India, Aug. 19 -- As enterprises increasingly turn to AI to get work done, three new weapons are emerging in their fight to control spiralling AI adoption costs: agent harness, model selection and inference economics.

Simply put, AI adoption is no longer being judged solely on model capabilities, benchmarks or impressive agent demos, but on whether these systems can deliver measurable productivity gains without pushing project costs higher.

As AI moves from pilots into everyday enterprise workflows, the cost of every model call, token, inference and computing resource begins to add up. The bigger question, then, is not simply which model an enterprise uses, but how the entire AI system is designed around it.

Companies are increasingly ...