Vishaal Gupta argues that building an AI-ready workforce is less about technology and more about culture. From transparent leadership to continuous learning, this feature lays out how organisations can move beyond hype to action, bridging people readiness gaps, reducing risk, and turning AI into a true strategic advantage for organisations.
AI is fundamentally transforming organisations, creating a clear competitive distinction between those acting decisively and those hesitating. This isn’t just another technology upgrade; it requires a complete rethink of how organisations function. The commercial case is compelling: Pearson Skills Outlook research found that properly implemented AI tools could help UK workers reclaim nearly 19 million hours a week.
Executives guiding enterprises through this transformation have the opportunity to reimagine workforce development, turning it into a strategic driver of measurable productivity gains, operational efficiency, and sustainable business growth in an AI-enhanced economy.
However, organisations are full of people with diverse AI readiness levels that require attention. National Cybersecurity Alliance data exposes a troubling governance gap: About 38% of employees share confidential data with AI platforms without approval. Unauthorised AI usage introduces risks to data security, operational efficiency, and ethical practice. Without executive direction, this shadow AI adoption also undermines corporate strategy.
Such challenges represent clear opportunities for leaders to establish meaningful governance frameworks and guide their organisations through holistic AI adoption. The strategic imperative for executives is clear: Cultivating an AI-ready culture is essential. Research from Gallup shows that among employees whose companies have communicated a clear AI strategy, 87% believe AI will positively impact their productivity. Yet only 15% of workers strongly agree their organisation has communicated such a strategy.
Leaders must drive change, starting by assessing workforce AI readiness, developing a compelling narrative about AI’s purpose in the organisation, and personally championing adoption. While L&D teams can support implementation, creating this culture demands executive vision and commitment.
Know the starting point
AI’s business opportunity is substantial. Our research indicates that generative AI can handle up to 30% of knowledge work tasks. This capacity creates extraordinary potential to redirect professional talent toward higher-value activities that drive competitive advantage.
One of the most urgent, emerging shifts in AI is grasping the transition from generative AI to agentic AI. Generative AI is primarily about producing content when prompted, but agentic AI takes things a step further. This more advanced AI not only creates content, but it proactively carries out tasks, makes decisions, and learns from its experiences to get better over time.
This progress is leading to a new kind of workforce, where AI agents act like digital versions of employees, making choices and taking actions to boost efficiency and innovation. Meanwhile, people will learn to work alongside agentic AI, using its strengths to improve decision-making, simplify processes, and spark creativity.
For those in training and development, embracing this change is key to keeping their organisations competitive and flexible, as the partnership between human skills and AI becomes crucial for success. Fortunately, employees already possess an appetite for this kind of learning. Our research on employee sentiment found that more than three-quarters of workers expect to keep learning throughout their career. What’s more, they prefer to learn via their employer. Such alignment between employee expectations and business needs creates the right foundation for an AI-ready culture.
The first step is to conduct a thorough workforce AI readiness assessment. Consider how many professionals are secretly using AI tools already. Identify what kind of opportunities disappear when teams use such tools without guidance. A combination of methods provides quantitative and qualitative insights, self-diagnostic tools to gather broad data, focus groups to identify common themes, and targeted interviews with key leaders. This intelligence offers a clear map: areas for investment, points for intervention, and existing strengths. Such a data-driven approach ensures resources drive specific impact rather than broad attempts with limited ROI.
Make it personal
The next challenge is cultivating continuous development of both technical and human capabilities. AI implementation requires continual learning as capabilities evolve. Organisations must create pathways for professionals whose tasks become automated, helping them develop higher-value skills.
Tailoring AI implementation to different segments of the workforce is essential. For those unfamiliar or uncomfortable with AI, focus on foundational knowledge and practical applications relevant to their roles. For technically proficient teams, invest in advanced learning to deepen expertise.
The most successful AI strategies recognise that technology skills alone are insufficient. Developing both technical AI fluency and essential human capabilities, like strategic thinking and innovation, shapes a workforce that works with, not against, AI’s strengths and limitations.
Research shows organisations are prioritising communication, leadership, and precision in their talent strategies. In parallel, Pearson’s Skills Outlook: Employee View reveals professionals are focusing on developing both technical knowledge and distinctly human capabilities, such as problem-solving and leadership. This convergence sends a clear message: Workforce learning strategies must balance technological expertise with human judgment.
The cost of failing to follow through has real economic consequences: Our Lost in Transition report reveals that inefficient career transitions and learning gaps cost the U.S. economy alone $1.1 trillion annually. Simply reducing the average transition time between education and work from 24 to 18 weeks could generate an additional $40 billion in economic value.
Transparency wins
Building ethical guidelines and responsible practices into the AI strategy is essential for sustainable adoption. Emphasise transparency by ensuring teams understand how AI systems are developed, tested, and implemented within the organisation. Provide clear information about decision-making processes and data sources behind AI algorithms in language that makes sense to everyone involved.
When AI systems are transparent and their decisions well-explained, teams can more easily identify and address potential biases or errors. Educating employees on both AI capabilities and limitations helps them feel more comfortable using these tools, which will accelerate integration and improve effectiveness across the organisation.
Actions over words
Cultural transformation begins with visible, committed leadership. People follow what leaders do with AI, not what they say about it. Senior executives must personally demonstrate their commitment through active engagement with AI technologies, sponsorship of strategic AI initiatives, and meaningful resource allocation.
The leadership team should be fluent in articulating how AI drives business value not just in global terms but with language that connects to the organisation’s goals and values. Establish cross-functional implementation teams that report directly to executive sponsors so that information flows quickly and adjustments can roll out seamlessly.
Open the communication channels
Not every employee will eagerly embrace AI. Some may have valid concerns about job displacement or data privacy. One of the first steps in redefining the company learning culture is encouraging open dialogue.
Create an environment where discussions about AI and its implications are welcomed. Participate in these conversations; share personal and professional experiences with new AI tools. Regular town hall meetings, workshops, and round-table discussions can serve as platforms for these conversations.
It’s also important to maintain clear communication between meetings. Regularly inform employees about AI developments and their impact through newsletters, blogs, webinars, and leadership updates. Use anonymous feedback channels to address concerns about AI implementation.
Demonstrate the real-world value
Taking practical steps to address hesitancy around AI use can improve AI integration. When professionals move from fearing AI to leveraging it, work transforms from repetitive tasks to meaningful challenges that utilise their full talents.
Organisations should provide real-life examples and case studies showing successful AI implementations within the industry. Sharing customer success stories during training sessions can help make the concepts more real and persuasive to team members.
Encouraging experimentation with AI tools in a “sandbox” environment lets employees explore AI’s potential without fearing failure. These risk-free simulation environments help employees better understand what AI can and cannot do, building familiarity and confidence.
Measure the impact
Organisations must establish metrics for success in their AI culture-building efforts. These include measuring AI proficiency through periodic assessments, tracking the productivity gains from AI adoption, and monitoring employee sentiment regarding AI. Creating feedback loops helps improve the AI training programmes and address emerging challenges continuously.
These strategies aren’t just good business practice; they’re the foundation of an AI-ready future. Imagine teams confidently experimenting with AI, discovering new efficiencies, and tackling challenges that once seemed insurmountable. Picture professionals liberated from mundane tasks, applying their uniquely human talents to innovation and connection.
Leaders must prioritise cultivating an AI-centric culture today to create workplaces where technology and humanity seamlessly complement one another. These strategies not only position organisations to remain competitive, but also foster vibrant environments where people flourish, skills evolve organically, and continuous learning becomes second nature.
Vishaal Gupta is President of Enterprise Learning and Skills at Pearson
