The AI Executive Brief: November 2025

Why 88% of organizations use AI but only 6% see real business impact

Three years into the generative AI era, a paradox has emerged.

Nearly nine out of ten organizations now use AI regularly. Yet only a tiny fraction—about 6%—report meaningful bottom-line impact.

The data reveals something counterintuitive: the bottleneck isn’t AI capability. It’s organizational ambition and transformation courage.

The Numbers That Matter

McKinsey’s November 2025 Global Survey on AI (1,993 respondents, 105 countries) reveals a stark divide:

of organizations now use AI in at least one function

are “high performers” seeing 5%+ EBIT impact

remain stuck in pilot purgatory

Only 39% of respondents attribute any EBIT impact to AI. The gap between “using AI” and “benefiting from AI” has never been starker.

Pilot Purgatory: Why 62% Are Stuck

The pattern is predictable:

• Month 1: Excitement. “We’re piloting AI!” Demos look promising.
• Month 3: Complexity reality. Edge cases emerge. Integration harder than expected.
• Month 6: Expansion stall. “Let’s evaluate before expanding.” (Code for: it’s stuck.)
• Month 12: Quiet cancellation. Pilot still running with 10 users. No production roadmap.

“While 70% of enterprises succeed with pilots, integration with legacy infrastructure, poor cross-functional collaboration, and governance gaps prevent 80% from reaching production.”

— AIM Research Council

What the 6% Do Differently

McKinsey’s “AI high performers” share four patterns:

1. They Pursue Transformation, Not Just Efficiency

High performers are 3.6x more likely to pursue transformative change—not just cost cutting.

The efficiency-only approach is the default. High performers layer on growth and innovation. They’re not trying to do the same things cheaper—they’re trying to do different things entirely.

2. They Redesign Workflows, Not Just Tasks

High performers are 2.8x more likely to have fundamentally redesigned workflows.

“This intentional redesigning of workflows has one of the strongest contributions to achieving meaningful business impact of all the factors tested.”

— McKinsey Global Survey, November 2025

Most organizations bolt AI onto existing processes. High performers ask: “If we started today with AI, what would this process look like?”

“You can’t automate your way to transformation. You have to rethink the work itself. It’s the process redesign—not the technology—that creates most of the value.”

— Bain & Company

3. Senior Leaders Own It Personally

High performers are 3x more likely to have senior leaders demonstrating personal ownership—not just sponsorship.

Why? Because transformation breaks organizational boxes. Budget reallocations. Process changes across teams. Cultural shifts.

Pilots fit in boxes. Transformation breaks them. Only the CEO can break boxes.

4. They Invest Meaningfully in Change Management

Organizations investing properly in change management are 1.6x more likely to exceed expectations.

What “meaningful” looks like:

• 20-25% of project budget (not squeezed from contingency)
• T-60 days before launch through T+90 days after
• Dedicated roles, not “someone’s side project”
• Compensation adjustments when AI changes productivity expectations

87% of organizations that skip change management face more severe people challenges than technical ones. The algorithm works. The humans refuse to use it.

The AI-Native Benchmark

While incumbents struggle, AI-native companies show what’s possible:

Cursor: $1M to $100M ARR in 12 months. $3.3M ARR per employee. (Salesforce: ~$800K.)

Lovable: Fastest ever to $100M ARR—8 months. 45 employees. $2.2M revenue per employee.

Gamma: $100M ARR profitably with 70 million users.

These aren’t outliers. They’re previews of what happens when AI is embedded from day one rather than bolted on afterward.

The Three-Lens Problem

Why do 95% of AI initiatives fail to deliver value? Organizations evaluate success through three incompatible lenses:

1. CEO Lens: Competitive advantage, market share, productivity gains
2. HR Lens: Staff adoption, fair expectations, positive role evolution
3. Finance Lens: Proven ROI with data, baseline comparisons

The tragedy: 75% of AI projects can’t prove ROI because no baseline was established before launch.

The High Performer Playbook

Based on the patterns distinguishing the 6%:

1. Set transformation objectives—not just efficiency goals. Pursue growth and innovation alongside cost reduction.
2. Redesign workflows from first principles. Ask: “If we started today with AI, what would this look like?”
3. Secure CEO ownership. Visible, active engagement—not delegation to committees.
4. Invest 20-25% in change management. Update compensation when AI changes productivity expectations.
5. Measure outcomes, not activity. Revenue affected, cost reduced—not tools deployed or adoption rates.

The Bottom Line

AI adoption is no longer the differentiator—88% have crossed that threshold.

The new divide is between organizations that treat AI as a tool to bolt onto existing processes and those willing to fundamentally transform how work gets done.

The question for every executive isn’t “Are we using AI?”

It’s “Are we using AI to do the same things faster—or to do fundamentally different things?”

The bottleneck isn’t AI capability.

It’s organizational ambition and transformation courage.

Sources: McKinsey Global Survey on AI (November 2025), McKinsey “The AI-Centric Imperative,” Bain, Deloitte, BCG research.