Optimization Framework for Enterprise-Level AI Adoption

• In 2024, 78% of companies reported using AI in at least one function, up from 55% in 2023.​

• Despite widespread adoption, only 1% of U.S. companies have successfully scaled AI across their organizations.​

• Over 80% of AI projects fail to move beyond the pilot phase, often due to issues like poor data quality and lack of strategic alignment.
  
• Companies that strategically invest in high-priority AI opportunities tend to scale more effectively and achieve higher ROI.

To move forward, organizations need more than AI as a technology. They need a governance framework to choose the right AI initiatives with the greatest impact, strongest readiness, and clearest path to value.

Are you investing in AI or just deploying it?

Enterprise AI is no longer a question of capability. It’s more about clarity.

The Strategic AI Optimization Framework introduces a rigorous yet flexible approach to AI decision-making that factors in time-to-value, budget constraints, data readiness, and strategic alignment.

Why should you read this?

• You want AI decisions to feel as accurate as any other capital allocation process.

• You are leading or supporting AI initiatives and need a clearer way to prioritize them.

• You are working with a fixed budget or timeline, and can’t afford waste.

• You are tired of scattered pilots and are ready for a unified, measurable strategy.