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.

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.

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.

The post Transformation Programs in IT: How to Make The Right Changes appeared first on Digital Adoption.

It’s a real challenge. So it’s no surprise that lead generation teams have been joining forces with AI for years, as a vintage McKinsey report from way back in 2016 shows.  

However, the rise of generative AI has changed everything. Applying AI to sales opens doors to many use cases throughout the customer journey. And lead generation is no exception. Lead generation relies on big databases, repetitive tasks, and routine conversations. 

Generative AI is a natural ally of lead generation. If that’s news to you, this article will give you a rundown of how it works. 

We’ll start by providing a concise explanation of AI in lead generation. Next, we’ll introduce key techniques for leveraging AI in lead gen. We’ll then present an overview of the market’s available AI-powered tools for lead gen. 

Lastly, we’ll explore the significant risks associated with AI lead generation.

AI Lead Generation: The Basics

Lead generation is the process of identifying potential customers for a product or service. 

With AI Lead generation, the sales team applies the power of generative AI to their lead generation activities. AI tools can enhance the full process, from lead capture to outreach to the reactivation of old contact databases. 

AI has been used in sales and lead generation for some time. AI-powered analytics have helped companies use big data sets to discover the most likely prospects for years. AI tools have a track record of supporting efficient, effective, and reliable lead-generation activities. 

When we bring generative AI into the picture through ChatGPT, Bard, and 3rd party software, the benefits of AI for lead generation start to make a huge difference. 

Generative AI means that many tasks can be scaled rapidly and efficiently. Even if you spend monthly subscriptions for the right tools, AI tools can quickly deliver a startling ROI.

Right now, thought leaders in sales are keeping quiet about the limitations of AI-based lead generation. 

After all, everyone’s still in the first wave of hype about this new technology. But the challenges are easy to spot. Sales fundamentally rely on human empathy and connection in a way that the best AI bot cannot emulate. Intuition, networking, and decision-making capabilities are not AI’s strong suit.

Some of the features of AI lead generation 

Lead generation strategies include a wide range of activities. Lead gen professionals must find a target audience to generate leads, qualify leads (with lead scoring tactics), contact qualified leads, undertake lead nurturing tasks, and more. 

Sales and marketing teams may already have lead-generation strategies in place. However, generative AI can enter the process at every stage. Let’s take a look at some important possibilities for AI lead generation. 

Social media scraping

AI can help collect data from social media platforms like LinkedIn. 

With the right prompts, you can use AI to filter LinkedIn contacts by searching their profiles for specific and relevant terms. This helps identify potential leads that align with your criteria, saving both time and effort.

AI can also be employed to extract precise data from a large pool of profiles swiftly. This automated approach is a game-changer, as it accomplishes tasks that could take hours, days, or even weeks in just an instant. 

It’s important to note that while AI streamlines the process, compliance with platform rules is crucial to avoid any potential violations.

Segment leads quickly and effectively

A 2023 McKinsey report on AI in Sales explains that segmentation is one of the core capabilities of AI. With advanced AI algorithms, marketing and sales teams can ” identify segments with unique traits that may have been overlooked in existing customer data.”

Swift processing and deciphering massive datasets unveil valuable insights, identifying distinctive buying patterns and behaviors. 

This data-driven approach enables sales professionals to pinpoint precisely when and how to engage potential customers, tailoring their strategies accurately. 

With Generative AI as their ally, sales teams are better equipped to deliver personalized and compelling sales pitches that resonate with their audience’s unique needs and preferences, ultimately driving higher conversion rates and sales success.

Cold outreach

Once you’ve gathered your contact lists, modern generative AI lead generation tools can take your outreach to the next level. Personalization is the key for any business owner looking to generate leads, especially high-quality ones.

Text-based outreach is made effortless with generative AI. You can use chatbots to craft personalized messages by setting simple parameters. Sending these messages to your leads is as simple as a few clicks.

Another noteworthy advancement lies in AI-generated videos for personalized outreach. Creating a hundred unique videos has become fairly straightforward, enabling you to engage with your leads in a more personalized and impactful manner.

In one surprising statistic, a report from Gartner predicts that 30% of outbound marketing messages will be AI-generated by 2025.” 

Looking at the latest tech, it’s certainly possible. 

Lead generation Chatbots for initial contact

Chatbots are going to revolutionize the whole of the customer journey. But they are especially valuable when it comes to lead generation.

Bots act as initial filters for potential customers, especially cold leads. When a cold lead interacts with your website, the chatbot can swiftly gauge their interest and intent. 

The chatbot determines if the lead aligns with your ideal customer profile through specific questions and response analysis, aiding lead qualification. Should the lead meet the criteria, a seamless handover to a sales representative for further engagement is possible.

This streamlines the lead qualification process and ensures that your sales team spends their time on the most promising leads, ultimately boosting sales efficiency and conversions.

Chatbots are likely to be a major business sales tool in the future. This may seem a bit strange. But we’re not so far away from this reality. 

Reviving a dead database

While AI is gradually becoming integral to the entire lead generation process, it currently holds a unique role for older databases of potential leads.

With a “dead” database in hand, lead generators need some serious power to sift through the results: AI-powered engines are uniquely capable of this task. 

First, they identify segments within the database that show surprising promise. AI aids in swiftly identifying these segments and enables the automation of messages. 

Leveraging AI can help uncover overlooked or dormant opportunities and possibilities. This revitalization process allows you to tap into the full potential of your existing database and engage with high-quality leads effectively.

Database revival uses all the strengths of AI to create great results. But a human being must still operate the tools. 

Experienced lead generation experts, such as Dan Wardrope and Jamie Woods, are demonstrating their expertise and showing us how it’s done. You can see their valuable insights in action here.

AI lead generation tools to make your sales funnel move 

How will you start generating leads with artificial intelligence? The simplest way is with one of many third-party tools. 

When other AI lead-generation efforts fail, they prove to be highly valuable. For instance, scenarios like onboarding new staff, providing specialized training, and implementing prompt engineering from within may yield different results. 

If you’re looking for rapid results, these tools could help you reach your target audience: 

1. Instantly AI: Instantly AI offers artificial intelligence solutions to help businesses automate their processes and improve efficiency.
2. LeadZen: LeadZen is a lead generation company that uses AI to provide high-quality business leads.
3. Lyne AI: Lyne AI develops chatbots for businesses, helping them automate customer interactions and deliver excellent customer service.
4. Smartwriter: Smartwriter is an AI-powered writing assistant that can generate content across various formats, including emails, blog posts, and social media posts.
5. Copilot AI: Copilot AI leverages artificial intelligence to automate sales outreach, helping businesses connect with their target audiences more effectively.
6. High Level: High Level is an all-in-one marketing platform for businesses, combining CRM, email marketing, and other functionalities.
7. Gong.IO: Gong.IO uses AI to analyze sales calls and meetings, providing insights to help sales teams close deals more efficiently.
8. Enrich with AI: Clearbit’s Enrichment tool uses AI to provide businesses with comprehensive data about their customers, helping them make informed decisions.
9. Reachout with AI: Reachout with AI is a platform that uses artificial intelligence to automate and personalize email outreach.
10. bHuman.ai: bHuman.ai is an AI-powered platform that helps businesses build more human-like digital experiences.
11. Task Genie: Task Genie is an AI-powered task management tool that helps teams streamline workflows and improve productivity.
12. Getlead.ai: Getlead.ai is a lead generation platform that uses artificial intelligence to help businesses find and connect with their ideal customers.
13. Chatbros.ai: Chatbros.ai is a chatbot development platform that allows businesses to automate their customer service and improve customer engagement.

There are plenty of obvious advantages to using 3rd party software. 

These tools often bring expertise, advanced algorithms, and extensive data resources that may surpass in-house capabilities. 

Tapping into external AI solutions allows businesses to access more accurate lead insights, faster data processing, and innovative lead generation techniques. This enhances their efficiency in identifying and engaging high-quality prospects.

The risks (and limits) of AI lead generation

Like any business application of AI, AI lead generation mixes opportunities with AI risks. 

These risks of AI, in general, are well-documented. But what about the specific challenges when it comes to AI? 

Before you rush head-first into adding AI to your lead generation processes, consider these weak points: 

• Data scraping is prohibited by the terms of service on many social media platforms, including LinkedIn. If you use ChatGPT or Bard for invasive purposes – you could end up in big trouble with the LinkedIn police!
• Personalization still isn’t perfect. Of course, the developers of AI sales tools boast that their tools produce “real-life” content. But will customers be fooled? Tread carefully if you are using AI for customization.
• Privacy is a major issue. We still don’t know how AI engines use, retain, and re-package data. Mishandling or data breaches can lead to major legal and reputational issues.
• Costs and Investment. Implementing AI solutions can be costly, and businesses may not see a return on investment if the technology is not used effectively—the AI-powered tools listed above all charge hefty monthly subscription fees. 

Is AI the future of the lead generation process? 

Investing in an advanced AI lead generation tool can significantly propel your sales strategy forward.

After all, how many companies DON’T need to generate quality leads regularly? AI brings major efficiencies over traditional methods. 

This doesn’t mean you need to replace all of your sales staff overnight, far from it. 

As we’ve seen, AI tools can be most useful when taking over ONE part of the lead generation process at a time. You don’t need to convert every lead generation task to AI overnight to feel the benefits. 

Reviving a dormant database using AI hacks alone would be sufficient in and of itself.

More and more tools are being rolled out specifically to support lead generation. As the months roll by, finding an application that works well for your business needs will become easier and easier. 

The post AI Lead Generation: A Beginner’s Guide appeared first on Digital Adoption.

So, while AI adoption has quickly grown across many industries, the sector-specific pathways to AI maturity are unique. 

Globally, the financial services industries have emerged as the most significant early adopters of AI solutions. Healthcare and retail are hot on their tails.

In this article, we’ll dive into the realities of AI adoption in several of these key industries. We will:

• Examine the large-scale factors that make a difference to AI adoption rates;
• Summarize the barriers to AI adoption across industries;
• Explain examples, risks, and future plans for AI in the business operations of three key industries (finance, healthcare, and retail).

Since the advent of generative AI in late 2022, businesses have had to quickly get ready for an AI digital adoption process. Now that we have detailed research from international foundations, we’re starting to get a clearer picture of how AI adoption might work in the years to come.

And by the way, although we will mention “AI” in general, this article will focus on the new kid on the block generative AI  – in other words, AI in the age of ChatGPT and Bard.

AI adoption rates: what makes a difference?

As we move towards the end of 2023, why don’t more businesses use AI solutions? 

After all, in many standard white-collar workplaces, AI has a clear support role for the workforce. And 2023 research has shown that the costs of AI software and hardware are dropping dramatically. 

Although there are numerous technical risks and barriers, AI adoption depends on all kinds of factors. For example:

AI adoption can vary according to different business functions

Whether that’s HR, marketing, sales, or logistics. As March 2023 research from Statista shows, AI adoption rates are uneven across business functions with sectors, and across sectors.  

The term “AI” is a wide umbrella term

There are many types of artificial intelligence (and many types of generative artificial intelligence) and their adoption rates are not even. As US Census Bureau researchers demonstrated in a 2023 working paper,  different types of tech are adopted at radically different rates. If you want to be sure about AI adoption, you must be clear about the specific AI tools and AI technologies you are interested in.

AI Adoption varies significantly depending on job role.

42% of HR leaders surveyed in Gartner in 2023 leaders expected entry-level positions to be significantly impacted by AI. The same thing has, of course, happened before. The arrival of desktop word processing didn’t change things for CEOs. But in time, it resigned the secretarial “typing pool” that processed so many documents into history. AI adoption will be different at all levels of the company. 

AI adoption rates vary by country, continent, and geographic region. 

This connects with the relative cost of labor, the levels of digital transformation and digital maturity, and by industry. 

These factors remind us that the idea of “AI adoption” is far more complicated than we might want. In this article, we’ll keep things simple by focussing only on a sector analysis. We believe this is a useful choice, as in globalized industries, sector-specific demands are likely to be a driving force for more extensive AI adoption.

Cross-sector barriers to AI Adoption

Some of the barriers to AI adoption are present across all industries.

After the past year of global excitement about ChatGPT, extensive research has revealed many of the challenges of adopting AI in different businesses.

Looking at 2023 research from Statista, KPMG’s Generative AI Survey from 2023, and McKinsey’s “State of AI” report from 2023, some of the common barriers are:

• Recruiting specialist AI experts  

• Cost of AI implementation
• Lack of tools or platforms to develop models or AI algorithms
• Data complexity and related data privacy issues
• Project complexity
• Regulation and compliance
• Updating legacy software
• Customer expectations
• Workforce impact, including redundancies
• AI Strategy with ROI 
• Risk management
• Shadow AI

With these in mind, let’s take a look at the opportunities, risks, and future of AI applications in financial services, healthcare, and retail.

AI adoption in financial services

Financial services has been using AI more extensively than most other sectors. To understand the lay of the land, we’re lucky to have thorough 2023 research published by the International Monetary Fund (IMF). 

Examples of AI adoption in financial services

Generative AI has significant real-world applications for financial services business. 

Companies are showing how it can enhance fraud detection, improve investment decisions, automate document processing, and power in-house software development. 

These are proven, not speculative, use cases, with global companies harnessing generative AI to optimize their processes.

Risks

Amid the rapid AI adoption in finance, the sector grapples with well-acknowledged risks. 

These include issues of bias, privacy breaches, opacity, fragility, and cybersecurity threats. The sensitive nature of financial data magnifies these concerns, impacting wider financial security. 

Legitimate fears of Shadow AI have led numerous institutions to ban ChatGPT and similar AI tools.

The future

The future of the financial sector’s AI use promises innovation but carries limitations. 

Well-known problems with AI like hallucinations and context comprehension are especially significant. Vigilant monitoring is vital to ensure alignment with industry standards. 

Continuous oversight is crucial to strike a balance between AI benefits and risk mitigation, maintaining precision, transparency, and security in financial services.

AI adoption in healthcare

The healthcare industry already has a clear track record of digital adoption. AI tools are just the next step in the industry’s progress towards better outcomes. 

But for healthcare, the challenges of change management are especially precarious. Healthcare needs extremely careful change management – after all, a mistake could lead to very serious consequences. 

So it’s no surprise that a leading 2023 HBR article says that AI adoption “won’t be easy” in healthcare. But how can AI support healthcare? what are the risks? Let’s take a look.  

Examples of AI adoption in healthcare

AI tools have some very interesting possibilities in the healthcare sector. In the background, AI can accelerate scientific discovery; and on the client side, it can support healthcare professionals to make informed decisions. 

It can sometimes improve medical advice given to patients. And “under the bonnet”, it can alleviate the onerous burden of administrative tasks and paperwork. 

Risks

In healthcare, the transition to AI-driven solutions comes with high risks. The phenomenon of “switchover disruption” is not just an inconvenience – it’s about safeguarding patient lives and data. 

Moreover, doctors, nurses, and other support staff may themselves resistant to any new technology that might threaten their patients. 

As a result, shadow AI must be treated very carefully. Uncertain risks such as AI hallucinations and privacy breaches can have life-or-death consequences, depending on their position within the healthcare system.

The future

Since healthcare faces similar technical challenges to finance, it’s very important for companies to monitor their AI systems carefully. 

Companies in this position could use a digital adoption platform that is capable of handling AI. However, AI adoption in healthcare must also navigate the resistance to change in a compassionate field. 

This is a “human” challenge – not a technical one. Leaders must give staff a clear narrative about AI’s role, and actively reassure patients that their safety and privacy are their highest concerns. 

AI Adoption in Retail

In retail, adopting AI will change business processes and customer experience. There’s no “life or death” in retail. It’s just a matter of profit, efficiency, and good business. 

All businesses will be keen to implement AI in at least one function, consumer retailers are currently approaching AI adoption with caution. 

The US’s National Retail Federation has produced a particularly useful report on how the retail sector is handling it. 

Examples

In 2023, fully implemented case studies for the use of AI in retail are still emerging. The sector-changing plans are still speculative. 

These prospects include many possibilities. AI-driven inventory tracking across the supply chain, personalized customer styling recommendations, and generating AI models tailor-made for specific applications, are all on the horizon of global retail. 

AI also proves its worth in predicting in-store foot traffic, facilitating customer engagement through responses to reviews, enabling dynamic pricing strategies, and tailoring marketing communications on a customer-by-customer basis. 

Risks

In retail, as in the entertainment industry, the shift from creative human work to AI-generated output has sparked significant criticism. 

A critical concern revolves around the potential for mass unemployment if human roles are supplanted by AI counterparts. 

The sector leaders must strike a delicate balance. On the one hand, they should leverage AI’s efficiency – and on the other, safeguard employment among the global workforce. That’s a big challenge! 

The future

The future of AI in retail hinges on identifying the “right” opportunities, especially when existing systems function smoothly. Many businesses are taking a cautious approach, waiting to see how AI can seamlessly integrate into their business models. 

The most promising applications often emerge in multi-site businesses, requiring substantial infrastructure investment. Initiatives like the NRF working group are poised to bolster the adoption of industry-wide AI applications, providing a supportive ecosystem for the retail sector’s AI-driven transformation. 

As the industry navigates this transformative path, collaboration and innovation will be key to harnessing AI’s potential for enhanced customer experiences and operational efficiency.

AI adoption – what do we do now? 

In this article, we’ve focussed on the ins and outs of different industries- rather than AI adoption statistics, the range of digital technologies available, or the demands of natural language processing. Those are topics for another day.

There’s no doubt that many of the challenges and opportunities for generative “AI adoption” cut across businesses and sectors. That’s why so many third-party app developers are making good money from AI-driven software. 

But as soon as you go deeper, there are many factors that make a difference to AI adoption practices. As we’ve seen, the opportunities and challenges are different across sectors – but the specific business units, locations, and job roles will all make a difference too. 

As a result, tech-savvy business leaders should not be adopting AI solutions without the appropriate level of diligence. After all, we still haven’t got a fully mature ecosystem of AI tools. At the end of 2022, a Gartner analysis suggested that Generative AI was just a phase at the start of a “peak of inflated expectations” in AI’s hype cycle. 

So. 2023 is not the time to sit still – but it’s also not the time to go crazy. Now’s the time to prepare, listen, adapt, and implement when appropriate. And then, as the right solutions come, you will be able to implement them for maximum business results.

The post AI Adoption: A sector-by-sector guide appeared first on Digital Adoption.

Yet, caution is warranted. The excitement around AI’s potential must be balanced with a thorough understanding of associated risks, particularly in AI risk management and regulatory compliance. 

This is precisely where an AI Acceptable Use Policy (AI AUP) becomes essential.

Alongside other risk management strategies, an AI AUP supports long-term stability for generative AI in your organization. 

This article will provide a comprehensive overview that: 

• Explains the different meanings of an AI Acceptable Use Policy 
• Examines the key characteristics of any AI Acceptable Use Policy
• Gives an overview of the businesses that will need an AI Acceptable Use Policy
• Points out some further reading about AI ethics. 

Generative AI makes us stop and ask many new questions about how we deploy business IT. A usage policy is just one of the key steps you need to take to make sure that AI does you more good than harm.    

What is an AI Acceptable Use Policy?

An AI Acceptable Use Policy (AI AUP) is a set of guidelines that outline the responsible and ethical use of artificial intelligence within a specific context. 

Typically an AI AUP addresses issues such as data privacy, transparency, fairness, and compliance with relevant laws and regulations. 

The policy supports best practices in AI, ensuring that the organizational use aligns with ethical and legal standards.

Introducing an AI use policy is a guiding framework for many of the risks associated with AI. 

A policy safeguards sensitive data, promotes transparency, and mitigates biases in AI decision-making. It also assigns accountability and responsibility, fostering trust among stakeholders. 

Organizations with an AI AUP protect themselves from potential legal and reputational risks and demonstrate their commitment to using AI for the benefit of the organization, its stakeholders, and society at large.

The key characteristics of an AI Acceptable Use Policy

Each business has the power to decide on what “acceptable use” means for them. 

Your uses of technology, customer needs, and staff experience may all make a difference to the type of responsible AI use you expect. 

So, what will be part of your AI acceptable use policy? Some of the key aspects are likely to be: 

• Compliance with Laws and Regulations

• Data Privacy and Security
• Transparency
• Fairness and Bias Mitigation
• Accountability
• Use Case Guidelines
• Ethical Considerations
• Monitoring and Auditing
• Training and Awareness
• Data Quality and Accuracy

But acceptable use policies are actually quite fickle things. 

Many use policies emphasize privacy, transparency, and accountability (these are all important matters) – according to a 2023 meta-analysis of global policies. 

However, not so many valued truthfulness, intellectual property, or children’s rights (which are much more important – even if they are harder to police).

Which businesses need an AI Acceptable Use Policy? 

Introducing an AI AUP should be a priority for a wide range of businesses, particularly those that heavily rely on or are influenced by artificial intelligence. 

Here are some types of businesses that should prioritize the establishment of such policies:

Tech Companies and AI Providers

Tech companies, especially those providing AI services, should lead the way in implementing AI AUPs. These policies not only guide their internal operations but also set industry standards. 

Healthcare and Financial Institutions

Businesses in the healthcare and financial sectors handle sensitive and highly regulated data. It is critical in these industries to safeguard patient health information and financial data, maintain compliance with strict regulations like HIPAA and GDPR, and ensure the ethical application of AI in decision-making processes.

Large Corporations 

Large corporations with diverse operations and extensive data handling processes should establish AI AUP as a matter of priority. These policies can provide a framework for responsible AI usage, preventing unauthorized AI applications, and ensuring transparency, accountability, and compliance across all departments. They also serve to mitigate risks related to data breaches and operational disruptions.

Startups and Innovative Enterprises

Even smaller businesses and startups should prioritize the implementation of AI AUPs as they integrate AI into their operations. These policies help set clear boundaries for AI usage from the outset, preventing ethical and regulatory pitfalls as they grow and expand their AI-driven initiatives.

Education and Research Institutions

Educational institutions and research organizations should introduce AI AUPs to guide the responsible use of AI in teaching and research. These policies can help ensure that AI technologies are used ethically and that data privacy is protected when conducting research or deploying AI in educational settings.

In summary, AI Acceptable Use Policies are essential for a wide spectrum of businesses, but they are particularly critical for tech companies, healthcare and financial institutions, large corporations, startups, and educational institutions.

What are the business use cases for an AI Acceptable Use Policy?

At present, you’ll find there are three business-specific use cases for an AI usage policy. They are as follows:

AI Providers

Companies offering AI services, like ChatGPT, Google Bard, and Meta’s Llama, recognize the critical need for use policies. 

These policies establish clear terms of use and ethical guidelines, such as those found in OpenAI’s usage policy, Google’s generative AI terms of service, and Meta’s Llama acceptable use policy. 

They help maintain accountability and promote responsible AI usage, ensuring transparency and compliance with legal and ethical standards.

Third-party app developers

Prominent entities like Salesforce have introduced AI-acceptable use policies for their product development. 

This proactive approach assures customers that their data will be handled with care and consideration. 

Salesforce’s commitment to its August 2023 policy demonstrates a commitment to responsible AI practices, enhancing trust and accountability.

End-user corporate users

As businesses increasingly integrate AI into their operations, employees often explore AI applications independently, sometimes without proper regulation. 

This has prompted the need for AI-acceptable use policies. 

To avoid issues like unauthorized AI usage and data leaks, some companies have taken drastic measures, as seen when Samsung temporarily banned unauthorized AI applications following an internal data breach in May 2023. 

Implementing an AI-acceptable use policy is a proactive solution to monitor and regulate AI usage within organizations, ensuring ethical, compliant, and secure AI practices.

AI Acceptable use and the ethics of AI tools

AI is a diverse landscape of emerging technology – and your company may need a more nuanced approach to the problems. 

Fortunately, the field of AI ethics is helping businesses and governments to really understand the challenges.

The following resources will help to discover more about the use of AI technology. 

• Some organizations are shedding light on the broader considerations of morality and ethics in AI. Organizations such as the Center for AI Safety have taken a pioneering role in developing comprehensive guidelines to address the ethical dimensions of AI. These guidelines tackle the fundamental questions that arise from the use and development of AI, establishing a foundation for responsible AI deployment.

• AI use is not identical across every business. So, domain-specific AI guidelines can help to focus your attention on the critical issues in your industry. Whether it’s AI in college admissions, legal practice, healthcare, or talent development, these applications come with their own set of ethical dilemmas. Industry bodies are starting to provide valuable insights into the evolving ethical considerations surrounding AI in these specialized contexts.

• Some organizations are keeping a close eye on how AI policy is developing as a business sub-discipline. For example, Algorithm Watch keeps a global inventory of AI ethics guidelines. Whatever your business, these resources can offer you make comparisons about how companies negotiate the inherent risks of AI. 

AI Usage policies and the future of digital trust 

In the journey to use AI responsibly, having an AI Acceptable Use Policy is essential, but it may not be the first thing you do. As we’ve seen, you must think carefully about the ethical challenges and opportunities that AI brings, even when those are not yet clear. By doing all of this, organizations can continue to build digital trust, which is crucial in using AI safely.

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