Building AI Value Creators: the comprehensive workforce transformation guide

The artificial intelligence landscape has reached what experts call a "Netscape moment" - a transformational period comparable to when the first web browser democratized internet access in the 1990s. This transformation is comprehensively documented in "AI Value Creators: Beyond the Generative AI Mindset," an ebook written by Rob Thomas (SVP and CCO at IBM), Paul Zikopoulos (IBM VP focused on skills and AI), and Kate Soule (IBM research director who leads technical product management for Granite, IBM's family of large language models). The ebook was released online by IBM in April 2025 and published by O'Reilly Media.

As will.i.am, founder and CEO of FYI.AI, notes in his praise for the AI Value Creators approach: "A handbook for the AI Renaissance to help entrepreneurs and innovators drive AI value creation at the next level." This transformation demands more than technical adoption; it requires developing AI Value Creators who can build entirely new solutions and workflows rather than simply consuming existing AI tools.

Summary

Who: AI Value Creators represent workers and organizations that build new AI-powered solutions rather than simply consuming existing tools. Industry leaders like will.i.am, Malcolm Gladwell, and Jessica Sibley endorse this strategic approach for sustainable competitive advantage.

What: The framework encompasses comprehensive workforce transformation including curiosity-driven hiring, digital mindset development, systematic skills programs, cultural change, and strategic AI implementation through "shift left, shift right" methodologies. These insights are detailed in the "AI Value Creators: Beyond the Generative AI Mindset" ebook by Rob Thomas, Paul Zikopoulos, and Kate Soule, published by O'Reilly Media and released by IBM in April 2025.

When: The transformation occurs during what experts call the "Netscape moment" for AI - a period of fundamental technological democratization requiring immediate organizational response to maintain competitive positioning.

Where: Implementation spans all business functions from human resources and customer service to manufacturing and legal operations, with particular emphasis on internal automation before external transformation.

Why: Organizations must develop AI Value Creators to avoid dependency on external AI providers, maintain data control, create sustainable competitive advantages, and participate in the broader societal transformation enabled by artificial intelligence technologies.

The fundamental distinction between AI Value Creators and basic AI users represents a strategic shift that organizations must understand to maintain competitive advantage. According to the AI Value Creators framework, "The AI Value Creators will be the ones who make the biggest impact. They will take the amazing foundational technology that is GenAI and use it to build entirely new solutions and workflows."

This distinction centers on value creation versus value consumption. As the research explains: "In the past, we've seen a lot of value-extractive business models—if you're on social media, you're a part of one. Quite simply, we always tell people if you're not paying for it, make no mistake about it, you're more than likely the product being sold." AI Value Creators reverse this dynamic by maintaining control over their data, processes, and AI implementations.

The platform approach enables organizations to become "your own AI fire starter," where companies have "all the elements and ingredients (data, governance, and LLMs) in place to build your own AI solutions." This comprehensive method provides "access to a vast number of GenAI models (both open source and proprietary), or you can bring your own models into the platform."

The Value Creation Imperative

Malcolm Gladwell, host of the Revisionist History podcast, emphasizes the strategic importance: "Rob Thomas brings insight, common sense, and his long experience at IBM to bear on the greatest technological transformations of our lifetime. On the subject of AI, there are few people whose perspective I would value more." This endorsement underscores the critical nature of developing proper AI leadership and implementation strategies.

The economic implications drive urgency in AI Value Creator development. The research indicates that organizations face a fundamental choice: "Do we, as a society, really want to have just a few keepers of the AI 'fire' upon which we are all dependent? Is that what's best for your individual business and for your shareholders? We think no."

Transformational Skills Framework: From Traditional to AI-Ready Capabilities

The skills transformation required for AI Value Creation represents one of the most significant workforce development challenges organizations face. According to the comprehensive analysis: "Quite simply, the skills that businesses needed to grow 20 to 50 years ago are not the skills that will be needed to grow in the future."

Leadership Evolution: From Command to Adaptive

Traditional hierarchical leadership approaches must evolve to support AI implementation. The research contrasts old and new leadership requirements: "Hierarchical leadership. Command and control with a top-down approach wasn't just paramount, it was the de facto style" versus "Adaptive leadership. Leadership virtues include flexibility, surrounding yourself with people smarter than you, equal opportunities, and giving everyone a chance to be heard."

This transformation extends beyond management styles to fundamental communication approaches. The framework notes: "Emotional intelligence (EI). The ability to understand, empathize, and connect with people with different experiences, educational backgrounds and cultures is a critical skill. It really comes down to not being a jerk—yes, leaders must make tough decisions and give tough talk, and it's not a popularity contest. But getting people to want to work for you is the better path—remember, out of curiosity alone!"

Digital Communication Mastery

Modern AI-ready workforces require sophisticated digital communication capabilities that go far beyond basic technology usage. The analysis explains: "Digital communication. Proficiency in digital communication tools and platforms is crucial, and hybrid work creates the conundrum of working from home and going back to the office with different schedules and approaches."

The legal implications of digital communication have evolved significantly: "Some courts have ruled that a thumbs-up emoji sent via text messaging can bind a contract for purchase, and one airline lost a challenge in court based on their LLM-fronted chatbot giving incorrect (but believable) information about its pricing policies." These developments require workers to understand the legal and business implications of AI-mediated communication.

Lifelong Learning as Core Competency

The transition from specialized expertise to continuous learning represents perhaps the most significant skill shift for AI Value Creators. The research emphasizes: "Lifelong learning. The most effective leaders bring and integrate multidisciplinary experiences into their jobs. Experience in development, product management, and sales creates true agents of change—so be a decathlete in the Skills Olympics!"

This approach recognizes that "specialized skills matter, but you need to always be adding to your 'skills suitcase.'" The framework acknowledges that "technology skills age quickly. This necessitates a commitment to continuous learning and upskilling."

Curiosity as the Fundamental Driver of AI Innovation

The role of curiosity in AI Value Creation cannot be overstated. According to the research: "And don't forget curiosity! Look, you're never going to get your workforce to stop walking by problems that can be solved or made better with technology every day if you don't know what to look for or if workers don't take displeasure in some rote process and think, 'It doesn't have to be this way.'"

Curiosity-Driven Problem Identification

The framework establishes curiosity as essential for recognizing AI implementation opportunities: "If your staff isn't empowered to make changes, all the skills you may uplift in your organizations may be for naught. After all, there is no sense in having chess pieces if you're only planning to play a game of checkers."

This principle extends to daily operations where transformation opportunities exist everywhere: "Every day, we walk by problems that can be solved or made better with technology. We repeated this section's title here because it's a mantra we want you to start thinking about."

Performance Correlation with Learning Engagement

IBM's internal research demonstrates the practical value of curiosity in professional settings: "At IBM, we have a special recognition for our top sellers, called The Golden Circle. If you make it, you're considered an exemplary performer who consistently demonstrates a dedication to client excellence and commitment to delivering outstanding measurable outcomes."

The key finding reveals: "One of the top predictors that jumped off the page was learning: Golden Circlers learned more, completed their assigned learning journeys (faster than their peers too), and made their own learning plans." This correlation suggests that "curious employees are leading indicators in your upskilling adoption curve."

Recruiting for Curiosity

Organizations must fundamentally change their recruitment approaches to identify curious candidates. The guidance emphasizes: "To really put curiosity at the core of the hiring process, ensure you work with your HR team's talent acquisition teams so that they closely monitor for curiosity attributes during the hiring process."

The assessment goes beyond traditional credentials: "You're going to get recruiters who don't know what GitHub is; they need to get upskilled so they know how to look beyond a CV or LinkedIn page because a candidate's GitHub is often a curiosity calling card."

A practical example illustrates this approach: "One candidate stood out to us because not only was she technically curious and accomplished, but she also had a thriving social media account (@culinarychum) where she focused on restaurants that do a great job accommodating allergies (like celiac disease) and great gluten-free products at grocery stores." This demonstrates "social network (active, with a personal point of view), compassion, community, writing, engagement, and more."

Digital Labor and Workforce Transformation

The concept of digital labor represents a fundamental shift in how organizations approach workforce augmentation and productivity enhancement. According to the framework: "In the past, the term 'digital worker' described a human employee with digital skills. Today, when you use this word, its definition resolves to a category of software robots (not the ones you see in movies, they're coming, but not quite here yet), which are trained to perform specific tasks or processes in partnership with their human colleagues—often referred to as bots."

Digital Labor Definition and Capabilities

The comprehensive definition explains: "We define digital labor as software-based labor that can independently execute meaningful parts of complex, end-to-end processes using a range of skills." These capabilities extend far beyond simple automation: "Digital labor can leverage AI to execute a sequence of tasks within a given workflow. Specifically, digital employees (the bots) leverage AI capabilities such as natural language processing, agents, and GenAI (among others) to interact and communicate, think and reason, sequence skills on the fly, and put those skills into context by maintaining a working memory of past interactions."

Practical Implementation Examples

Real-world applications demonstrate the transformative potential of digital labor. The Sport Clips example illustrates immediate impact: "The Sport Clips team used watsonx Orchestrate to create digital labor workers and reduced the process for candidate outreach from three hours to three minutes."

Similarly, external implementations show broad industry adoption: "Klarna announced in early 2024 that it partnered with an IBM competitor to put digital labor to work for its customer service team; today, AI handles two-thirds of the calls (a rate similar to CVS), which led to a 25% reduction in repeat inquiries, and does the work equivalent of 700 full-time agents, allowing staff to focus on higher-order tasks."

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Scale and Economic Impact

The economic advantages of digital labor implementation are substantial. The framework notes: "If a human employee picks up a phone to handle a call, that's typically going to cost about $5 for a simple case; if a digital employee handles that call, it's about $0.25."

Government implementations demonstrate public sector value: "The Oregon Department of Motor Vehicles (DMV) stood up some digital labor to help them handle the massive call volume spikes they experienced during the COVID-19 pandemic. Within weeks, they were deflecting about 30% of the basic questions they received." The results were significant: "The Oregon DMV noted that this effort saved them almost $3 million (the 2-year cost of about 30 workers) and reduced customer wait times."

The Shift Left, Shift Right Strategic Framework

The shift left, shift right methodology provides a structured approach to AI implementation that balances automation with human value creation. According to the framework: "There's a popular concept in software development and manufacturing known as shifting left. The premise is that if you capture defects earlier in the cycle, they become much less costly than if you'd caught them downstream, when they're in the hands of a customer."

Shift Left: Automation and Efficiency

The shift left concept, when applied to AI implementation, focuses on "spending money to save money" through early-stage automation and problem-solving. The research explains: "GenAI and agents give all companies a moment to redefine what shifting left means and benefit from the compaction of work (or getting it right the first time, or done faster, or automated) and compressing those costs."

This approach enables significant productivity gains: "In Chapter 1, we said shift left so you can shift right. This is about building automation early in the workflow or 'job to be done.' AI is exceptional at this, if we take the time to explain to an AI what we want done. Said another way, this is the construction of a digital worker."

Shift Right: Strategic Value Creation

After establishing automation foundations, organizations can shift right to focus on transformational activities: "Now that you're shifting part of your business left and are saving time, money, and even lives, you've got the confidence and experience to shift right by spending money to make money (that is, doing the transformational stuff)."

The shift right approach enables human workers to focus on higher-value activities: "Because digital workers increase the bandwidth of their human bosses, they have largely been adopted through digital transformation efforts (shift left), allowing companies to reallocate their workforce to more strategic tasks (shift right)."

Real-World Implementation Examples

Healthcare applications demonstrate the life-saving potential of shift left strategies. The framework provides a compelling example: "Some companies have HR enterprise resource planning (ERP) systems that literally take 20 minutes of clicking to transfer an employee to another department! Not surprisingly, they come with high failure rates."

IBM's internal transformation illustrates the business impact: "Our chief human resources officer (CHRO), Nickel LaMoreaux, personally skilled up on the very things we are covering in this book and drove a plan to shift this left. Today, employee transfer failure rates are pretty much nil, and over 4,000 hours have been returned to the business in the form of 'think time.'"

The cumulative impact demonstrates substantial value: "In aggregate, across all functions, actions like these have saved IBM $3 billion since inception."

Comprehensive Skills Development Framework

Organizations must implement systematic approaches to skills development that address both individual capabilities and cultural transformation. According to the research: "Make no mistake about it. If you're a business, a government, or any other kind of entity, your people will need new skills for the organization to grow."

The Eight Levers of Skills Development

The framework provides eight specific implementation levers for sustainable skills programs:

1. Curiosity-Focused Hiring: "Start at the beginning—hire the employees who want to know the 'why.'"
2. Digital Talent Recruitment: "Recruit digitally minded talent" who "look for people who can demonstrate how they constantly embrace innovations that make stuff better, go faster, be more accurate, are more streamlined, and more."
3. Skills Inventory: "Take count—inventory your skills" to understand current capabilities and gaps.
4. Comprehensive Planning: "Plan for everyone—a plan without action is a speech."
5. Learning Curve Management: "Embrace the learning (and forgetting) curves" to acknowledge that skill development requires ongoing adaptation.
6. Multi-Modal Learning: "Combine instruction, imitation, and collaboration" to provide diverse learning pathways.
7. Cultural Leadership: "Culture matters—be a skills verb, not a noun" where leaders demonstrate learning participation.
8. Organizational Tone Setting: "Set the organizational tone for AI" through transparent communication and clear guidelines.

Identifying Non-Digital Mindsets

The framework provides specific indicators for identifying workers who may struggle with AI adoption: "You probably already know what non-digitally minded talent looks like. They're the people who openly say, 'I'm not technical'; they likely click on File Copy then File Paste (over and over again) versus eloquently pressing Ctrl-C, Ctrl-V; they present dashboard reports with copied images in PowerPoint that are a week out of date."

The most telling indicator: "The biggest tell are those people with $1,500 iPhones who leave 90% of their capabilities untouched (and unknown)—like using AI to grab text from a photo." This matters because "if someone is digitally minded, they will always independently seek out more efficient ways to do things like using agents to get more work done."

IBM's Corporate Skills Challenge: A Large-Scale Implementation Model

IBM's watsonx Corporate Skills Challenge provides a concrete example of enterprise-level AI skills development that organizations can adapt. The initiative demonstrates how to implement skills development at scale while maintaining engagement and practical outcomes.

Challenge Structure and Scope

The program's scope was ambitious: "The challenge: increase the AI skills of 280,000 people using a core set of training materials. Offer hands-on training access to IBM's new watsonx AI platform and products. Make it fun."

The approach emphasized practical application over theoretical learning: "The Challenge encouraged all IBMers to come up with applications, workflows, assistants, or anything...all in an effort to formulate compelling use cases for putting AI to work. Notice it wasn't ideas? It's easy to get a bunch of people to tell you what they want or think AI can do. But this was a very different approach."

Participation and Engagement

The program achieved remarkable voluntary participation: "IBMers could participate as individuals, but most people, including our C-suite leadership (be a verb, remember), formed teams—over 10,000 of them!" This approach created organic collaboration: "This had the benefit of bringing people together (somewhat organically, large in-person scrums spun up where teams would get together in person to generate some of that serendipitous magic that comes from in-person interactions)."

Resource allocation supported serious experimentation: "You got a week of company time to work on The Challenge and pretty much all the compute (within reason; we didn't let people build their own LLMs from scratch) you needed."

Prerequisites and Quality Control

The program maintained quality standards through prerequisites: "A prerequisite gated access to The Challenge: complete assigned training, which included a 'stand and deliver.' Pulling from our sales and consulting training practices, we asked everyone at IBM to not just learn the new story of GenAI but to showcase having a conversation about it."

Measurable Results and Impact

The 2024 iteration demonstrated significant scale and impact: "In 2024, a whopping ~160,000 of our employees (that's ~60% of our workforce—remember, voluntary) trained on our companies newest AI offerings, sharing our message more confidently and singing from the same song sheet in countries and communities around the world."

The practical engagement was substantial: "This time, they created a community in the form of 30,000 teams and made a whopping 8 million inferences (nerd talk for having an AI do what you ask it to do) calls a day! They collectively submitted 12,000+ prototype projects for evaluation."

The business value extended beyond skills development: "On top of all of this, live testing of 50,000+ workloads, and more than 8,000 pages of feature requests, feature enhancements, usability improvements, resiliency tests, bug reports, and new use cases were identified across the wide suite of IBM watsonx-branded products—channeling a skills growth project into a productivity multiplier."

Skills Development Validation

The program's effectiveness was validated through participant feedback: "After all that (and why we're talking about it in this chapter), 88% of IBMers significantly thumbed-up the question, 'Did you increase your AI skills in this challenge?'"

The long-term impact extended to production deployments: "Both times we ran The Challenge (we even made it repeatable such that one of our VADs ran it for their ecosystem partners), we ended up with thousands of amazing ideas. We picked the top dozen or so and rewarded them, and some of them got all the way to production and completely shifted-left how many IBMers do their work today in 2025."

Organizational Culture Transformation for AI Value Creation

Successful AI Value Creator development requires fundamental cultural transformation that goes beyond individual skills development. According to the framework: "Before you put any plans into action, leadership must decide to be verbs when it comes to skilling, not nouns. We've seen it many times (even inside IBM; no company is immune): there are leaders who lead by doing and those who hit the sound bites, but that's about it."

Leadership Modeling and Transparency

Authentic leadership engagement requires vulnerability and shared learning experiences: "And if you're serious, you're in there with them—being vulnerable and sharing what you've learned and where you've struggled along the way." This approach helps address employee concerns about AI implementation.

Fear Management and Communication

Organizations must proactively address employee fears about AI adoption: "Engaging employees with transparency is key because many are going to feel your initiatives are targeting their jobs. Remind them that people who get comfortable using AI will replace those who don't."

The communication should include clear explanations about role evolution: "Explain how their job might change as the rote tasks are shifted to the left. For example, an HR employee whose job is to handle failed department transfers or answer state-to-state (or province-to-province) questions on parental leaves gets their time freed up to help managers plan a more efficient onboarding strategy that gets new hires delivering for the business faster."

Systematic Feedback and Support

The framework recommends using AI tools to manage the cultural transformation process: "Finally, prompt conversations and interactions about all of the above using digital check-ins with support from AI-generated discussion topics. From there, you can use AI to classify the sentiment, create discussions, and start your fear removal plan."

The approach ensures comprehensive support while maintaining individual agency: "You'll want to ensure employees feel like they have an active role in the learning, expectations, and what they need too. But it's equally important to just have that done in one place to share feedback, take suggested actions, and schedule manager check-ins."

Investment Perspective: Skills as Value Creation

Organizations must fundamentally reframe their approach to skills development from cost center to value creation mechanism. According to research cited in the framework: "A Boston Consulting Group (BCG) report noted that just '15% of leaders believe that learning constitutes a core part of their company's overall business strategy' and 'only a handful of companies indicate that they have a structured process for forecasting skills gaps based on corporate business needs.'"

The Strategic Value of Upskilling

The research is blunt about the strategic imperative: "Organizations! Stop seeing upskilling as a cost center—it's the ultimate value creator." The business case is compelling across functions: "Well-trained developers or cloud engineers could learn how to properly assess applications to forecast how many tokens they will use; well-trained marketers will rethink marketing copy and put agentic AI to work to assist them with campaigns, asset designs, ad buys, and getting new insights on which initiatives are fueling meaningful engagements; well-trained sales associates will be more creative and collaborative partners with your clients and spend less time on internal preparation and paperwork."

Employee Retention Through Development

Investment in skills development creates retention advantages: "Not only will your upskilling investment be critical to your employee's success, but it will also be critical to their retention. Your top learners will know that the more they invest in their skills, the more packed their skills suitcase becomes—and there are no overage fees on this airline!"

The competitive advantage for skilled workers drives retention: "People who travel with multiple skills suitcases put the onus on their employer to figure out a way to keep them because they're so valuable." This correlation extends to company reputation: "A quick search of Reddit comments across the main hiring boards of any tech company will quickly show which companies foster a culture that prioritizes and invests in learning and which don't. Fun fact for your HR department: it's highly correlated to the turnover rates."

Comprehensive Growth Approach

The framework emphasizes holistic development: "In the end, reskilling should be positioned as a tailored growth opportunity addressing the whole person." This philosophy extends beyond immediate business needs: "Create time to empower and invest in those employees. They will tell you the how: from external training, conferences, community volunteer work—your job is to help them connect the dots to a growth path aligned to your business."

Future-Proofing Through AI Value Creation

The AI Value Creators framework positions organizations for long-term success in an rapidly evolving technological landscape. As Jessica Sibley, CEO of TIME, notes: "With AI reshaping industries, this handbook provides actionable insights that can help you drive innovation and navigate the next wave of AI advancements, positioning your business for long-term success."

Avoiding Platform Dependency

The framework warns against over-reliance on external AI services: "If you can show some restraint and not carelessly check the 'I put AI in the business' box using fast and easy options (or be pressured to do so); if instead, you are thoughtful, deliberate, and strategic about using a platform that considers all the components you need (AI, data intelligence, data integration, and governance); and most importantly, if you set your GPS to a destination of 'AI Value Creator,' then you're going to be in a position to succeed over the long term."

This approach provides resilience against technological changes: "What's more, like so many before you, your company won't have to start over every time the winds of AI change direction."

Societal Impact and Responsibility

The framework emphasizes the broader implications of AI Value Creation: "Personally, we're very excited about this new chapter in technology. We, all of us together, are going to use GenAI and agents to reshape not just our digital world but also our physical world. We're going to use it to help tackle some of our toughest social, medical, and environmental problems, and more."

The approach balances innovation with responsibility: "We'll do it through science, but also by empowering businesses—like the ones you work for and the one we work for—to do more faster and more responsibly. Whatever thing it is that your company does, AI is going to be a powerful new tool to help you do it better."

The Transformation Imperative

The conclusion emphasizes the critical nature of this transformation: "Truth be told, it's just the beginning. The beginning of all the things you need to know to use AI to drive value for your business to deliver results. If you read the whole book, you have a crisp understanding of the pitfalls and the windfalls that are GenAI and agents. You have confidence. You have knowledge. You have a plan. You know how to create value."

The call to action is clear: "We can't wait to see the value you're going to create and what you do with it. In other words, for those about to AI, we salute you!"

Timeline

• August 2023: IBM launches watsonx Corporate Skills Challenge for 280,000 employees
• 2024: Second Skills Challenge achieves 160,000 voluntary participants with 8 million daily AI inference calls
• 2024: IBM reports $3 billion in productivity savings from AI implementation across functions
• April 2025: Publication of "AI Value Creators: Beyond the Generative AI Mindset" ebook by Rob Thomas, Paul Zikopoulos, and Kate Soule, released online by IBM and published by O'Reilly Media