Why AI Strategy Lives at CEO Level, Not in Operations
Dec 16 2025
By Bob Howland, Chairperson, MACH Alliance
There is an incredible amount of pressure right now for CIOs and CEOs to answer one question: what is your organization doing with AI?
What is not a great answer: "well, I have this great vendor and they put AI in their products." That's not a great answer. It's not even close.
This isn't an operations question anymore. This is about strategy. And it's being asked at the board level whether you're ready for it or not.
Why this question keeps moving up
CIOs are being hired and fired based on how they answer the AI question. And increasingly, that question is rotating up the flagpole to CEOs who, frankly, are ill-equipped to answer it as well. What makes this different from previous technology shifts is the breadth of the question. It's not just about digital commerce. Boards are asking what finance is doing with AI. What supply chain is doing. Customer service. Data. Every function is being asked to account for AI strategy. That's why individual operational answers don't satisfy board-level questions - the board is looking at the whole enterprise, not one department.
AI isn't a technology initiative. It's a business strategy question that touches every function. That's why it keeps moving up the org chart.
The complexity even creates the reality of enterprises standing still, or keeping the head in the sand. And both is a recipe for falling behind. I am not saying enterprises should rush, on the contrary, but they should definitely move at a strong pace.
The framework for strategic AI decisions
So what does a CEO-level AI answer actually look like? I'll pose four questions that separate strategic AI thinking from tactical feature-chasing.
First: What business solution is your tech solving for?
Not "what can AI do" - that's the wrong starting point. The question is what problem you're solving for the business. Business outcome first, technology second. Always.
Second: Where does this solution fall in their overall enterprise priority?
Your AI initiative doesn't exist in isolation. It competes with what I call the "data spaghetti mess" and dozens of other priorities. That e-commerce manager who needs to spend more money because their vendor built AI into the platform and raised the price? That funding decision lives in the context of every other funding decision the organization is making. And the people approving those decisions are under pressure to showcase an enterprise AI strategy - not a collection of individual tools.
Third: What triggers the business problem now?
Timing matters. What's changed that makes this urgent? What's the trigger that moves this from "nice to have" to "strategic priority"? If you can't answer that, you're not ready to make the case.
Fourth: Are you working with your customer to build an implementation plan that includes testing and measurement?
Not just deployment - measurement. Not just shipping features - building with the customer. This is where strategy meets execution.
Those in the technology community who can truly answer these questions on a customer-by-customer basis will be those who win.
The cost of tactical thinking
When AI lives in operations instead of strategy, you get a predictable pattern. Individual teams make individual tool decisions. The e-commerce team upgrades to the AI-enabled version of their platform. Marketing adds an AI feature. Customer service deploys a chatbot. Each decision makes sense in isolation.
But none of it adds up to an enterprise AI strategy. The board keeps asking what you're doing with AI, and you keep presenting a list of features instead of a strategy.
Get the strategic frame right, and the opposite happens. Investments compound because they're aligned. Tools integrate because architecture decisions support integration. Capabilities connect to business outcomes because that's how they were selected in the first place.
What the research confirms
MIT has a research arm called the Center for Information Systems Research - CISR. They recently released a framework based on a longitudinal study they've been running for about 15 years. The question they've been asking: how are the most successful businesses succeeding against their peer group?
They have shown statistically that composability - a composable mindset and being designed digital-first - is a market leader indicator. Companies that embrace these principles outperform their peers.
Now they've released a new framework for what that looks like in the advent of AI. And here's the newsflash: we're going back to the future.
Business outcomes? Much more important than they've ever been. Knowing your customer? Much more important than it's ever been. Strategic business execution? Much more important than it's ever been.
The fundamentals haven't changed. AI has raised the stakes on getting them right.
This is what composable architecture enables - the flexibility to make strategic AI decisions without being locked into single-vendor roadmaps. When AI lives at CEO level, architecture decisions become business strategy decisions. You need the freedom to integrate, adapt, and evolve as the technology landscape shifts.
The question isn't going away
The pressure on CEOs and CIOs to answer the AI question isn't temporary. This is the new normal for enterprise leadership. Every board meeting, every investor call, every strategic planning session - the question will be there.
The organizations that win don't per se have a long list of AI features or vendors to show for. They'll be the ones who can answer that question with a strategy.
The board wants to know, investors need to know. Make sure you have an answer that actually answers the question.
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