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Winning with AI: Strategy Before Technology

In the race to adopt artificial intelligence, many leaders start with pilots, vendors, and products—only to stall at scale. My experience, reinforced by decades of research, suggests the reverse is true: technology delivers impact only when anchored in strategy.

AI StrategyDigital TransformationOrganizational AlignmentLeadershipBusiness Value
Winning with AI: Strategy Before Technology

Executive Summary

In the race to adopt artificial intelligence, many leaders start with pilots, vendors, and products—only to stall at scale. My experience, reinforced by decades of research, suggests the reverse is true: technology delivers impact only when anchored in strategy.

Evidence from MIT Sloan, Harvard Business Review, and decades of IT economics consistently shows that organizational alignment, clear business priorities, and leadership sponsorship explain success far more than any single algorithm or product choice. In other words, AI is not a strategy—it is a capability.

This article outlines why strategy should lead, how firms that start with business outcomes outperform those that start with tools, and what CEOs can do to ensure their AI programs scale.


The Argument: Technology is Not a Strategy

Leaders today feel immense pressure to “do AI.” Boards are asking, competitors are announcing, vendors are selling. But as Henderson & Venkatraman’s Strategic Alignment Model has long shown, value creation comes from alignment of business strategy, IT strategy, organization, and infrastructure—not from technology alone.

Economists Brynjolfsson and Hitt demonstrated this nearly 25 years ago: IT only improved productivity when paired with complementary investments in processes, incentives, and skills. The same principle applies even more strongly with AI.


Quote – Technology Alone is Never Enough

Technology alone is not enough. You need to convert it into changes in the way you run your business, and that starts with identifying what the opportunities are.

— Erik Brynjolfsson


AI Without Strategy: Why Most Pilots Fail

Recent research confirms the gap. MIT Sloan notes that an AI strategy must encompass business priorities, data strategy, and employee skills —otherwise pilots stall. A Harvard Business Review analysis found that only 8 percent of firms have the practices in place to scale AI; the majority get stuck because culture and operating model are not aligned.


Exhibit 2 – Enterprise Capabilities for Digital and AI Transformation (McKinsey)

McKinsey - Rewired to Outcompete
Source: McKinsey - Rewired to Outcompete

Digital transformation research: strategy comes first

A systematic review of transformation success factors (2024) concluded: clear strategy, top-management sponsorship, and alignment mechanisms consistently predict success. A recent Journal of Business Strategy article (2024) was even more explicit: “digital transformation: strategy comes first” .

What CEOs should do differently

In my work with executives, I use a simple checklist to ensure strategy leads: 

  1. Define business outcomes first (e.g., cost reduction, growth, resilience).
  2. Prioritize 5–7 AI use cases explicitly tied to those outcomes.
  3. Design the operating model—roles, governance, funding, incentives.
  4. Build the data and talent strategy to support it.
  5. Track metrics and iterate.

This flips the common pattern of “buy the product, hope it fits” into “shape the strategy, then invest with purpose.” 

Closing thought 

AI is powerful. But as the evidence shows, AI cannot substitute for strategy. The organizations that win are those that make AI serve their priorities—not the other way around.


References

  1. Bughin, J., Catlin, T., Hirt, M., & Willmott, P. (2020). Rewired to outcompete: Driving growth and efficiency in the digital age. McKinsey & Company.
  2. Henderson, J. & Venkatraman, N. (1993). Strategic Alignment Model.
  3. MIT Sloan Management Review (2024). Leading With AI: The Business Strategy Imperative.
  4. Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-Powered Organization. Harvard Business Review.
  5. Ghosh, R. et al. (2025). Critical success factors in digital transformation. Technological Forecasting & Social Change.
  6. World Scientific (2024). Digital Transformation Success Factors: A Systematic Literature Review.
  7. Brynjolfsson, E. & Hitt, L. (2000). Beyond the Productivity Paradox: Information Technology, Complementary Innovations, and Productivity.
  8. Bresnahan, T., Brynjolfsson, E., & Hitt, L. (2002). Information Technology, Workplace Organization, and the Demand for Skilled Labor.
  9. Journal of Business Strategy (2024). Digital Transformation: Strategy Comes First.
  10. Business Horizons (2024). Digital Transformation Canvas.

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