Entrepreneur op-ed: chasing every AI model upgrade can hurt, not help, businesses
An Entrepreneur contributor argues that companies often rush to deploy new AI models the moment they show marginal accuracy gains, without weighing the real costs of testing, deployment, monitoring and engineering labor. The piece uses an example of a model that improves just 0.2% to show how such upgrades can cost far more than they're worth while customers notice no difference. The core argument: technical accuracy gains and genuine business value are not the same thing, and conflating them leads to wasteful decisions.