Adaptive Products Need a Predictable Core
Games have adapted difficulty, rewards and offers around player behaviour for years. AI lowers the cost of doing it everywhere — and raises the cost of operating it.
Most software is designed to help you finish today’s task. Games are designed to make you want to come back tomorrow.
That difference changes how the product is built.
A banking app benefits from consistency. A game cannot assume that the same experience will work equally well for a new player, someone who is stuck, and someone who has already mastered the system. The same level can lose one player because it feels too difficult and another because it feels too easy.
That is why games have spent years adapting difficulty, guidance, progression, rewards, LiveOps and offers around player behaviour. The objective is not personalisation for its own sake. It is to keep challenge, pacing and motivation in balance.
None of this started with AI.
What AI changes
What AI changes is the operating cost. Systems that previously depended on manually defined segments, rules, exceptions and overrides can increasingly use behaviour, context and history to decide what should happen next.
Sometimes that means offering guidance. Sometimes it means increasing the challenge, rewarding progress or delaying an offer. Sometimes the best product decision is to do nothing.
The uncomfortable part is that adaptive products are also harder to operate. Experiments become harder to interpret. Bugs become harder to reproduce. Support gets more complicated when two users may no longer be experiencing the same product.
So the goal should not be to make the whole product adaptive. Keep the core predictable. Adapt the few decisions where context materially changes what the right experience should be.
Gaming has been managing that trade-off for years. AI is making it relevant to everyone else.