Within the past month, the number one burning issue I have heard from business leaders, ranging
The argument sounds logical.
“You’re using AI. AI makes your people more productive. The work takes less time. Therefore, you should charge me less.”
Maybe.
But maybe not.
For any business, using AI has two edges to the sword. On the one hand, when people who know what they are doing use AI effectively, they can create significant efficiencies, produce better work faster, and sometimes more cheaply.
On the other hand, AI isn't free, and there is a much steeper learning curve than most people understand. Companies are investing enormous amounts of money in platforms, infrastructure, integration, security, governance, training, and new capabilities. And when you factor in rework and lost productivity from people misusing AI and producing what has affectionately become known as “AI slop,” the economics aren't nearly as simple as customers might think.
But in business, perception is reality.
And customers increasingly perceive AI as a cost-saving tool. Which means this conversation isn't going away.
I spoke with clients and industry leaders and reviewed emerging thinking from academia and the consulting world. Based on that research, here are five ways I think business leaders should handle the objection:
1. Stop Defending Your Costs and Start Defining Your Value
The first mistake is responding to the question by explaining why AI isn't really saving you that much money. Nobody cares.
Your customer doesn't want to hear about your AI licenses, implementation costs, governance committee, or how much time your people spent learning how to prompt an agent.
They care about the value they receive.
If AI allows you to deliver a better answer in three days instead of three weeks, is that worth less, or potentially more?
If AI enables a pharmaceutical company to identify an issue earlier, a professional services firm to analyze significantly more data, or an engineering company to reduce project risk, the economic value to the customer may actually increase even though the amount of human labor required decreases. That's the conversation you want to have.
2. Don't Confuse Hours with Value
This may be the biggest challenge for professional services firms.
For decades, many businesses have essentially priced human effort. Ten people working 100 hours each equaled 1,000 billable hours. Everyone understood the model.
AI starts blowing that model apart. If those same people, with AI support, can produce a superior outcome in 600 hours, should the customer automatically receive a 40% discount?
I don't think so. The customer isn't buying 1,000 hours. They are buying expertise, judgment, intellectual property, risk reduction, speed, and an outcome.
This is why AI is going to accelerate the move toward fixed fees, milestone pricing, shared savings, outcome-based pricing, and other models in which price is more closely tied to value than to labor consumed.
The fascinating irony is that AI may finally force companies to price what they actually create instead of how long it took them to create it.
3. Share Some of the Productivity Dividend
That doesn't mean customers should receive nothing.
If AI creates real, sustainable efficiencies, good business says that some of those benefits should eventually make their way to customers. But not necessarily all of them.
Think about the productivity improvement as a dividend that can be shared among several stakeholders. Some can go to the customer through lower prices or more services for the same price. Some can go to employees through better tools and less low-value work. Some can be reinvested into innovation. And some should accrue to the company and its shareholders as the return on the initial AI investment.
If every dollar of AI-generated productivity is immediately surrendered through lower prices, there isn't much economic incentive to make the investment. The smarter discussion isn't, “How much should we cut the price?”
It is, “How should we share the value we've created?”
4. Make the Invisible Value Visible
This is where many companies will struggle.
AI will increasingly do things the customer never sees.
It might run thousands of scenarios before a recommendation is presented. It might identify risks humans would have missed. It might enable your team to examine ten alternatives instead of three. It might provide quality assurance, challenge assumptions, synthesize massive amounts of information, or help an expert spend more time thinking and less time searching.
That is value. But if customers don't understand it, they will naturally conclude that AI simply made the work cheaper.
Companies, therefore, need to get much better at articulating what AI actually enables.
Instead of saying, “We used AI to make the process more efficient,” say, “We were able to evaluate 14 scenarios, identify three risks earlier, and reduce the project timeline by two weeks.”
Now we're talking about business outcomes instead of technology.
5. Be Ready to Walk Away from the Wrong Economics
This may be the hardest one. Some customers will simply say, “I know you're using AI, so I expect a 20% reduction.”
At that point, you have a business decision to make.
Maybe the strategic value of the relationship justifies it. Maybe your AI-enabled operating model really can support the reduction while maintaining acceptable margins. Maybe you can redesign the scope. Or maybe you shouldn't take the business.
AI doesn't repeal the laws of economics.
Revenue still has to exceed costs. Investments still need returns. Businesses still need margins and cash flow. And customers who continually demand every productivity gain eventually create suppliers who can no longer afford to innovate for them.
That's not a sustainable partnership.
The Bigger Question
There is an interesting twist to all of this.
Customers are asking suppliers to lower prices because suppliers are becoming more productive with AI. Fair enough. But what happens when the customer becomes more productive with AI?
If my work helps your organization generate $20 million of value instead of $10 million because your employees are now using AI to implement my recommendations faster and more effectively, should I be able to double my price?
Probably not.
And that's exactly the point.
Price has never simply been a mathematical calculation of the seller's cost.
Price sits somewhere between cost, competitive alternatives, willingness to pay, and value created.
AI doesn't change that fundamental principle. What AI does change is the conversation.
For years, businesses have talked about AI primarily as a technology issue. Then it became a productivity issue. Now it is becoming a pricing issue.
And very soon, I think it will become something even bigger:
Who gets to keep the value AI creates?
The answer, of course, is probably some combination of all four.
Figuring out the right combination may become one of the most important business acumen challenges of the AI era.