AI Converged Your Innovation With Your Competitor's

Imagine two direct competitors, both using AI to screen and prioritize innovation opportunities. Models trained on similar market data, similar success benchmarks, evaluation logic built on the same industry references.

When the inputs are similar, the outputs tend to converge. Not because the companies coordinated, but because the criteria the AI learned to value are essentially the same. It is optimizing for the same market signal.

The result: pipelines accelerating in the same direction. Competition is no longer about which idea to pursue, and has become about who can execute the same idea first. Efficiency in the process. Convergence in the destination.

This raises a question I still see few people asking: if the opportunity filter is the same for everyone, competitive advantage no longer comes from selection. It comes from execution, from proprietary data no public model has seen yet, or from a strategy that deliberately moves against the consensus generated by these systems.

The companies that will win in this environment are not necessarily the ones with the best evaluation model. They are the ones that understood where their competitors' AI is looking, and decided to go where it has not yet arrived.

Have you noticed this convergence in your industry? Tell me in the comments how you are dealing with it.