AI as input multiplies; as output replaces

With the state of AI as I use it, a simple distinction keeps returning. If the output of an AI system is an input or building block of an individual’s or organisation’s output, it makes them more efficient and productive. If the output of the AI system is the same as the output of the individual or organisation, it makes them redundant.

That is not a moral claim about tools. It is a placement claim. Where you sit in the chain relative to the model decides whether the tool multiplies you or substitutes for you. The useful question for a person, a team, or a region is therefore not only “do we use AI,” but “are we still the ones who own the final work that matters?”

As AI makes it easy to build products, customise them, and migrate, customer stickiness becomes doubtful. Competition, price pressure, and in-house tools follow. Moats that assumed switching cost and scarce builders need a new story: trust, data gravity, operations, or depth that still takes years.

The interfaces where reality becomes data, and data becomes reality, also gain value. Moving bits inside the digital world is getting easier. The scarce work concentrates at the entry and exit points: sensing the world truthfully and acting back on it reliably.

Drawn from writing on X as devendrasm on AI placement, stickiness, and reality–data interfaces.