The work environment is evolving faster than ever. Artificial intelligence has progressed from being a promise of the future to being at the core of today’s business activity. What was previously the domain of IT functions and centers of innovation is now on every organisation’s agenda.
Each team, from finance to marketing, from product to human resources, is being requested to comprehend and apply AI in their daily work. Since the 2026 Global Learning & Skills Trends Report indicates, we are at a turning point in how we learn, acquire skills, and equip ourselves for the future.
For businesses, this transformation is not merely about embracing tools. It’s about reframing how they think, collaborate, and expand. For workers, it’s about remaining relevant in professions that are evolving quickly. Yesterday’s skills are already becoming outdated today, and whole new jobs are being created overnight. As a result, organisations and individuals alike have come to one fundamental realisation: learning must be quicker, ongoing, and tied to actual work.
This transformation is centered on the concept of AI fluency. In contrast to simple training courses on how to operate a tool, fluency is the ability to think, query, and collaborate with confidence with AI. It is knowing its limitations and capabilities, when to rely on it, and when to stop. It is learning to be adaptive in terms of curiosity, judgment, and flexibility. All in all, AI fluency is no longer a choice. It is the language of work.
The report uncovers that AI learning demand has surged. Training courses involving teaching AI tools how to be prompted, developing generative models, and working with tools such as Microsoft Copilot and GitHub Copilot have experienced unprecedented growth. Workers are clamoring to learn more, and companies are scrambling to keep pace.
Firms such as Genpact and Devoteam have already demonstrated how massive-scale AI training programs can reshuffle workforces within months. Genpact had its 125,000 staff trained in a 12-week immersion program, achieving high levels of proficiency and developing proof-of-concept projects to utilize their new skills. Devoteam implemented a firm-wide AI program within three months, with 70 percent of its workforce up-skilled in AI shortly afterward. The payoff was not just new abilities but also reduced employee turnover, demonstrating that workers feel safer when they are equipped with learning.
However, the report emphasises that classroom or online training is not sufficient. Classroom or online training knowledge decays rapidly unless put to practice. Effective learning occurs when employees exercise skills in actual scenarios, receive feedback, and hone their skills over time. This is why it’s so popular to have immersive, work-integrated learning.
For instance, rather than being told about AI ethics, staff could role-play through AI avatars to try their decision-making. Rather than being lectured on prompt engineering, they could work with live projects using AI tools and record the results. Research indicates that individuals who use skills with instant feedback learn three times as fast as those who merely hear them.
Firms such as Prodapt are spearheading this change by integrating learning in real workflows. Ninety percent of their workforce are now familiar with the fundamentals of generative AI, thanks to customised micro-learning streams incorporated into their work. The strategy demonstrates that learning is not an activity outside of work or alone. It is part of the work itself.
Another powerful message from the report is that it is impossible to scale AI capabilities without scaling leadership, ethics, and trust. AI is also exciting and causes worry. Most workers fear losing their jobs, their personal data being used for something bad, or losing all human interaction.
These concerns, the report contends, are not only sparked by technology but by leadership gaps. Leaders must not only embrace AI themselves but also make it an environment where employees are encouraged to experiment, question, and even fail when they’re learning. They must set clear ethical standards, encourage transparency about difficulties, and provide workers with real agency in determining how AI is being implemented.
PepsiCo’s example highlights how leadership programs can build resilience. By partnering with Udemy Business, the company created a culture of operational excellence in procurement. More than 1,200 employees completed leadership programs with high success rates, leading to higher promotion rates and improved agility. The lesson is that future competitiveness will not come from who has the best AI technology, but from who has the best leaders to guide its use.
The report also cautions against the usual pitfall: thinking of AI as an end point. AI can be the most headline-grabbing disruption now, but it will not be the last. Companies that invest only in AI preparation will get blindsided by the next change wave. True competitive edge comes from adaptability—the capacity to learn, unlearn, and relearn repeatedly. Adaptive competencies such as critical thinking, resilience, creativity, and decision-making will survive any one technology.
Udemy data indicates a steep increase in demand for these so-called soft skills. Training in domains such as decision-making and critical thinking increased by over 35 percent over a single year. This indicates an awareness that while AI can be used to automate tasks, humans will always be necessary for judgment, innovative thinking, and emotional intelligence. Gen Z employees, in fact, view soft skills as necessary for professional success, with 84 percent specifying that they are important. Mid Career managers also are investing in communication and creativity to remain relevant.
Those types of companies like Integrant are already implementing adaptability. Through the development of a learning matrix that charts technical and adaptive skills by job function, they have achieved almost 100 percent AI adoption and considerable skills gap reductions. Their focus is not only on today’s requirements but to remain prepared for future disruptions as well.
The report provides pragmatic recommendations to companies. It advises measuring AI fluency at various levels, from basic literacy to sophisticated integration of agentic AI systems. It advises shifting from generic training to job-specific programs, incorporating AI values and ethics right from the beginning, and connecting learning with business outcomes. It also emphasizes keeping learning entertaining, rewarding, and ongoing, through mechanisms such as gamification and social sharing of AI applications.
In summary, the report boldly declares: AI is not a technology. It is the grammar of enterprise in the modern era. But the key to success won’t be who implements AI first. It will be who develops the best culture of continuous learning, flexibility, and moral leadership. The most forward-looking companies will be those that approach every disruption as preparation for the next, accepting constant reinvention as their business model.
For workers, the message is no less clear: becoming valuable in tomorrow’s workplace is about mastering technical fluency and adaptability. For executives, the test is to lead with vision, trust, and empathy. For companies, the promise is to transform learning from a one-off activity into an ongoing growth engine.
As the report writes, the future is being rewritten in real time. Every organization, large and small, is now in the business of learning. Every employee, every role, is a lifelong student. And every leader is an architect of change. AI can be changing how we work, but human adaptability, ethics, and creativity will determine how well we will succeed in this new world.
