Why AI Isn’t Strategy — And Why That’s Good News

By: Marc Sanderson

 

Artificial intelligence is not radioactive. And it is not a miracle cure.

 

It is a tool.

 

That distinction matters. Because the companies that win in the next decade will not be those that “adopt AI.” They will be those that integrate it into a coherent strategy that improves economics, strengthens differentiation, and deepens customer value.

 

Today, AI sits squarely on the CEO desk. When the terrain shifts significantly, many leaders default to old playbooks of expense reductions and operational excellence. That is not strategy. Doing nothing is worse. Many executive teams fixate on compliance, model accuracy, feature velocity and competitive signaling. The game has changed — and winning requires quickly redefining what it means for your strategy.

 

The key question to ask is: What problem are we solving — and how does AI strengthen our integrated set of activities?

 

AI does not create advantage by existing. It creates advantage when it reinforces how you compete.

 

The Three-Part Equation

Organizations that will leverage AI effectively will lead with strategy, then deploy AI where it strengthens their differentiated system — not where it simply looks innovative. That requires focusing on creating real value.

 

Real value follows a very simple formula: Value Desired × Value Created × Value Captured.

 

If any one of those is zero, the outcome is zero:

• Value desired defines the problem — and focuses on the customer.
• Value created is the solution — and requires listening to the voice of customer.
• Value captured is how you monetize it.

Miss one, and the initiative becomes a science project rather than a business strategy.

 

Start Where It Matters — The Customer

 

Many organizations jump straight to value created — the model, the tool, the feature. They rarely pause to rigorously define value desired.

 

One CEO recently described his AI roadmap as “aggressive.” When asked what specific customer problem it solved, the room went quiet. That silence is common. Activity has replaced clarity.

 

AI initiatives that start with novelty instead of need quickly become internal experiments disconnected from measurable impact.

 

Getting the formula to work requires connecting with customers and asking key questions:

• Where are customers losing margin?
• What are mission-critical workflows?
• Where does uncertainty create cost?

One company rolled out generative avatars in meetings. Customers were unimpressed. What they actually wanted was better estimating accuracy, increased engineering productivity, fewer production surprises, and clearer project visibility.

 

The difference is strategic discipline.

 

The lesson: The tool matters. But the integrated system matters more.

 

Clean Data Creates Clear Advantage

AI is unforgiving and exposes weaknesses in data immediately.

 

A leadership team recently blamed inconsistent forecasting results on the AI model. The real issue? Years of incomplete and inconsistently coded job-cost data.

 

AI performance acts as a mirror. It reflects the quality of an organization’s underlying systems. In the AI era, data governance is not an IT hygiene issue. It is a strategic infrastructure. Electricity required factories to be rewired. AI requires data to be standardized, structured, and stewarded — constantly.

 

Layering AI on top of messy systems produces disappointing results. Leaders then misdiagnose the problem as technological when it is architectural. If data is fragmented, AI will amplify fragmentation. If data is disciplined, AI will amplify precision.

 

The lesson: The output is only as good as the input.

 

Redefine the Workflow

 

AI’s real impact is structural, not cosmetic. Traditional enterprise systems are systems of record — capturing data. AI enables systems of intelligence — platforms that interpret, predict, and recommend in real time.

 

That means:

• Predictive alerts instead of reactive reporting
• Scenario simulation instead of static dashboards
• Embedded decision support instead of manual analysis

This shift is not about flashy features. It requires redesigning workflows around decision velocity and customer insights.

 

History is instructive. Gunpowder made castle walls irrelevant. Electricity did not improve candle factories — it forced factory redesign. The internet redefined distribution models.

 

AI belongs in that lineage.

 

The lesson: AI’s advantage is systemic, not incremental.

 

The Moat Moves

Horizontal AI may be widely available. Vertical intelligence is not. In many industries, adoption is becoming bimodal. Some firms hesitate. Others integrate deliberately and accelerate. The gap widens. Winners shorten the distance between strategy and execution.

 

Speed matters — but only after strategic alignment.

While moments like this feel unprecedented, they rarely are. When the printing press arrived, knowledge was no longer scarce. Institutions that adapted scaled influence. Those that resisted lost relevance.

 

Winners are those who redesign their activity system around AI — not just bolt it on.

 

The constraint on AI adoption is rarely model capability. The AI models are ready. The question is if we are willing to change how we work. In an AI-accelerated world, slow organizational change is a strategic risk. Leaders transform companies.

 

It is hard to run fast on sand. Winners provide leadership clarity:

• Anchor AI in real customer value.
• Strengthen data as infrastructure.
• Embed AI into the organization’s integrated set of activities.
• Redesign workflows to improve decision economics.
• Ensure value is captured, not just created.

No company is too custom. But only disciplined companies will convert AI from experimentation into sustained competitive advantage.

 

 

Marc Sanderson is the CEO of INNERGY and former President/Owner of Wilkie Sanderson. He began in the millwork industry 20 years ago with a small cabinet shop and built it into one of the most profitable operations in the country. A Harvard MBA and 2024 Wood Industry Market Leader, Marc is known for transforming complexity into clarity through data-driven strategy and culture first leadership. Equal parts analytical operator and motivator, he’s just as comfortable refining strategy as he is rallying a room around a shared vision.