The AI Illusion (II): The more “personal” it gets, the less it feels
AI promises better customer experiences.
However, as outlined in part 1, the real divide is not the tools themselves. It is how organisations think about using them.
Experiences are starting to feel increasingly similar. The tone is familiar and the interactions are predictable, largely because many companies are building them on the same foundations.
The result isn’t differentiation. It’s convergence.
What’s described as personalisation is often just classification at scale.
A customer who regularly buys vegan food may receive vegan recommendations. Someone who books business travel may receive business-focused offers. The system recognises patterns and adjusts accordingly.
That can be useful, but it is not the same as understanding context, intent, preferences, or emotion. It is recognition based on previous behaviour rather than genuine understanding.
The experience feels personalised because it references data. Whether it feels meaningful is another question.
There’s a difference between being recognised and being understood.
Everything functions. Nothing resonates.
The challenge is that many organisations are drawing from the same datasets, using the same models, and pursuing the same optimisation goals. Over time, they begin to sound alike. The recommendations become similar. The interactions follow familiar patterns. What starts as personalisation can gradually become standardisation.
AI improves the baseline. When everyone relies on the same systems, however, the baseline can quickly become the ceiling.
In part 3, I'll talk about how this sameness is rooted in a deeper shift: the collapse of creative barriers.