Where AI genuinely helps a commercial team

Reading volume, clustering similarity, drafting structure. Not deciding, not judging, not being trusted without a source. The commercial teams getting genuine value from AI are the ones who drew that line early, and have kept to it even as the tools have become more capable and more persuasive-sounding.

Where AI earns its place

AI is genuinely useful at the tasks that involve processing more material than a person reasonably can. Reading through hundreds of job adverts, news mentions or filings to identify which ones might be relevant is a volume problem AI handles well. Clustering similar signals together — noticing that several unrelated data points describe the same underlying pattern at a company — is another. Drafting the first structure of a written brief, a summary, or an outreach message, ready for a human to check and refine, is a third. In each of these cases, AI is doing preparatory work that speeds up a person's job without replacing their judgement.

Where it should not be trusted

The line gets crossed when AI output is treated as a verified fact rather than a starting draft. An AI-generated summary of a company's situation can sound entirely confident and entirely plausible while containing an inference presented as though it were confirmed. That is the exact failure mode that damages a sales team's credibility with a prospect — opening a call with a claim that turns out to be wrong because nobody checked the underlying source before it reached the rep.

The principle worth keeping

Evidence first, AI second, sales intelligence third. AI is a genuinely valuable layer in a modern commercial process, but it sits on top of verified evidence, not in place of it. Teams that keep that ordering get real efficiency gains from the technology. Teams that invert it — letting AI decide what counts as a fact — tend to discover the cost of that mistake in a lost deal, or a prospect who simply stops replying.