A customer asks whether you can deliver three weeks early.
The salesperson knows why the date matters. Operations knows which commitments would have to move. Finance knows what the exception would cost. Somewhere, somebody has the authority to say yes.
Now imagine asking an AI agent to handle that request.
Before you decide what the agent should do, your team has to agree on what the business should do. That conversation deserves someone who has had to earn a customer’s trust, negotiate competing priorities, and live with the consequences of a promise.
Sales experience belongs in that room.
What sales can teach an AI team
I’ve been writing about the CEO trust gap and the way we prepare people for leadership. One concern keeps coming back: how much responsibility do we give people before asking them to demonstrate that they can lead through disagreement?
Complex sales gives people repeated opportunities to learn that skill.
A customer may want speed while procurement wants another review. A technical sponsor may love the solution while the person accountable for the budget questions the need. Inside your own company, the delivery team may have a good reason to resist the terms that would win the deal.
A capable salesperson has to understand those interests well enough to help people reach a decision they can support. That takes patience, commercial judgment, and a willingness to hear something inconvenient.
Those same abilities matter when a company introduces AI into its work.
Someone has to ask why a process exists, whose problem it solves, and who will carry the cost if the new approach gets it wrong. Someone has to bring the people with conflicting answers together.
A strong sales professional may be well prepared to do that. Look for evidence in how they work.
Start with the promise to the customer
Take that early delivery request. This is an illustrative example, but the questions are familiar.
Your current process might be described as “sales submits the order, operations schedules it, and the customer receives a confirmation.”
That description leaves out most of what matters in an exception.
Has the customer made a firm commitment, or are they asking what is possible? Is the requested date tied to an installation, a contract obligation, or a preference? Which other customer would wait longer? Who can approve the added cost?
An AI tool can help organize the request, retrieve permitted information, and prepare a response. Your team still needs to decide what information counts as current, which decisions it may make, and when a person must take over.
If those rules are unclear, a polished response can get ahead of an operational commitment. Sales then has to repair a promise the company should never have made.
This is why I want experienced salespeople involved early. They can help explain what the request means to the customer and what would happen if the answer were wrong. Operations, finance, and technical colleagues supply knowledge they cannot supply alone.
Find the work people do between the steps
A useful working session begins with a recent case.
Ask the people involved to walk through what happened. Open the records they actually used. Follow the handoffs. Pay attention when someone says, “Usually we do this, except when…”
That exception may explain why the written process differs from the work.
Perhaps an account manager checks with a particular colleague because the scheduling system does not reflect a temporary capacity limit. Perhaps finance approves a term for one contract type but requires a separate review for another.
Those decisions need a clear owner and a reliable source of information before you ask software to act on them.
They also need scrutiny. An undocumented workaround might protect the customer, or it might be a bad habit that creates more work elsewhere. The person who knows it deserves a hearing; the process still deserves a challenge.
Sales professionals with good discovery skills can help run that conversation. They know how to ask a follow-up question when the first answer sounds complete but leaves the real problem untouched.
Give people a reason to tell you the truth
The employee who knows the workaround may also wonder what happens to their job after they explain it.
Leaders have to take that question seriously.
If a team has watched colleagues leave while work moves elsewhere, another request to document everything can feel threatening. Adding AI to the request does little to resolve that concern.
Research gives us a reason to pay attention. A meta-analysis of job insecurity and performance found negative associations with task performance and the helping behavior that supports colleagues. It does not establish a productivity penalty for every offshoring decision.
For an AI project, my concern is practical: will people bring forward the exceptions, uncertainty, and mistakes you need to understand?
Tell them why you are examining the work, how decisions about roles will be made, and what remains undecided. Give them time to contribute. Recognize the knowledge they bring. Then show them how it changed the plan.
Your people are not an expense necessary to run the business.
Your people are the business.
That includes their ability to recognize a customer problem the process never anticipated.
Develop a bench with evidence
A sales title alone tells you very little about someone’s readiness for broader leadership.
Look at how the person handles a deal that should be declined. Ask operations whether they involve the delivery team before making difficult commitments. Watch what happens when a customer challenges their assumptions.
Then give promising people a bounded assignment: lead the review of one workflow with colleagues from other functions.
Have them explain the customer outcome, surface the disagreements, document who can decide, and recommend one change. Include someone responsible for delivery and someone responsible for the systems involved.
You will learn more from that work than from a discussion about whether salespeople generally make good executives.
Some people will need coaching in listening. Others will need a stronger grasp of margins, capacity, or risk. A successful individual seller may need practice sharing responsibility and developing others.
That is useful information for a leadership bench. It tells you what to develop next.
Put the development into the work
An AI initiative gives you an opportunity to improve a workflow and develop the people who will lead its next version.
Include sales professionals who can connect a customer’s need to the decisions the business must make. Give them colleagues who will challenge them. Judge the result by whether the team can keep its commitments more reliably.
If you are developing that capability in your sales team, ask about OnPoint SPARK™ sales training. We use AI to help drive revenue momentum, and show you how to integrate them effectively in your own org.
Tell us who you want to develop and where customer conversations or internal handoffs are breaking down. We can discuss whether SPARK fits the work your team needs to do.
