New research from O’Reilly, the leading source for insight-based learning in technology and business, suggests that UK technology professionals are building on their existing programming expertise and adopting new AI-powered tools and learning methods.
Analysis of usage of the O’Reilly platform from Q1 2025 to Q1 2026 shows an 89% increase in the usage of Generative AI content in the UK. Overall, AI and machine learning has grown by 51% in the UK, with data now accounting for 31% of all platform usage in the UK, making it the number one topic on the platform.
“Our data captures a workforce that is rapidly transitioning to AI,” said Alexia Pedersen, vice president of international affairs at O’Reilly. “UK technology professionals are not just experimenting with generative AI, they are putting it at the core of their learning priorities. Many already have years of programming experience and are well placed to confidently deploy and apply AI tools in meaningful ways.”
Although the use of some established programming topics has declined over the years, O’Reilly cautions against interpreting this as a collapse of coding skills. O’Reilly believes this data reflects a broader shift in the way experienced developers learn.
AI-powered coding assistants and chatbots are now embedded in the development environments where day-to-day work takes place. As technology professionals face challenges and solve problems, they’re learning coding skills that traditionally took up their time in formal training. These employees are free to use this training time to focus on building skills in the rapidly evolving landscape of AI, learning by doing, generative AI, and more.
In the UK, programming fundamentals decreased by 73 per cent year-on-year, as did two topics related to established software engineering workflows: Agile (down 31 per cent) and Git (down 20 per cent). O’Reilly believes that these trends do not signal a decline in coding ability, but rather reflect experienced developers relying more on AI-assisted workflows for day-to-day development. Meanwhile, natural language processing sessions increased by 117% year-on-year, demonstrating strong engagement in one of the most applied areas of AI development.
O’Reilly cautions that AI fluency should always complement, rather than replace, basic programming knowledge. This is especially important for early-career developers, as over-reliance on AI tools can reduce the judgment needed to review, debug, and improve code.
“What this data captures is that employees are making active choices about where they spend their time,” Pedersen said. “Technical professionals in the UK are not casually browsing AI content; they are incorporating technical learning into new ways of working, building AI agents, testing different approaches, and exploring how these tools can improve productivity and outcomes. Importantly, many of these learners are not starting from scratch; they already have a strong programming foundation, so they can confidently explore AI can be implemented immediately and applied in a meaningful way.”
AI is changing how developers learn, but what employers expect remains the same. React, Node.js and Java remain among the most popular technologies in UK job advertisements, and cloud certifications continue to be valued by employers as evidence of technical competency.
And the demand for good engineering practices remains clear. In the UK, learning clean code has increased by 19% year-on-year, and C# has increased by 17%. This suggests that even though AI is receiving more attention, learners are still investing in hands-on coding abilities.
“The UK’s technology workforce is not turning its back on programming; it is building on years of engineering expertise to take advantage of the opportunities created by AI. That’s exactly what we expect from our experienced developers. The challenge now is to ensure the next generation can develop the same foundations before relying too heavily on AI,” Pedersen concluded. “AI can make great developers even better, but it cannot replace the technical judgment that comes from understanding how software actually works.”
