AI has changed what is possible in strategic planning.

However, there is still an open question as to whether a strategy actually gets executed.

Across industries, organisations are investing heavily in AI-enabled planning, analytics, and forecasting tools. Yet outcomes remain stubbornly inconsistent. Strategies look sophisticated in PowerPoint decks and pilots launch with enthusiasm, but real business value often fails to materialise.

The problem is rarely the technology.

It is almost always governance.

 

Why AI makes strategic planning harder, not easier

AI dramatically expands the range of options leaders can consider.

More scenarios.
More data.
More potential interventions.

This creates the illusion that better planning will naturally lead to better execution. In practice, the opposite often happens.

For years, strategy execution failure has hovered around 55-80% (a wide range of sources including McKinsey, Harvard Business Review and many consulting firms). Recent research hones in on AI implementation, and the failure rates are even worse.

MIT’s GenAI Divide research found that around 95% of corporate AI initiatives fail to produce measurable business value (MIT NANDA, 2025). McKinsey reports similar patterns, with most organisations struggling to move beyond pilots into scaled, enterprise-wide impact (“The State of AI”, McKinsey 2025).

The failure point is not ambition or intelligence. It is the absence of clear decision rights, accountability, and participation structures early in the strategic planning process.

 

Strategic planning without governance is just speculation

Governance is often misunderstood.

Some leaders hear “governance” and think bureaucracy.
Others assume it belongs later, during delivery.

In reality, governance is the operating system of strategy execution. It defines:
• Who shapes decisions
• Who makes final calls
• How information flows
• How conflict is resolved
• How learning feeds back into the plan

In AI-enabled strategy, these questions become more important, not less.

McKinsey has found that organisations where CEOs and boards are actively involved in AI governance significantly outperform peers on financial outcomes, compared to those that delegate AI oversight too far down the organisation (McKinsey Global Institute, 2024).

This is not micromanagement. It is clarity.

 

Why early stakeholder involvement changes execution outcomes

One of the most expensive mistakes in strategic planning is narrowing engagement too early.

Plans are often developed by a small group of senior leaders and specialists, then communicated downstream. This feels efficient, but it creates blind spots that surface later as resistance, rework, or stalled execution.

Research behind the Iceberg of Ignorance shows that executives are typically aware of only around 4% of frontline operational problems, while employees closer to the work understand the vast majority of issues (Iceberg research study originally published by Yoshida, 1989).

AI has widened this gap, not closed it.

McKinsey’s Superagency research found that employees are already experimenting with generative AI at three times the rate leaders believe, creating a growing disconnect between strategy intent and operational reality (McKinsey, 2024).

Strategic planning that ignores this reality plans in the dark.

 

Planning for orchestration, not prediction

AI exposes a flaw in traditional planning assumptions.

The goal is no longer to predict the future accurately.
The goal is to orchestrate learning and adaptation effectively.

Ethan Mollick describes this shift as moving from “command” to “orchestration”, where leaders design systems that combine human judgement and AI capability rather than trying to control every outcome (Harvard Business Review, 2024).

In practical terms, this means strategic planning must:
• Involve people who do the work early
• Surface cultural and operational constraints upfront
• Define how learning will update decisions over time

Governance structures such as cross-functional working groups make this possible. They are not consultation forums. They are decision-shaping mechanisms that continue throughout execution.

 

Culture intelligence belongs in the planning phase

When I’ve looked at reasons for strategy failure across different organizations, most are due to culture issues. These are typically tied closely to poor program governance.

Poor governance happens when the people across the organization are not appropriately involved in developing the strategies, and not consulted early enough (or at all).

Culture is not something to address after approval. It is data that should shape planning itself.

Gartner research has shown that change initiatives using participative, open strategy approaches reduce change fatigue by up to 29%, and employees’ willingness to change is almost 50% higher (Gartner, 2023).

A culture-intelligent planning approach:
• Tests strategic assumptions against how work really happens
• Designs decision rhythms that fit the organisation
• Adapts communication and change approaches early

This reduces the need to push strategy later. People recognise themselves in the plan and pull it forward.

 

From elegant plans to executable strategies

AI-enabled planning creates value only when it is anchored in governance, participation, and culture intelligence.

Organisations that execute well consistently:
• Establish governance before finalising plans
• Involve a broader range of stakeholders early
• Use AI to surface reality, not avoid it
• Design for adaptation rather than certainty

Strategic planning does not rely on producing the perfect answer. It is about creating the conditions where execution can succeed. This means involvement of staff early in an open strategy process. And AI makes this even easier to do this.

PS More Ways to Accelerate your Strategy

Looking to move your strategy forward? Lisa Carlin works with selected clients directly to go from strategy to plan to result. Email Lisa.

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