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AI in 2025: What Worked, What Failed & What’s Next in 2026
When AI Stopped Being Magic: What 2025 Taught Us About the Real Work Ahead
What happens when the shiniest new technology stops dazzling us and starts demanding something far more difficult: actual change?
John Hetherington brought the rain but not the cold when he flew in from Canada to London, a fitting metaphor for the conversation that followed. Because whilst 2025 didn't freeze AI innovation in its tracks, it certainly dampened some of the euphoria that characterised the previous three years. And according to John, that's precisely what needed to happen.
"After the whole 2022 release and then 2023 hype and 2024 even more hype, 2025 seemed to hit a bit more of a trough of disillusionment," John explained, invoking the Gartner hype cycle with the weary familiarity of someone who's seen this pattern before. "A lot of people were like, Is it really giving what we expect? Is it giving the value we were promised?"
The question wasn't rhetorical. Across boardrooms in North America and beyond, companies were demanding proof. The grand promises of massive cost savings and transformative productivity gains were meeting the cold reality of spreadsheets and quarterly reviews. 'Show me the numbers,' executives insisted. Prove it works.
In this episode of the Project Flux podcast, James, Yoshi and John discuss the key trends and realisations from 2025 in the realm of AI, including the cultural shifts in adoption, the importance of context in implementation, and the challenges of accountability and ROI. They also make predictions for 2026, exploring the evolving dynamics between consultancy and tech companies, the regulatory landscape, and the future of robotics and AGI.
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