Jamie Bartlett is one of the UK’s leading technology writers, known for explaining in plain, human terms how technology changes the way we live, work and behave. For the past few years his focus has been artificial intelligence and what it means for the people now using it every day.
His books include The Dark Net (2014), a study of the internet’s hidden corners that was named a book of the year by NPR and the Washington Post, and The People Vs Tech (2018), which won the 2019 Transmission Prize and was longlisted for the Orwell Prize for Political Writing. He has also written and presented several hit BBC podcasts. The Missing Cryptoqueen, which followed the trail of a multi-billion pound cryptocurrency fraud and the woman behind it, reached number one in podcast charts around the world.
His latest book, How To Talk To AI (And How Not To), is a Sunday Times bestseller and one of the BBC’s books to read in 2026. It examines the risks and opportunities of tools like ChatGPT, and how we can stay in control of them. Jamie’s work on AI is not new: in 2010 he founded a research centre at the think tank Demos that used AI software to study social trends.
For corporate audiences, Jamie cuts through both the hype and the anxiety. He shows teams how large language models actually work, why so many AI projects fail, and what separates the organisations getting real value from those producing confident nonsense. His talks are practical and grounded, drawn from years of testing these tools and reporting on the people building them.
AI masterclasses for corporate teams
Alongside his speaking, Jamie runs hands-on AI masterclasses for corporate teams. These are practical, in-person sessions for groups of seven to twelve, built around the work people actually do.
Rather than theory, participants use real commercial AI tools through live exercises: spotting errors and hallucinations, sharpening their prompts, getting honest feedback rather than flattery out of a model, and building reusable prompts for their own roles. Each session is shaped around the group’s existing knowledge and the tasks they want to get better at.
People come away able to judge when AI helps and when it wastes time, how to spot when it is wrong, and how to get genuinely useful work out of it.
