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Why Selling AI is Harder Than You Think

Why Selling AI is Harder Than You Think

 

By Matt Dixon and Ted McKenna

Here’s a story we hear some form of on a weekly basis these days:

A sales organization launches a new AI-powered technology to much fanfare and acclaim. Buyers are eager to learn, explore, book a visit and, after a short conversation, jump at the chance to see demonstrations of its capabilities. The seller—ecstatic at the palpable excitement and desire the buyer has arrived at largely on their own—quickly brings their subject matter expert in for the next visit. After what feels like the best demo they’ve ever witnessed, with the buyer asking detailed questions, the rep forecasts the deal to close soon.

But then the next week that same prospect requests another demo, only this time with other technical folks on their side. And yet another, only this time to pressure test your models. And then they start asking about a free trial or for a proof of concept. And then…crickets. Buyer goes cold or, even worse, totally dark. Can’t even get a reply to an email. Months of work and consideration goes down the drain.

This is the fear of messing up (FOMU) on display. The buyer, convinced of the need to change but consumed with fear of being blamed for a wrong decision, starts worrying that an enticing yet uncertain and unproven technology will burn them down the line.

We first coined the term “Fear of Messing Up” when we found evidence of it in our study of 2.5 million sales calls in 2022, featured in our book The JOLT Effect: How High Performers Overcome Customer Indecision. Our research proved that indecision is actually the biggest driver of sellers losing to “no decision.” Beating the status quo, which is primarily about dialing up the fear of not purchasing, is necessary but insufficient in getting to a purchase. Overcoming indecision requires sellers to dial down the fear of the purchase: it’s the purchase itself that drives the fear that something will go wrong, at which point people start pointing fingers and assigning blame to the person who made that decision.

Emerging technologies like AI are really the poster child for the potential to drive FOMU for buyers. Which is understandable. Most of us have, at various points in our own lives, felt like we’ve been oversold or have overbought in the past. When evaluating any unfamiliar technology—no matter how technically superior it may be—buyers wonder from the outset: 

  • Is this product really ready for primetime or are they rushing an unfinished product to market? 
  • Are they overpromising, given our experience with other AI products? 
  • Can our team really replicate these outcomes and returns that others have reported?
  • How can we get more assurance we can achieve outcomes that currently feel far too uncertain?

Particularly confounding for sellers is the fact that buyers are legitimately interested and engaged—at least, initially—making it easy to confuse excitement or activity with deal progress. And the hesitation is rooted at least as much in the buyer distrusting themselves and their ability to pull it off than it is about concern around value or ROI. 

What can teams do to sell more AI-related products in the face of FOMU? Here are four tips for sellers and sales leaders on where to get started:

1. Don’t: Make things worse

In our study, 73% of sellers mistreat indecision, acting in such a way as to make it actually less likely the buyer makes a decision. Most sellers assume “cold feet” moments are rooted in a lack of persuasion—the buyer must not want it enough!—and the instinct to fight that hesitation by throwing more pain and fear at the situation runs deep. Running the wrong playbook at the wrong time can cause critical failures on even the strongest-fit pursuits. 

2. Don’t: Wait until it’s too late

FOMU can set in quite early—perhaps even before the seller engages. This runs counter to what most think about indecision—that it sets in only in late sales stages after the buyer is convinced of the need to change. It’s true, of course, that in early stages the seller’s primary goal is to beat the customer’s status quo. However, the data is clear that indecision can be detected from the very first conversation with a buyer. But far too many sellers wait far too long to address indecision, too often caught by surprise in late stages where, by that point, it feels very difficult to do anything about it. The best sellers are proactive in detecting and treating indecision as early as possible.

3. Do: Weed out the junk

Most sellers misinterpret signals that indecisive buyers send across the purchase journey. Excitement and engagement may be good signs a buyer wants to purchase but can be totally independent of whether they are feeling FOMU. Consequently, much time is wasted chasing opportunities that will never close. Even worse, buyers also are left feeling they wasted a lot of their own time, stuck in a never-ending cycle of purchase exploration. Over time, word gets around and suppliers end up with—perhaps unfair—reputations of being too hard to buy from.

4. Do: Sharpen forecasts

Most sellers completely miss signs their buyer is struggling with indecision. Why? The buyer often isn’t aware that it is affecting their decision making—after all, they are typically relatively senior executives who regard themselves as very rational people—or, even if they are aware, they aren’t likely to explicitly admit to it. The best sellers are listening for signs not just that the potential customer can buy but also whether and when they can even make a decision. That information needs to find its way into forecasting expectations that roll up across the organization.

For any team selling AI or some other emerging technology, treating indecision will improve seller efficiency and win more deals by reducing the likelihood of “no decision” outcomes. But win rates also will rise for another reason: helping indecisive buyers presents an opportunity for sellers to separate themselves relative to others in the market. In other words, suppliers best able to help buyers gain comfort with uncertainty also gain a competitive advantage, increasing the odds of winning close fights.

To learn more about The JOLT Effect, visit us at www.jolteffect.com.

About The Author

Ted McKenna

Ted McKenna is a co-founder and CEO of SellingInnovations and is one of the world’s leading experts in sales, business development, and customer experience. A co-author of the bestselling book The JOLT Effect: How High Performers Overcome Customer Indecision and the upcoming book The Activator Advantage: What Today’s Rainmakers Do Differently (April 2025), Ted’s research frequently appears in the pages of Harvard Business Review. He is also a founding partner of DCM Insights, a company that uses data and research-backed frameworks to help professional services firms improve business development. An experienced business leader—having held numerous executive positions in product, strategy, research, advisory, and enablement for Tethr, Russell Reynolds Associates, and CEB (now, a part of Gartner)—Ted is an expert in analyzing behaviors and applying analytics in various forms of content, products, and services. As part of a large-scale study of 2.5 million sales calls, Ted worked on mining unstructured conversational data using advanced data science and leading AI/ML tools to build models, scores, and behavioral frameworks (the most well-known model is the Tethr Effort Index). Previous roles called for deploying syndicated research methods to mine more structured sources such as surveys, diagnostics, demographics, and jobs data (including research contained within the bestselling book, The Challenger Sale). Ted holds a B.A. in Economics from the University of Iowa and resides with his family in the Chicago, Illinois area.

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