Speed Is Useful. Thin Messaging Is Not.

Sales teams are under pressure to do more with less time.

AI can help with some of that work, and leaders should not ignore that. A sales team can use AI to prepare for a customer call, summarize account history, compare product information, draft outreach, identify buying signals, or shape a first version of a proposal.

The problem starts when speed is treated as the same thing as substance.

Technical buyers can usually feel the difference between a message that was prepared well and a message that was only polished. They may not know exactly which tool created it, but they know when the answer does not match their real question. They know when the proof is missing. They know when the person on the other side cannot explain the trade-off, the fit, the limitation, or the next step.

Gartner also found that 45% of B2B buyers used GenAI during a recent purchase. That means buyers are not waiting for sales to bring them the first version of the answer. They may already have a summary, a comparison, a shortlist, or a set of assumptions before the first conversation begins.

That changes what sales has to earn.

The New Sales Problem Is Validation

The useful question is not whether AI belongs in sales.

It does.

The better question is where AI should assist, and where a person still needs to review, challenge, clarify, and own the answer.

This is especially true in technical markets. A customer may be comparing products, applications, specifications, availability, integration risk, service support, or long-term supplier fit. A fast answer helps only if it is accurate enough to use.

Gartner found that 67% of B2B buyers prefer a sales rep-free experience, while the same research on AI-generated insights shows buyers still turn to sales reps when they need validation, reassurance, context, and decision support.

That is not a contradiction.

Buyers are not saying people do not matter. They are saying low-value interruption does not matter. They want to move independently when the work is simple or the information is clear. But when the decision carries risk, they still need someone who can help them know whether the answer is good enough to trust.

For sales leaders, this means the role of the seller is changing. The seller is not always the first source of information anymore. The seller becomes the person who helps the buyer make sense of information that already exists.

Credibility Is the Part AI Cannot Fake

This is where my conversation with Michael “Mic” Cardone, President of ENOVA USA, is a useful proof point.

Mic shared a line from earlier in his career that stayed with him. A VP of operations told him that salespeople were “all foam and no beer.” It was blunt. It also named a real credibility problem.

A message can look good and still have no substance behind it.

That is the risk AI can make easier to miss. A team can generate better-looking outreach, cleaner campaign copy, faster summaries, and more polished responses. But if the customer asks one more question and the substance is not there, the trust problem shows up quickly.

For leaders, the work is not to slow everything down. The work is to build a better review layer around the places where credibility is earned or lost.

Before an AI-assisted message reaches a customer, someone should be asking:

• Is the product information accurate?
• Does this match the customer’s real context?
• Are we making a claim we can prove?
• Does this sound like our company or like a generic tool wrote it?
• Who owns the final answer if the customer acts on it?

That last question is the credibility test.

AI can support the first draft, the first search, the first comparison, and the first summary. The last mile still belongs to the person who understands the customer, checks the answer, and can stand behind the recommendation.

Listen to the full conversation with Mic Cardone.

AI will keep changing how sales teams prepare and how buyers research. That is not the part to resist. The risk is using better tools to create more output without building the discipline to check what the output means.

Technical sales still runs on trust. AI can help your team move faster, but credibility is still earned by the people who know the product, understand the customer, and take responsibility for the answer.

Sannah Vinding