Human-Centered AI enhances efficiency in the healthcare sector for patients, doctors, and professionals. 

The algorithm analyzes diverse healthcare data, organizing it to reveal insights, patterns, and new drug applications, as demonstrated in developing a COVID-19 treatment. 

It organizes clinical trials, medical claims, and images effectively.

2. Human Resources

Organizations facing bias allegations in hiring can adopt Human-Centered AI to eliminate biases. Utilizing job-related data in applications ensures hiring decisions prioritize diversity, fostering an inclusive hiring process.

3. Education

AI significantly influences teaching and online education and optimizes the utilization of data science. 

Human-centered AI aids educators in course creation, student assessment, time-saving, and task automation, catering to individual student needs.

4. Cybersecurity

Basic AI detects network intrusion, fraud, hacks, user authentication, and spam. 

Human-centered AI systems anticipate attacks, fortifying security preemptively.

5. Renewable Energy

Human-centered AI is essential for harnessing renewable energy. It manages decentralized grids, balances, stores, and optimizes real-time electricity demands and supply. 

Gas turbines with attached sensors linked to AI systems adjust fuel valves, ensuring low emissions and informed decisions to reduce environmental impact.

How to implement human-centered AI into your workflow

Follow these steps to implement human-centric AI into your organization’s workflows. 

1. Prioritize user experience

Begin with research to grasp the user experience and pertinent data for interactions. Utilize methods like surveys, focus groups, and customer interviews. Apply these insights to craft AI applications.

2. Build human-centric AI applications

Develop solutions aiding users in task completion. These solutions are versatile, fitting into various platforms like apps, websites, ads, or mobile devices.

3. Deploy human-centric AI solutions

Extend these solutions across multiple touchpoints, ensuring easy user interaction for task assistance or information-seeking related to desired products/services.

4. Collect feedback, review, and adjust

Assess solution effectiveness by constructing a prototype. Monitor user interactions, purposes, and satisfaction levels to gauge the quality of their overall experience.

Adopt human-centered AI for outstanding employee experience

Embracing a Human-centered AI approach transforms the employee experience, fostering a workplace where technology aligns seamlessly with human needs. 

By prioritizing user-centric design with a human-centered approach, AI applications enhance task efficiency, decision-making, and digital employee experience. 

This approach ensures that technology becomes a supportive ally, minimizing biases in hiring processes and promoting a diverse and inclusive work environment. 

Adopting Human-Centric AI and the neural networks they utilize alongside human expertise enriches the overall employee experience, driving productivity and well-being.

The post What Is Human-centered Artificial Intelligence? appeared first on Digital Adoption.

However, recent insights from Gartner suggest otherwise, emphasizing that job manageability might play a more significant role in ensuring your success and that of your team.

Imagine a corporate world where nearly eight out of ten employees expect more support from their managers, whose roles have become increasingly complex and demanding. This isn’t a hypothetical situation— it’s the current state of the workplace as backed by Gartner’s data.

In this article, we’re going to distill the research and insights from Gartner’s reports, and together we’ll reflect on the importance of manageability over skills development and how you can implement strategies to enhance your effectiveness in the ever-evolving corporate environment.

What is job manageability?

Job manageability refers to how manageable a job is, with a particular focus on managerial roles. It relates to how effectively you can conduct your responsibilities with the resources and support available. 

Picture yourself juggling—your workload, autonomy, resources, support, and clarity are all in the air. If you’re managing your job well, you’re keeping these elements in motion smoothly, not just in fleeting instances, but as a constant practice.

Understanding job manageability

Your effectiveness as a manager is crucial—it ripples through your team, significantly boosting performance, engagement, and well-being. 

However, there are many factors that can impact your effectiveness. You are likely spending more time on project management than on leading and developing, with Garnter’s data suggesting nearly half of your peers are reporting the same. 

While this issue isn’t new, Gartner’s research reveals a notable correlation: Managers who view their roles as manageable tend to be markedly more effective. To unpack this further, Gartner has highlighted several critical insights:

• Your ability to effectively manage your workload, coupled with organizational support in resetting role expectations and simplifying tasks, can make your job 1.4 times more manageable.
• When you self-discover your fit for your role, your chances of finding your job manageable nearly double. 
• Habit-building within your organization can also lead to a significant improvement in job manageability.

So, with these insights in mind, what are the key elements that define job manageability and make a manager’s role not just doable but sustainable for long-term success? 

Workload

It’s not merely the volume but the complexity of the tasks that counts. 

Manageability means being able to tackle your responsibilities without feeling perpetually on the brink of burnout. 

Consider a day packed with meetings that leaves you with no time for reflection or team development— this is a sign your workload might be tipping the scales.

Autonomy

This defines your capacity to make work-related decisions. 

When you have the freedom to decide the ‘how’ and ‘when’ of your tasks, your job’s manageability improves. 

For example, choosing to delegate tasks to team members to better focus on priority areas where your expertise is crucial demonstrates autonomy.

Resources

Adequate resources mean having access to the right tools and people. 

This could look like being equipped with the latest project management software or leading a team that has the necessary skills to fulfill the demands of a project.

Support

Support encompasses the help you receive from your organization, including leadership and HR. 

Effective support can manifest as a mentor who helps navigate complex leadership issues or an HR department that resolves team conflicts efficiently.

Clarity

Having a clear understanding of your role and what’s expected of you is essential. 

Clarity in expectations and objectives means you’re better equipped to meet and surpass them.

The direct benefits of job manageability

Your well-being thrives when your job is manageable. 

Consider this: individuals who report manageable workloads experience a significant 12.5% increase in physical and mental health. This means you’re likely to feel less stressed, be in better health, and maintain a more optimistic outlook on life, which can ripple out to affect all areas of your performance positively.

Manageability plays a crucial role in your work-life balance. With a job that fits within the reasonable confines of your capabilities and time, work doesn’t have to spill into your personal life. 

You can wrap up your day with a satisfying sense of completion, knowing that you’ve accomplished what you needed to, and then disconnect to recharge.

Here are five ways job manageability directly enhances your professional life:

1. Sustained performance

You’re more likely to maintain high-performance levels without burning out, as a manageable job can mitigate stress even in high-stakes roles.

2. Enhanced engagement

With a 13.4% increase in engagement for employees under effective managers, a manageable job can help you stay invested in your tasks and more responsive to your team’s needs.

3. Higher retention 

Employees with manageable jobs are 3.2 times more likely to intend to stay with their current employer, indicating that manageability can foster loyalty and reduce turnover.

4. Elevated team success

With employees 15.4 times more likely to be high performers under effective managers, it’s evident that your ability to manage well translates to your team’s success.

5. Personal health and well-being

The 12.5% boost in well-being among employees with manageable jobs shows a clear link between job manageability and personal health.

By prioritizing job manageability, you’re not only setting yourself up for success but also paving the way for a healthier, more engaged, and dedicated team. 

The emphasis on manageability transcends mere productivity— it’s about nurturing an environment where you and your team can consistently perform at your best.

The indirect benefits of job manageability

When your job is manageable, it doesn’t just improve your direct output and well-being— it also sets off a chain reaction of positive effects within the workplace. 

The reach of manageability extends far into the realms of engagement, workplace culture, and adaptability.

Here are three indirect benefits of job manageability:

1. Fostering engagement

Engagement at work often hinges on the feeling that your tasks and responsibilities are within your control. 

When you’re not overwhelmed, you can dive deeper into your projects, contributing innovative ideas and demonstrating a greater level of commitment. 

This sense of engagement is contagious— when you’re invested, your enthusiasm can motivate your peers, creating a dynamic and collaborative team environment.

2. Cultivating a positive workplace culture

Job manageability contributes to a positive workplace culture by building a foundation of trust and support. 

A manageable workload implies that your organization values your time and well-being, which can lead to increased job satisfaction and a shared sense of purpose. 

In a culture where manageability is the norm, you and your colleagues are more likely to have the energy to support each other, celebrate successes, and work through challenges collaboratively.

3. Adapting to change and uncertainty

In an ever-changing work landscape, the ability to adapt is crucial.

A manageable job provides the bandwidth necessary to navigate uncertainty without succumbing to stress. 

When you’re not constantly at capacity, you can flexibly shift gears to address new challenges, learn additional skills, or re-prioritize tasks as needed. This resilience is invaluable, both for individual career progression and for the organization’s ability to stay agile in a volatile market.

The problem with over-emphasizing skill development

The current trend in many organizations is an overemphasis on constant upskilling. 

While staying current is undoubtedly important, an overzealous focus on learning new skills without addressing manageability can lead to burnout and diminished returns. 

Skills are not developed in a vacuum; they need an environment where they can be nurtured and applied. Without manageability, even the most well-intentioned upskilling initiatives can backfire, leading to frustration and a sense that the time and resources invested in learning are wasted.

A more sustainable approach recognizes that skill development and job manageability are interdependent. 

By fostering a manageable workload, organizations not only enhance the well-being of their employees but also set the stage for continuous, effective professional development. 

Manageability creates an environment where learning is integrated with doing, where employees can experiment with new methods, and where innovation is born from the ability to apply skills in a thoughtful, impactful manner.

How to integrate job manageability and career planning

Understanding and integrating job manageability into your plans can serve as a significant driver for both satisfaction and success as you navigate your career path.

Here are ten strategies and approaches that you, and the organizations you are part of, can employ to enhance job manageability.

Individual strategies for manageability

1. Assess your workload: Regularly evaluate your tasks and responsibilities. Are they reasonable? Do you have the necessary resources? If not, it might be time to speak with your manager about realigning expectations or securing additional support.
2. Seek autonomy: Advocate for autonomy in your role where possible. Autonomy can empower you to work in ways that suit your strengths and can make your job feel more manageable.
3. Build a support network: Cultivate relationships with colleagues and mentors who can provide guidance and assistance. A strong support network can ease the burden during challenging periods.
4. Develop clear role clarity: Work with your leadership to establish clear expectations for your role. Role clarity can eliminate uncertainty, allowing you to focus on your tasks with confidence.

Organizational approaches

1. Reset role expectations: Organizations should continuously reassess the scope of managerial roles to ensure they are realistic and aligned with individual capabilities.
2. Simplify managerial tasks: Introduce tools and processes that simplify managerial responsibilities. This can reduce the “work about work” that often burdens managers.
3. Invest in development programs: Tailor manager development programs to focus on practical skills that enhance manageability, such as delegation, prioritization, and stress management.

Policy recommendations

1. Industry standards for manageability: Industry leaders can create standards and benchmarks for job manageability, helping organizations to understand and measure how well they are doing.
2. Government role in workforce well-being: Policymakers can incentivize companies to prioritize job manageability through legislation or tax benefits. This could encourage investment in training programs and the development of more manageable job designs.
3. Promote transparency and accountability: Encourage organizations to be transparent about their efforts to improve job manageability and hold them accountable for their progress.

Job manageability: Redesign your role for success

In summing up our exploration of Gartner’s research on job manageability, we’ve underscored its pivotal role in shaping sustainable career trajectories. 

We’ve seen that manageability is a substantial factor that enhances work-life balance, fosters engagement, and sustains high performance. 

It’s clear from the data that while skills development remains important, the capacity to effectively manage one’s job is five times more influential in improving managerial effectiveness.

You’ve been equipped with the knowledge that job manageability extends far beyond the simplicity of tasks— it encompasses workload, autonomy, resource availability, support, and clarity. And you’ve discovered that when these components are in alignment, the ripple effects are profound, leading to better job performance, greater employee satisfaction, and a stronger, more resilient organizational culture.

For individuals, it’s crucial to recognize the power you hold to shape your job’s manageability. 

Engage in open dialogues with your leaders, assess your role regularly, and be proactive in seeking the support you need.

For leaders and HR professionals, the challenge is to pivot focus from constantly pushing skills development to fostering an environment where job manageability is a central concern. 

This can be achieved through resetting role expectations, simplifying tasks, and investing in development programs that promote practical, manageable skills.

And finally, for policymakers, it’s essential to step up and play a part in promoting job manageability. By creating incentives for businesses, setting industry standards, and ensuring that the workforce’s well-being is a priority, you can effect meaningful change.

It’s time to move forward with the understanding that our ability to manage our jobs effectively is a cornerstone of thriving organizations and economies.

The post Job manageability: From overwhelmed to overachieving appeared first on Digital Adoption.

A comprehensive tech strategy is essential to any future-ready IT strategy, providing a fundamental framework that guides technology’s role in supporting the business.

Research from Statista shows that many executives recognize technology investments as a valuable competitive advantage and want to reshape their entire business strategies around digital technologies. 

Adopting an appropriate technology framework allows businesses to standardize decision-making, highlight areas of improvement, prioritize tech investments, and streamline system upgrades.

In this article, we will define a technology strategy and explore some common technology frameworks businesses use, including examples of how they have been implemented successfully.

What Is A Technology Strategy?

A technology strategy is a detailed plan outlining how an organization will utilize technology to fulfill its goals and targets. 

The strategy supplements an organization’s overarching IT strategy and comprises key tenets, objectives, and methods related to the role of technology in business advancement. 

This involves determining technology’s prospective application within business environments, including identifying pain points and formulating a roadmap for implementing chosen technologies.

According to the IDC’s Worldwide Digital Transformation Spending Guide, global DX spending will reach $3.4 trillion in 2026, with a CAGR of 16.3% over the next five years.

The scope of a technology strategy transitions from broad to specific, with detailed strategies evolving from broader business ambitions. 

In the process, the technology strategy identifies the required capabilities to achieve these objectives based on the analysis of tangible business scenarios. 

Establishing a clear tech strategy is an essential prerequisite for any forward-thinking business, enabling them to leverage the benefits of technology in the most optimal way.

Why Is A Technology Strategy Important?

According to McKinsey, technology strategies have proven invaluable in helping organizations understand the scale of necessary change and think through interdependencies across various aspects.

Leveraging a strategic technology approach allows businesses to carve out a unique market position, streamline operations, manage risks robustly, utilize data effectively, enhance customer engagement, and prepare for future technological advancements.

Let’s take a closer look at why establishing a technology strategy is so important and some of the benefits that can be realized in doing so:

Competitive Edge

Through the strategic and thoughtful implementation of cutting-edge technologies, businesses can optimize their operations, increasing efficiency and productivity. 

This, in turn, paves the way for the enhancement of product or service quality, enabling organizations to better meet the shifting needs and expectations of their customers. 

An innovative approach such as this empowers companies to secure market dominance and a competitive advantage in the high-octane commercial world.

Operational Efficiency

Implementing a well-defined technology strategy enables efficient automation of routine tasks and seamless integration of various systems. 

This integration leads to the streamlining of processes, resulting in heightened productivity and cost reduction. 

With the elimination of manual efforts and the optimization of technological capabilities, organizations can improve operations resource allocation and bolster overall performance.

Data-driven Decisions

A well-defined technology strategy not only provides a clear roadmap for technology investments but also facilitates informed decision-making that parallels the strategic objectives of the organization. 

By establishing a comprehensive plan that considers the evolving technological landscape and the specific needs of the business, a strategy enables effective asset allocation and maximizes return on investment (ROI).

It also helps identify emerging technologies, assess their potential impact, and ensure that technology initiatives are in line with the long-term vision of the organization. 

Customer Experience Optimization

Cutting-edge technology tools such as AI and data analytics, when strategically applied, have the remarkable ability to enhance customer interactions in countless ways. 

Leveraging the power of AI allows businesses to uncover valuable insights into customer preferences and behaviors. 

This knowledge enables them to craft personalized experiences that boost satisfaction and cultivate enduring loyalty. 

Future Preparedness

Staying current with the latest emerging technology trends and proactively structuring their integration with a well-crafted technology strategy primes businesses for a future-ready state. 

This approach allows them not only to remain adaptable and relevant but also to seize new opportunities. With a keen focus on innovation, holistic learning, and proactive planning, organizations can position themselves as true digital transformation leaders.

What Is A Technology Strategy Framework?

A technology strategy framework plots the actionable approach a company will take to leverage technology in achieving its objectives. 

The framework provides a concrete roadmap for the acquisition, utilization, and management of technology resources, including hardware, software, and human capital.

The strategy often involves identifying key technology trends relevant to the business, establishing technology-related goals, and crafting action plans to meet these goals. This includes evaluating current technology infrastructure, identifying gaps and pain points, and determining the solutions to remedy them.

Different frameworks emphasize different aspects, such as IT governance, data management, cybersecurity, or digital transformation. 

For instance, the Technology Business Management (TBM) discipline guides organizations in managing and communicating the cost, value, and quality of IT services in a business context. 

A well-defined technology strategy framework ensures technology investments remain aligned with business goals and delivers maximum value. 

Technology Strategy Examples

Cloud Computing, Digital Transformation, and Data Analytics strategies characterize three of the top strategic approaches to technology that many leading organizations are currently pursuing

Let’s take a closer look at these areas of interest:

Cloud Computing Strategy

A cloud computing strategy enables organizations to operate on scalable, flexible cloud-based platforms. It involves moving data storage, processing, and management from on-premise servers to the cloud.

This strategy helps save on infrastructure costs, as companies only pay for the resources they use and can scale up or down based on demand. It also enhances accessibility, as employees can access data and applications from anywhere, anytime, improving collaboration and efficiency.

Depending on the organization’s requirements, they can opt for public clouds for cost-effectiveness, private clouds for enhanced security, or hybrid clouds for both.

Digital Transformation Strategy

A digital transformation strategy completely overhauls business operations by integrating digital technology.

It’s not just about updating systems; it’s about fostering a culture that embraces change, innovation, and continuous learning. 

In this regard, a DX strategy provides businesses with a vehicle for capturing the benefits of technology, delivering superior customer experiences, and creating bleeding-edge products and services.

It also improves operational efficiency by automating processes, enhancing data management, and facilitating real-time communication. However, successful digital transformation requires strong leadership, clear vision, and employee engagement.

As shown by McKinsey research—when organizations undertake a large-scale transformation, their efforts fail about 70 percent of the time.

Data Analytics Strategy

A data analytics strategy leverages advanced technologies to convert raw data into actionable insights.

Businesses can analyze vast amounts of data quickly and accurately by harnessing Big Data, Machine Learning (ML), and artificial intelligence (AI). This strategy enables businesses to forecast trends, optimize operations, and better tailor products or services.

For instance, predictive analytics can forecast customer behavior, while prescriptive analytics can suggest actions to achieve business goals. 

However, a successful data analytics strategy requires quality data, skilled analytics officers, and a culture that sees the value of data-driven decision-making.

Technology Strategy Framework Essentials

Developing and implementing a technology strategy involves steps crucial for aligning technology with an organization’s strategic objectives.

To fully understand the mechanics, let’s take a look at key touch-points essential to a technology strategy framework:

1. Goal Definition: An organization must explicitly outline strategic objectives and the role of technology in facilitating these objectives. Goals could encompass enhancing operational performance, boosting customer service quality, or reimagining products or services.
2. Technology Review: Investigate the existing technology environment within the organization and the larger industry. This entails cataloging current technology resources, evaluating their efficiency, and exploring emerging technologies that could provide a competitive edge.
3. Gap Recognition: Pinpoint any discrepancies between the organization’s existing technology capabilities and the requirements necessary to meet strategic goals. These gaps could be present in hardware, software, data management, security measures, and skill sets, among other areas.
4. Solution Exploration: Recognize potential remedies to address the identified deficiencies. Solutions could involve acquiring new technology, upgrading current systems, outsourcing, and cultivating new organizational competencies, among other initiatives.
5. Plan Development: Devise a comprehensive plan for deploying the identified solutions. The plan should encompass a timeline, necessary resources, responsibilities, and crucial performance metrics (KPIs) to track progress.
6. Implementation: Execute the devised plan, track advancement against the KPIs, and modify the plan based on feedback and evolving circumstances.
7. Ongoing Assessment: Regularly scrutinize and assess the technology strategy to verify its effective alignment with the organization’s strategic goals. Modify the strategy in response to evolving business requirements, technological advancements, and insights gained from implementation.

What’s Next For Technology Strategies?

As we look ahead, the potentially infinite potential of evolving technology calls for the constant introduction and reshaping of tech strategies for delivering value in both business and wider social zeitgeists.

IT leaders and CIOs can anticipate a landscape dominated by an accelerated pace of innovation, where agility and adaptability become essential survival skills for those companies chasing state-of-the-art status.

Artificial intelligence and machine learning will continue to evolve, offering organizations unprecedented capabilities to analyze data, automate processes, and improve decision-making. 

The adoption of cloud technologies will continue to surge, providing organizations with greater flexibility, scalability, and cost efficiencies. This will be complemented by the rise of edge computing, bringing computation and data storage closer to where it’s needed, improving response times, and saving bandwidth.

Cybersecurity, too, will take center stage, with solutions becoming more nuanced and complex as increasing digitization and connectivity raise new challenges and threats.

“It is our responsibility to take all measures possible upfront to ensure we increase our resilience over the years for an improved cybersecurity landscape in 2030 and beyond,” says Juhan Lepassaar, Executive Director at ENISA (European Union Agency for Cybersecurity).

The role of IT leaders and CIOs is set to become more strategic. They’ll be expected not just to manage technology but to drive business value, foster innovation, and continually transform. 

The emphasis will shift from merely keeping the lights on to using technology as a competitive differentiator and a catalyst for growth.

Ultimately, the future of technology strategies will be shaped by those who can blend technical acumen with business savviness and understand that at the heart of every tech strategy lies the goal of creating value for the organization, customers, and stakeholders.

The post What Is A Technology Strategy? Frameworks, Examples & Implementation appeared first on Digital Adoption.

It evokes excitement but also carries a hint of fear. Any type of transformation holds the potential to bring prosperity, happiness, and profitability to an organization. 

However, beneath the surface of this transformative journey, a subtle threat lingers that things may not unfold as planned.

That’s why you must be careful about transformation programs in any organization. Whereas organizational evolution happens naturally, transformation programs will take place in a relatively short space of time. 

This article will introduce you to transformation programs in a business context. 

With a particular focus on digital transformation programs, we will:  

• Explain what the phrase “transformation program” means 
• Introduce five key examples of transformation programs from the world of digital transformation
• Examine some research-based advice about avoiding significant problems in your change program. 

Amidst rapid change, implementing a successful transformation program becomes a pivotal strategy to maintain a firm grasp on business success.

What Are Transformation Programs? 

To get us started, we’ll outline some of the fundamental knowledge of transformation programs: the meaning of the term, their objectives, and the challenges they involve.

The meaning of transformation programs 

In April 2023, a McKinsey analysis pointed out that “transformation has been a catchall term for how organizations make the right moves to achieve their full potential.” 

In other words, a transformation program refers to how organizations can adapt to new circumstances: change initiatives, business transformation, digital transformation, organizational change, and more. 

But if transformation programs come with risks and benefits, why do managers and leaders go through with them?

Transformation Programs: Common Objectives 

Like any difficult decision, transformation programs are about good business: increasing revenue, improving profit margins, and reducing costs. 

A transformation program may target some more specific areas. For example:

• To improve customer experiences 
• To reduce the number of staff employed 
• To make more sales 
• To appeal to a different portion of the market
• To continue to meet demand while scaling  

The good news is that “transformation” doesn’t simply entail “terminating all your employees.” In the 2020s, businesses are adapting to keep pace with significant shifts in commerce. 

Transformation projects sometimes have a bad reputation. Transformation efforts won’t magically fix all of the problems in your organization. And if your preparation is inadequate, they might cause you a lot of fuss (without much in the way of a return).

Fortunately, analysts are already familiar with some major challenges in today’s business environment.

Common Challenges for Transformation Programs 

The challenges for transformation programs come as a surprise to newbie transformation agents. However, if you ask some experienced transformation agents, they will tell you these challenges are not new. 

The following challenges are common across various transformation programs: 

• Human resistance to change. If your drivers have been using paper to sign out their deliveries for years, how will they feel about using a tablet?
• Poor communication. If you didn’t tell everyone that the new HR system was going live next Wednesday, can you be surprised that no one is using the new software on Thursday?
• Insufficient training. Transformation programs will often make processes simpler. However, there is a period of adaptation where front-line employees are getting used.  
• Rapid roll-out.  When you’ve discovered a brilliant solution to an old problem, rapidly rolling the whole thing may be tempting. It’s important to leave enough time to address the challenges of transformation programs.
• Unintended consequences. Quick changes may disrupt existing processes, creating unforeseen bottlenecks or inefficiencies.

It’s easy to see these problems when you look back on a failed project. But they’re very hard to predict! 

The good news is that a clear strategic plan can be enough to secure the success of your project. 

We will talk more about the ingredients of a successful project later in the article.

Five Examples of Transformation Programs in Action

Although “Transformation program” can refer to any kind of change project, we are limiting ourselves to digital transformation programs in this article. 

Perhaps these are some of the most important change programs you’ll see in 2023.

So you’re thinking about transformation programs. What does it look like? What might it be? 

Let’s check out five quick examples:

Replacing legacy systems with new technology

“Legacy system” can apply to many types of outdated technology.

It may be a move from outdated digital infrastructure to more efficient systems. But it might also involve a substantial shift from paper-based processes to computerized solutions.

Surprisingly, even as we enter the final stretch of 2023, some companies are still in the early stages of embracing full-scale cloud adoption. 

This transformation endeavor presents an opportunity to harness the capabilities of cloud technology for enhanced scalability, flexibility, and data accessibility, and it is a crucial step for businesses to remain competitive and adaptable in the evolving digital landscape.

Transformation programs can be a great way to “start over” when it comes to older technology.

Creating a one-stop customer self-service portal

Today’s customers, whether they are individuals or businesses, have heightened expectations for seamless and efficient experiences.

Achieving this requires robust software solutions, thorough testing procedures, and seamless integration with a spectrum of services. Developing a comprehensive self-service portal empowers customers to access information, resolve issues, and perform transactions independently. 

Such a transformation endeavor enhances customer satisfaction, streamlines operational processes, and strengthens the organization’s competitive edge by delivering the convenience and efficiency that modern customers demand.

Harnessing AI appropriately and effectively

IT leaders have been dealing with the challenges of rogue IT (also known as Shadow IT) for many years. 

Now, there’s a new enemy in town: shadow AI. If you didn’t know, that’s how we talk about all the unauthorized AI applications that employees might use.

Many businesses will need a transformation process to bring AI on board quickly and effectively. It will take planning, risk management, and thoughtful decision-making to ensure that AI gives you a competitive advantage in the years to come.

Introducing an enterprise-wide software platform

Comprehensive software solutions like ERP (Enterprise Resource Planning), HRM (Human Resource Management), or CRM (Customer Relationship Management) packages are some of the most transformative technologies today. They can radically improve your business processes, rapidly returning business benefits across the organization.

However, introducing these packages can be a big deal, including updating existing systems, replacing outdated digital infrastructure, introducing entirely new functionalities, or a vendor switch. 

The details involved in configuring, integrating, and deploying enterprise-wide software platforms underscore the non-trivial nature of this transformation effort, which, when executed effectively, can optimize business processes, enhance data management, and bolster the organization’s overall efficiency and competitiveness.

Implementing a wide-ranging data security

Data security can be a transformation program on its own. However, it should be on your radar whenever you introduce new digital technologies in your business.

This kind of transformation involves looking at and making better the rules and tools for keeping data secure. This includes using special codes to hide data, controlling who can access it, setting up systems to catch any threats, and teaching employees how to keep data safe. 

The main goal is to strengthen the organization’s defenses against the many kinds of online threats and to follow the rules about data protection. This change is important but tough because it needs careful planning and ongoing work to deal with new threats. However, when done right, it reduces the risks of data breaches and makes customers and others trust the organization more.

How to Organize Transformation Programs: Twelve Tips From The Research 

A successful transformation program can distinguish between success and failure in today’s competitive market. But how can you ensure your digital transformation program gives you everything you hoped for? 

To put it simply, you need a digital transformation strategy. There are so many ways to organize digital transformation projects – and many tried-and-tested change management models would work very well. 

But the good news is that business researchers from Morocco have compared all these models and discovered 12 crucial success factors to improve things. 

They outlined the 12 most crucial factors in the success of transformation programs: 

1. Clear vision and strategy for change

2. Change readiness and capacity for change

3. Change team performance

4. Activities for managing change management

5. Resistance management

6. Effective communication

7. Motivation of employees and change agents

8. Stakeholder engagement

9. Leadership and sponsorship

10. Reinforcement and sustainment of change

11. Approach and planning for change

12. Monitoring/measurement

We’d be lying if we said it was simple. 

However, it’s heartening to know that the ingredients of a successful transformation are all there. If you have a project transformation office set up, they can make sense of these challenging priorities. 

To get a clearer idea of how to improve your transformation, you can look at some sector-specific guidance. And on this site, we have a lot of relevant articles! For example, see these articles: 

• Digital transformation programs for financial businesses 
• Transformation programs for the procurement process  
• Educational transformation programs
• Business digital transformation for the airline industry 

Get set for a successful transformation project 

Over the past year, we have witnessed remarkable advancements in the realm of digital technologies and global events. These developments have brought about significant changes, impacting various aspects of our lives. 

For those fortunate enough to have remained unaffected by these changes, it is important to recognize the opportunities they present. However, for the rest of us, it is time to contemplate the scope of our transformation program and embrace the possibilities that lie ahead.

As we have observed, achieving success in the face of these transformations is not akin to rocket science. It requires a thoughtful approach and a clear strategy. Start by formulating a comprehensive plan that considers your industry’s unique challenges and opportunities. Seek sector-specific insights on transformation, understand the trends and emerging technologies, and identify the potential hurdles that lie ahead.

With a solid foundation in place, you will be prepared to rally your team and garner their support for the impending change. Engage them in the process, communicate the vision, and demonstrate the benefits that the transformation will bring. Together, you can navigate the complexities of this ever-changing landscape and emerge stronger and more resilient.

Remember, the path to success may not always be easy. But with the right mindset and a proactive approach, you can transform challenges into opportunities and drive meaningful change in your organization. 

Embrace the journey and let the winds of transformation propel you towards a brighter future.

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