CIOs: AI’s Presence Means We Must Test Strategic Moves Before Executing Them

For decades, companies could afford the gap between strategy and execution. AI has erased that buffer. Matt Keane, a data and AI executive, explains why organizations must test strategy at prototype speed and how executives can eliminate the structural misalignment that slows learning and surrenders advantage.

Early in my IT career, strategy felt like a black box. Somewhere, decisions were made about where the business was headed. Eventually those decisions reached delivery teams like mine, translated into projects, milestones, and success metrics. We built what we were asked to build. We met our objectives. Performance reviews were positive.

And yet, at the end of the cycle, the organization often hadn’t achieved what it hoped to achieve.

That gap between successful delivery and unmet strategic outcomes was not accidental then, and it’s not now. It is the hidden cost organizations pay when thinking and doing operate on different timelines. I call it the alignment tax. For decades, every company paid this tax. Today, artificial intelligence is turning this gap, and its associated costs, into an existential risk that calls for correction action. The question for leaders is no longer whether the alignment tax exists, but how quickly they can eliminate it and what must change inside their organizations to do so.

Defining the alignment tax

The alignment tax is the compounded cost of executing at governance speed while the environment demands learning speed.

Organizations plan annually or in multi-year cycles. They rely on approval gates, risk reviews, and oversight structures designed to ensure control and accountability. This is what executing at governance speed looks like. Meanwhile, markets shift continuously, customer expectations evolve, and competitors experiment in real time.

The alignment tax hides what appears as success. Dashboards stay green. Milestones are met. Budgets are respected. But value fails to materialize because learning about customer demand, pricing sensitivity, feature adoption, and competitive response arrives too late to influence strategic decisions. Delivery succeeds. Strategy misses. The difference is the tax.

Historically, this misalignment was survivable. The pace of change allowed lagging organizations to catch up. Today, that buffer is collapsing.

How the tax accumulates

The alignment tax rarely appears as a failure. It often emerges through initiatives that succeed technically but fail behaviorally. Consider a company entering a new market segment with a three-year growth target. The strategy is sound on paper, and execution teams respond by launching targeted marketing programs, adjusting pricing, developing product features, and expanding distribution partnerships aligned to that plan.

Within months, market signals begin to shift: customer acquisition costs climb, competitors reposition, and demand patterns diverge from original projections. Yet in traditional operating models, execution teams remain aligned to the initial plan, retrofitting new information into existing assumptions and making tactical adjustments rather than reconsidering the strategy itself. The initiative succeeds operationally but the strategy underperforms. Nothing appears broken. The failure lies in IT operating models that separate strategic intent from software development and delivery.

It shows up as paralysis — teams grinding through backlog features, chasing data quality flags, closing out bug tickets, staying busy without being productive. Not because the work is wrong, but because decision lag has grown so wide that nobody can draw a straight line between what they're building and what actually matters. When that line disappears, teams stop making judgment calls. They just deliver.

I've watched this play out from inside planning cycles that should have caught it. You leave a meeting knowing — everyone in that room knows — that two sprints and a live test would answer the question the whole quarter is betting on. Instead you hear: we have our marching orders, let's execute. And so the teams execute. Sprint by sprint, the gap between the plan and the signal widens, quietly, predictably, avoidably. By the time the miss is undeniable, the quarter is gone and the retrospective is already framing it as an execution problem.

The pattern compounds when organizations have cycled through enough vendors, integrations, and reorganizations that institutional memory erodes entirely. Teams lose not just alignment — they lose the meaning of the work itself. Each handoff strips another layer of context until the people closest to delivery can no longer articulate why they're building what they're building, or for whom.

Nothing appears broken. Sprints close. Demos happen. Roadmaps update. The failure lives in the widening space between strategic intent and the team's moving code — a gap so normalized it no longer registers as a problem worth naming, let alone solving.

Why AI makes this existential

Before AI, delayed learning was costly but manageable because competitors moved at roughly the same speed. Organizations could absorb missteps, conduct post-mortems, and recalibrate during the next annual planning cycle without permanently surrendering advantage. Today, AI is collapsing the distance between strategy and market feedback. Organizations can test strategic assumptions at prototype speed, deploying limited market releases in weeks, gathering real-time adoption and pricing data, and refining features before scaling. AI amplifies software development and product experimentation capacity, accelerating iteration cycles and allowing small teams to deliver and learn at a pace once possible only for much larger organizations.

The result is a compressed feedback loop. Competitive advantage is no longer defined by who has the most sophisticated technology stack, but by who learns and adapts fastest. Learning curves, not feature catalogs, now determine separation. And learning cannot be accelerated on demand.

Companies that shorten their learning loops will pull away from those operating at governance speed. The gap will widen faster than slower organizations can close it.

The move to testing strategy before execution

When results lag, leadership teams often diagnose execution failure. This preserves the legitimacy of the strategy while placing accountability on delivery. The response is predictable: tighten oversight, add checkpoints, reinforce accountability, and increase reporting cadence. Each step feels prudent. Each step slows learning further.

The deeper issue is structural misalignment: delivery teams often detect early signals that strategic assumptions may be flawed, yet those insights are reframed as execution risks rather than strategic ones. Product managers absorb the friction into timelines and scope adjustments instead of elevating the issue for executive reconsideration. This allows strategy to harden even as learning is constrained and the alignment tax continues to compound.

One of the most significant shifts organizations must make is moving from executing strategy at governance speed to executing strategy at prototype speed. This requires collapsing the distance between ideation and delivery. Strategy should not be handed off for execution; it should be tested as it is formed.

Imagine strategy sessions where architects and developers prototype concepts in real time, modeling feasibility, customer response, and operational implications as decisions are made. This is not about replacing governance; it is about embedding learning into it. When strategy is informed by immediate feedback, organizations reduce the cost of wrong decisions and accelerate the value of right ones.

Actionable steps to reduce the alignment tax

Leaders can begin reducing alignment tax immediately.

Audit your learning latency.
Measure how long it takes for market feedback, delivery retrospectives, and operational insights to reach decision makers. If delivery teams detect strategic friction, ensure those insights reach executives, not just product managers.

Start with decisions, not platforms.
Technology investments often precede clarity about the decisions they must support. Instead, identify critical decisions that must be made faster or with greater confidence, and design learning loops to support them.

Redesign governance as part of delivery.
Governance should not function as a stage gate. It should be embedded in the delivery cycle, enabling rapid experimentation within guardrails rather than delaying action until certainty is achieved.

Make strategy malleable.
Strategies must be responsive to evidence. When feedback challenges assumptions, adaptation should be viewed as discipline, not failure.

A competitive inflection point

Industries burdened by legacy systems and slow change management, including financial services and insurance, face particular urgency. In saturated markets where product differentiation is narrow, the ability to deliver features customers want, at the price and speed they expect, will determine market share.

Organizations that close the gap between strategy and execution while leveraging AI to amplify human capability will gain measurable advantage. Those that do not will find themselves learning too slowly to compete. The alignment tax has always existed. For the first time, it is optional. Companies that eliminate it will redefine the pace at which they compete.