​Great AI Systems Need A Human Touch

Innovation​Great AI Systems Need A Human TouchByAmbarish Majumdar,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)Jun 03, 2026, 09:45am EDT--:-- / --:--This voice experience is generated by AI. Learn more.This voice experience is generated by AI. Learn more.Ambarish Majumdar is a Marketing Science Partner at Meta, where he uses his SME knowledge in Marketing Science to better AI models. getty​As enterprises accelerate AI adoption, most conversations begin with model selection, infrastructure and deployment speed. Those decisions matter, but they are rarely what determine whether AI succeeds in production. The real difference between a system that looks impressive in a demo and one that creates lasting business value is human judgment.That human layer comes from subject-matter experts (SMEs).Large language models can generate fluent, fast responses, but fluency should not be mistaken for quality. A model can sound confident while giving the wrong recommendation, missing a compliance issue or creating customer friction. In enterprise environments, quality is rarely just about correctness—it is about trust, context and decision-making.Anthropic captured this clearly in its writing on evaluations: Evals are not the final checkpoint before launch. They are the foundation of responsible AI development.My experience working with AI models that power ad ranking and relevance for Bing at Microsoft underscores a critical truth: Automated systems, no matter how sophisticated, cannot fully replace human judgment.Consider a client case I worked on. Our AI models served advertisements for a popular SUV when users searched for the SUV's model name. Internal quality systems flagged these placements as high-fidelity matches; after all, the keyword and the ad were lexically aligned. However, a human review of the user sessions told a...