AI

If publishers want to use AI meaningfully, they first need to know whether their own data is in a fit state to support it. Publishing data is not a neat database of facts waiting to be queried. It is a living, fragmented, territory-specific web of claims, registrations and human judgement. Anyone who has spent any length of time inside the operational machinery of publishing knows this instinctively- this is the world AI is entering.

AI is forcing every business to ask a difficult question: what work actually needs a human, and why? ‘Work’ is context, judgement, memory (personal and corporate), relationships, accountability, taste, intuition and the ability to discern why something matters in the first place. If those things are stripped out too quickly, the short-term efficiency gain can become a long-term organisational cost.

For all the noise around AI over the past year- new models, new capabilities, new fear- the most important developments haven’t been technical, but structural. In recent months, the UK government has tried to start defining an approach to one of the most consequential economic questions of the next decade: How do you build a world-leading AI sector without undermining the value of the content it depends on?

On Spotify’s latest earnings call, there was a few moments, including the quote “Technology is seldom disruptive on its own. Significant disruption happens when new technologies enable new asymmetric business models.” The real question isn’t whether AI is powerful, but whether it enables new business models entirely.