Udemy’s 2026 report reveals that AI has transformed workplace learning, making AI fluency, adaptive skills, and continuous, in-the-flow training essential for competitiveness. With companies rapidly upskilling employees and rethinking leadership, ethics, and culture, the report argues that true advantage lies not in mastering AI tools but in building permanent adaptability across organisations.
As artificial intelligence reshapes workplaces across the world, organizations are confronting a challenge more complex than adopting new technology. The global workforce is entering a period where change is constant, skills expire rapidly, and traditional learning systems can no longer keep pace with the speed of transformation. Udemy’s 2026 Global Learning & Skills Trends Report offers a comprehensive and data-rich look into this shifting landscape, arguing that AI readiness is no longer about technical proficiency alone—it is about building a new operating system for how companies learn, adapt, and thrive in a world defined by permanent reinvention. The report synthesises insights from millions of learners and thousands of enterprises, ultimately positioning AI not as a finish line but as a catalyst for a broader cultural, organizational, and human transformation.
At the heart of the report is a central argument: AI fluency is not a technical goal; it is an organization’s new operating logic. As AI moves from specialized teams into everyday workflows, the distinction between those who merely learn tools and those who successfully integrate AI into decision-making, creativity, and strategy becomes increasingly stark. Most organizations, the report suggests, still think of AI readiness as a training problem—a matter of equipping teams with knowledge about prompting or using specific tools. Yet the real challenge lies in rewiring enterprises to work differently. Fluency means not only understanding what AI can do but learning to use it habitually, responsibly, and collaboratively. It requires employees to develop adaptive skills such as judgment, critical thinking, curiosity, and ethical reasoning, allowing them to evaluate outputs thoughtfully, question assumptions, and understand when to rely on AI and when to pause.
The surge in global demand for AI learning is unprecedented. According to Udemy, AI is the fastest-growing area of professional development worldwide. Learning consumption for tools such as Microsoft Copilot and GitHub Copilot has grown exponentially, with employees across sectors rushing to develop prompting skills and understand generative AI technologies.
AI agents and agentic AI—systems capable of making autonomous decisions and adapting to new situations—have seen the highest rate of learning adoption, signaling a widespread belief that future workflows will combine human creativity with AI-driven execution. Yet the report stresses that technical growth alone cannot secure long-term competitiveness.
To understand this transition, the report divides AI fluency into three levels: Augment, Assist and Automate, and Agentify and Rework. At the first level, employees gain foundational literacy—how AI works, what its limitations are, and how to use tools like ChatGPT, Google Gemini, or Copilot. This baseline understanding helps reduce anxiety and builds familiarity. At the second level, fluency expands into role-specific use cases. Marketing teams might rely on AI for personalization and analysis, while financial teams use it for risk forecasting. At this stage, organizations begin redesigning processes, not just tasks. The third level represents the frontier of AI maturity: integrating agentic systems capable of multi-step coordination, intelligent reasoning, and autonomous problem-solving. This requires rethinking workflows, governance structures, and leadership responsibilities at a fundamental level.
The report’s examples of companies adopting these models highlight the scale and ambition of global upskilling efforts. Genpact, a firm employing 125,000 people, created a 12-week learning program to teach generative AI fundamentals alongside advanced techniques. Within eight weeks, employees achieved 75 percent proficiency in AI and applied their knowledge to proof-of-concept projects. The company achieved 100 percent of its learning and development goal and built AI capability rapidly across teams
Another example, Devoteam, launched a generative AI training program for its 11,000 employees within three months, resulting in 70 percent of the workforce upskilled in AI and a measurable reduction in employee attrition. These cases underscore the urgency with which organizations are acting—and the growing recognition that AI fluency affects both productivity and retention.
Yet fluency cannot flourish through classroom learning alone. The report makes an emphatic case that immersion, not instruction, drives lasting skills. It points to research from Carnegie Mellon University showing that students who practice skills with immediate feedback learn three times more efficiently than those who rely on lectures alone. In the context of AI, learning in the flow of work becomes essential. Employees must be able to experiment with tools, build prototypes, test use cases, and iterate. Immersive learning environments—labs, sandboxes, contextual role-plays—ensure that knowledge is applied rather than simply memorized. Udemy reveals that more than 3,300 AI-powered role plays have been published within three months of launch, with enterprises designing customized scenarios to help employees strengthen both their technical and adaptive skills through real-time feedback. In one example, technology services company Prodapt reported that 90 percent of employees gained GenAI fundamentals after integrating micro-learning and practice-based training into their daily routines.
This shift toward continuous, contextual learning has broad implications for managers and organizational leadership. According to the report, leadership is the new bottleneck in AI transformation. While most employees agree that effective leadership is essential for the success of AI initiatives, only 48 percent believe their leaders are prepared for the AI era, and just 55 percent trust their management to mitigate AI-related risks. Companies like PepsiCo are attempting to close this gap by training leaders through structured programs aimed at operational excellence, resilience, and change management. PepsiCo’s program has been executed 35 times, reaching 1,200 employees with completion rates of up to 98 percent, and participants have been promoted at more than twice the rate of their peers.
The report argues that leadership in the age of AI demands a fundamentally different skill set. Instead of command-and-control models, leaders must act as coaches and catalysts who create psychological safety, encourage experimentation, and communicate AI strategy transparently. Leaders must also set ethical guardrails that help employees understand the boundaries of acceptable AI use, protect privacy, and recognize biases in automated systems. Udemy notes a 98 percent increase in learning around AI ethics and governance, reflecting growing concern about responsible implementation. Ethical stewardship, the report stresses, is as critical as technological know-how in an era where misused AI can cause reputational, financial, and societal harm.
Ethics is also inseparable from the concept of employee agency. Fear of job displacement, loss of privacy, and diminished human interaction are common anxieties surrounding AI. The report says these anxieties often stem from failed leadership rather than the technology itself. When employees lack agency—when decisions are made for them rather than with them—they become resistant to change. Conversely, organizations that distribute agency, allowing employees to design AI workflows and challenge existing processes, build stronger trust and more resilient transformation cultures. This empowerment model also accelerates learning as employees feel invested in shaping the future of their work.
But perhaps the most striking argument in the report is its insistence that AI should not be seen as the endgame. Transforming a company solely for AI risks setting an organization up for obsolescence when the next disruptive technology arrives. Instead, the true competitive advantage is adaptability, built through what Udemy calls adaptive skills. Skills such as critical thinking, communication, resilience, decision-making, and creativity have become some of the fastest-growing areas of learning. Decision-making courses grew 38 percent year-over-year, while critical thinking courses grew 37 percent. Adaptive skills enable employees to navigate uncertainty, learn new technologies quickly, and innovate in ways AI cannot. As the report notes, humans excel at originality, imagination, and navigating ambiguity—capabilities that remain essential even as AI becomes more powerful.
Integrant, another company featured in the report, recognized this. It adopted a skills matrix to measure both technical and adaptive skills across job roles, ensuring that employees develop the resilience and learning agility necessary to prepare for future transformations. The result was nearly 100 percent AI adoption and a 50 percent reduction in skills gaps for key competencies. Companies taking this approach, Udemy argues, are not merely preparing for AI—they are building cultures capable of surviving whatever comes next.
The final takeaway from the report is clear: the organizations that lead in the age of AI will be those that treat learning not as an event but as an engine. Permanent reinvention must become the operating norm. Learning pathways should not simply teach employees how to use AI tools but should help them cultivate judgment, communication, critical thinking, and resilience. Leaders must embed learning into performance metrics, reward cross-skilling, and normalize experimentation. They must refresh learning programs continuously and scan the horizon for emerging trends, building not just competency but strategic foresight.
In many ways, Udemy’s report reads not just as an analysis of current trends but as a manifesto for the future of work. It urges organizations to embrace discomfort, to view disruption not as a threat but as practice for the next transformation. The report’s message is ultimately optimistic: with the right learning systems, organizations can not only survive but thrive in the face of relentless technological change. The future, it suggests, belongs to those who build a human-centered, AI-enabled workforce—one capable of learning faster, adapting quickly, and leading confidently through uncertainty.
