Your AI advantage isn't speed -- it's judgment

Taking a different approach

I learned this not from a whitepaper but from a negotiation that was going sideways. We were locked in a high-stakes commercial dispute where the other side's behavior was confusing. Their positions seemed irrational, their strategy incoherent. We were deep in the weeds and locked into our own framework, seeing their moves through the lens of what we would do, not what they were doing.

The real advantage isn't acceleration. It's judgment.

So, we tried something different. We fed an AI tool the commercial background, the industry context, the business documents and our own strategic assessment of both sides. Basically, a brain dump of everything we knew and everything we thought.

What came back wasn't magic. But it surfaced a pattern in the other side's behavior that we had missed entirely -- a coherent strategy that was only visible when we stepped outside the position we'd been arguing from for weeks. It was like having a seasoned advisor who could see the negotiation from the other side of the table.

In another case, we needed to persuade a policymaker with a distinctive worldview. AI helped us reframe our argument to align with not just his stated priorities, but his style of thinking -- the way he reasoned about problems, the language he used and the policy aspirations that animated his decisions.

We weren't changing our position. We were translating it into his cognitive framework. The approach works for any third-party decision-maker whose perspective you need to inhabit: regulators, judges, activist investors, counterparties or key customers.

Neither of these outcomes had anything to do with going faster. They were about seeing things differently.

The efficiency trap

There's a deeper confusion underneath the obsession with speed. Most organizations equate efficiency with acceleration. But true efficiency isn't about doing things faster; it's about thinking more rigorously.

Judgment is the scarce resource that turns analysis into action.

The scientific method isn't quick. It's efficient because every failed hypothesis narrows the field and sharpens what remains. Even "move fast and break things," before it became a cliché about velocity, was really about breaking bad ideas before the market breaks them for you.

That's what strategic AI does. It eliminates wrong answers, narrows the field and creates a path to better answers and more strategically valuable outcomes. These include solutions such as a negotiating position you hadn't considered, a contractual framework that creates leverage where none was visible, a litigation theory that reframes the dispute on your terms or a compliance approach that turns a regulatory constraint into an operational advantage. Businesses achieve these outcomes by using AI to think more deeply, more rigorously and with more strategic imagination than speed-obsessed organizations.

The cases are out there. Coca-Cola used AI to mine millions of social media posts for emerging flavor trends -- not to process orders faster but to reshape its product portfolio. Retailers are using machine learning pricing engines not to cut costs but to reposition themselves competitively in real time.

Research published in the Journal of Financial Economics found that companies investing in AI have higher sales growth and market valuation, driven not by operational efficiency but by increased product innovation. McKinsey & Co. research suggested that organizations using AI in strategic planning report 15% to 20% revenue lift over peers. But these examples are buried under an efficiency myopia that races past them toward the quicker solution. The strategic use of AI is underreported -- and chronically undervalued.

When organizations use AI to process contracts faster or shorten research cycles, they're using it as an appliance -- a valuable but routine, administrative tool. The contract gets done. The memo gets drafted. That's AI as a dishwasher: It performs the task you were already going to do, with less effort.

When organizations use AI to refute assumptions, stress-test strategies and discard bad paths before committing resources, they're using it as a strategic instrument. That's where efficiency actually equals strategy -- not because it's faster but because it's more rigorous.

The real competitive advantage is judgment. Not some ephemeral Olympian wisdom, but the ability to make better decisions when the data is contradictory, when frameworks don't agree, when pressure distorts perspective and when logic alone doesn't tell you what to do next.

Judgment is the scarce resource that turns analysis into action. AI can't automate it. But it can sharpen it if organizations use it as a strategic asset to challenge assumptions, test theories, reveal blind spots, develop new insights and inhabit perspectives the room can't naturally access.

AI for judgment and strategy

Beyond the tactical realm of speed, AI expands the strategic field of vision. It becomes a laboratory for testing assumptions with analytical rigor, refuting ideas and refining what emerges.

When we become obsessed with AI's capacity for speed, we eliminate the very arena in which judgment is produced.

This approach is particularly powerful in negotiations with asymmetric leverage. Dominant players tend to dig into terrain they know and control. They're used to dictating terms, not thinking differently. But when you're the challenger or a dominant player in a shifting market, success comes from reframing the problem, not pressing harder on the existing one.

Clayton Christensen's Innovator's Dilemma showed why dominant firms struggle to question their own success. It happens not because they lack data, but because they're overfit to their own success metrics. AI can expose that blind spot, helping organizations challenge the assumptions that feel most solid and convert disadvantage into strategic advantage. Asymmetric competition isn't about speed. It's about seeing what others miss.

The deeper irony is that when we become obsessed with AI's capacity for speed, we eliminate the very arena in which we can produce judgment. In a corporate culture of "this meeting could have been an email," we're dismissing the space where judgment forms. The debate that seems to slow things down actually illuminates the detour in the right direction. The seemingly random question ends up challenging a premise or reframing an issue.

In a quest to eliminate friction, we're creating a world where efficiency means using AI to write an email that the recipient uses AI to summarize, and we're racing to remove the very things that produce judgment, strategy and innovation.

What leaders should do differently

The distinction shows up in practice. Processing contracts faster is tactical. Asking "What assumption in our negotiating position is most vulnerable?" is strategic. The shift requires concrete changes in how organizations use AI -- not just what they use it for.

• Red team your own thinking. Before finalizing a strategy, a negotiation position or a regulatory approach, use AI to generate the strongest possible arguments against it. What would the other side say? What patterns in their behavior are you missing? What assumptions are you treating as settled that are actually fragile? The goal of this red-teaming approach isn't to undermine confidence, it's to earn it. This approach institutionalizes dissent. AI just makes it scalable.
• War-game outcomes. Use AI to play out scenarios: If we take this position, what are the three most likely responses? If the regulator pushes back on this point, what's our fallback? If the other side's behavior follows the pattern AI identified, where does that lead in six months? This replaces forecasting with strategic rehearsal.
• Bring AI to the table. When the CEO asks "What does Finance think? What's Legal's take?" strategic organizations will add "What does AI say, and what was the prompt?" This approach uses AI to get cognitive diversity -- a voice that can challenge groupthink and provide adversarial perspectives. It helps surface what the room can't naturally see.
• Look for blind spots. Ask "What are we missing?" before leaping to "How do we automate this?" The first question produces a strategy. The second produces efficiency. Both matter. But the order determines which one drives the organization.

The coming divide

The coming divide isn't between AI adopters and holdouts; that gap effectively closed in 2025. The divide is now between organizations that use AI to go faster and those that use it to think better. The first will optimize. The second will win.

The optimizers will find that an obsession with speed often leads to bad outcomes -- just faster. And the winners won't be the ones who move quickest. They'll be the ones who see the whole track differently.

Eric Dodson Greenberg is executive vice president, general counsel and corporate secretary of Cox Media Group, an Apollo Global Management portfolio company. Before CMG, he was a highly ranked private practice partner, recognized by Chambers USA and inducted into the Legal 500 Hall of Fame.