Most Companies Don't Have an AI Problem. They Have a Leadership Problem.

Almost every leadership team I talk with is asking some version of the same question: why isn't our AI investment showing up in the numbers?

They are not alone. McKinsey's latest State of AI research finds that 88% of organizations now use AI in at least one business function, yet only 37% can attribute any impact on earnings before interest and taxes (EBIT) to it, a share that has barely moved in a year. Only about 6% qualify as true high performers.

Boston Consulting Group (BCG) sees the same gap from another angle. In its 2026 Applied AI Index, nearly half of companies now generate some value from AI, but only 7.5% are what BCG calls "future-built." BCG's rule of thumb says it plainly: success is 10% algorithms, 20% technology and data, and 70% people, organization and processes.

Seventy percent. The tools are not the bottleneck. Leadership is.

Where AI exposes leadership

AI is a stress test. It takes whatever was already true about how a company makes decisions, rewards people and runs its processes, and it makes that truth visible faster. In my work with revenue and operating teams, the same five gaps show up again and again.

1. Unclear decision rights. AI can cut a week of analysis to an afternoon. If nobody clearly owns the decision, that speed just produces more meetings and more opinions.
2. Incentives that reward activity, not outcomes. Harvard Business Review reported in October that AI gives a disproportionate lift to the people and teams who reinvest the time it saves into understanding customers and sharpening strategy. If your compensation plan rewards volume, the time AI saves becomes more volume.
3. Processes nobody designed. Many workflows grew up around workarounds and handoffs. Automating a broken process doesn't fix it. It makes the breakage faster and harder to see.
4. Value nobody owns. BCG found that companies tracking AI value directly on the profit and loss statement realize about three times as much value as companies that don't formally measure it (3.6% versus 1.2%). Measurement is a leadership choice, not a technical one.
5. Controls that lag autonomy. In the same BCG study, 42% of companies expect AI agents to act autonomously by 2030, yet only 5% have the full set of critical controls in place today. Giving systems more autonomy than your governance can support is a leadership risk, not an IT risk.

Go-to-market is where the gap shows first

The revenue engine is usually the first place these gaps hurt. Forrester's 2027 business-to-business (B2B) predictions, released in October 2026, say two-thirds of providers will lose deals because buyers can't verify their claims, and buyers will double their human interactions to check what their own AI tools recommend.

In other words, AI is raising the bar for trust. The companies that win will not be the ones with the most agents. They will be the ones whose leaders decided what to automate, what to augment and what must stay human, and then built the team, the incentives and the operating rhythm to match.

Stop chasing an "AI-ready culture"

Harvard Business Review made a sharp point in October: there is no such thing as an AI-ready culture. Most organizations are built to perform reliably today, not to keep transforming, and the traits transformation needs (speed, agility and a bias for action) are among the rarest. A companion HBR piece describes the mindset shifts leaders need as AI speeds everything up: from certainty to clarity, from expertise to exploration, and from emotional control to emotional insight.

That matches what I see. The leaders who get value from AI are not the most technical people in the room. They are the ones willing to redesign how work gets done, and to say out loud what is changing and why.

Five questions for your next leadership meeting

1. Who owns each AI-assisted decision, and how quickly can they make it?
2. What will we stop doing with the time AI saves?
3. Do our incentives reward outcomes or activity?
4. Is AI value measured on the profit and loss statement, with a named owner?
5. Are our controls keeping pace with the autonomy we are giving AI agents?

If those questions are hard to answer, that's the real work. Not another pilot. Not another tool.

The pattern repeats

Over 20+ years building commercial teams at Google Cloud, Amazon Web Services (AWS), Microsoft, LinkedIn and Dropbox, I've watched every major shift (cloud, subscription and now AI) reward the same thing: leaders who redesigned how their organizations work, not just which tools they used.

AI is the biggest version of that test yet. The good news is that leadership gaps are fixable, and fixing them pays off faster than any new platform.

If your team is investing in AI but not yet seeing it in revenue, I'd welcome the conversation. At BC Global Partners, we work alongside leadership teams, from high-growth companies to global enterprises, to turn go-to-market strategy into revenue growth.