Last year, a highly decorated deal team in the investment space lost a bid they should have won.

The model was right. The data was right. The team had every analytical reason to believe they were positioned to win. But in the room with the founder, something happened that models can’t capture: no one asked the question that mattered. 

However, the competitor did.

“They read something human in that meeting — something no model had flagged — and they acted on it,” says Alexander Tolstoy, a director at Stand & Deliver. “That’s not a story about AI failing. It’s a story about what happens when we forget to train the other side.”

That “other side” is becoming one of the most important variables in business. As AI becomes more capable, more accessible and more deeply embedded into daily workflows, the advantage it creates is also becoming easier to replicate. Organizations that once differentiated themselves through analytical sophistication, processing speed or technical modeling may soon find that those capabilities are no longer enough.

The next competitive edge may come from what AI cannot commoditize: human judgment, trust and the ability to lead when certainty runs out.

The Analytical Advantage Has Changed

AI is not weakening the importance of analysis, but it is raising the baseline.

Models can process enormous amounts of data, identify patterns, synthesize information and generate options with speed and consistency. For many organizations, that creates real value. But as more firms gain access to similar tools, the gap between them begins to narrow.

“Analytical parity is becoming table stakes,” Tolstoy says. “If your edge was the quality of your model or the speed of your processing, that edge is compressing fast.”

He points to a conversation with a senior leader who had recently sat through board presentations from three different management teams. They represented different companies, but the experience felt strangely uniform.

“Three consecutive management teams — three different companies — had used almost identical slides. Same frameworks. Same language. Same AI-assisted logic,” Tolstoy adds. “He said, ‘I couldn’t tell who was running which business.’”

That’s less of a technological problem and more of a differentiation crisis. 

When every team has access to clean analysis, polished slides and AI-assisted logic, sameness becomes a business risk. The question is no longer whether leaders have the information, but whether they can use it to create trust, make meaning, build alignment and inspire people toward action.

The human edge AI can’t commoditize

For years, capabilities like presence, listening, judgment and trust-building have often been categorized as “soft skills.” In an AI-driven environment, that framing is increasingly inadequate. More than ever, these abilities are what define the human edge, or the advantages AI can’t replicate. 

Lars Strannegård, president of the Stockholm School of Economics, describes AI as mimicking the logical and computational part of human ability. Yet, according to Strannegård, human intelligence is much wider — “empathy, perception, the ability to read what’s really happening in a room, the courage to say something difficult. Machines will always be better at being machines. The question is whether we get better at “being human.”

“The better AI gets, the more exposed the human layer feels,” Tolstoy adds. “Not incompetent — exposed. Because the questions that now land on the managers’ desks are the ones the model couldn’t answer. They’re judgment calls. They’re conversations where the relationship is on the line.”

In other words, the human edge isn’t about being warmer, more charismatic or more polished for its own sake. It’s more about what leaders do in unscripted moments when data is incomplete, the stakes are high and they can’t generate an answer on command. 

Take the ability to understand what’s actually happening in a room, for example. To notice hesitation, resistance or unspoken risk. To know when a team needs candor and when it needs confidence. To ask the question that changes the conversation.

“Those aren’t soft skills,” Tolstoy says. “They’re hard-edged business drivers.” 

That distinction matters. Communication is a key part of how decisions are made, tested, challenged and carried through an organization. It shapes whether people speak up, teams align and if ideas come to fruition. 

The Power of Real-Time Judgment

One of Tolstoy’s examples involves a young leader at an investment firm. The team was moving quickly toward a close. The model was clean. The numbers worked. Every analytical signal pointed in the same direction.

But something felt wrong. The concern was difficult to articulate. The management team looked strong on paper, but the young professional sensed a lack of focus. The core offering felt scattered. No slide proved it, no memo captured it, no data point gave them an easy case.

Still, they raised the concern with their managing director. After reevaluating the deal, they confirmed what they sensed, but the model could not. The firm passed on the deal — and in retrospect, it was the right call. 

“What stayed with me about that story wasn’t that they were right,” Tolstoy explains. “It was where the judgment lived — not in the analysis, but in the room. In the willingness of one person to say the uncomfortable. And in a managing director who created enough safety that they could.”

These tangible outcomes require conditions where people feel comfortable surfacing doubt, naming risk and challenging momentum, even before the cost becomes visible. Without those conditions, organizations may still make fast decisions. They may even make well-documented ones. But they may miss the human signals that determine whether those decisions hold.

Developing human capacity by design

As AI handles more of the analytical layer, the bar for human performance shifts away from processing and speed. Instead, leaders judge it based on precisely the things AI can’t do, such as the quality of one’s discernment in ambitious situations, their ability to read a room and whether others trust them enough to tell the truth. 

The challenge is that these capabilities are often concentrated in a handful of senior leaders who have developed them over decades of difficult conversations. According to Tolstoy, that creates fragility. If judgment and trust-building remain implicit, organizations risk leaving the next generation of leaders underprepared for the very decisions AI cannot make for them.

Developing this capacity takes more than a standalone workshop or a one-time conversation. Leaders need practice. Teams need shared language. Organizations need to prepare for the moments that matter: difficult questions, judgment calls, dissent, uncertainty, conflict and high-stakes alignment.

Tolstoy compares it to training a muscle. The work must be repeated, deliberate and connected to real business situations.

“Organizations realize that to be competitive, you need to sharpen the way humans interact with each other,” he explains. “Communication shapes how people think, feel and act, and ultimately how organizations perform.”

That is where the opportunity lies. AI will continue to improve. Analytical tools will become more powerful and more widely available. But the organizations that win will not be those that simply adopt AI fastest. They will be the ones who deliberately cultivate what AI cannot commoditize.

“The question isn’t whether to be more human,” Tolstoy says. “The question is whether you do it by design — or leave it to chance while your competitors figure it out first.”