The Judgment Gap: Why AI Drafts but Will Not Decide

A veteran financial advisory consultant sees today's AI as a fluent but immature junior that drafts well and decides nothing, making human judgment and disclosure the real premium.

This brief captures one senior financial and M&A advisory consultant, a former CFO with an audit background, reflecting on AI in high-stakes professional work. His core view is that AI writes like a junior professional: verbose, polished, and unwilling to make a directional call. For clients paying premium rates, that is precisely the missing ingredient. He warns that the productivity story is overstated for narrative work, because verifying AI-generated prose and slides to a standard he will sign his name to takes about as long as starting from scratch. He trusts AI mainly for quantitative tasks like projections and industry analysis. Drawing on his audit discipline, he applies a personal governance rule: label AI content openly, then add his own commentary on what matters. He recounts telling a chief operating officer to stop using AI for emails and a peer who refused an AI-drafted recommendation, both wanting his authentic voice even with small errors. He reframes AI hesitation as a capability gap, a lack of training to judge when machine output is fit to send. Taken together, his perspective points executives away from measuring raw generation speed and toward net value after human review, disclosure norms that protect trust, and training in critical evaluation of AI output.