The Execution Chasm: Why AI Transformation Is an Operating System Problem

“The Execution Chasm,” a new piece from Council Advisors, featuring Handshake co-founder and CEO Garrett Lord, examines a gap many companies are facing: why their AI investments are not resulting in financial gains. The piece argues that AI transformation stalls when companies adopt AI without changing how they operate. In the Q&A, Lord explains why executives keep seeing minimal returns and what the companies getting real value from AI do differently. The piece describes SSA’s six pillar framework as a blueprint that can close this gap by combining strategy, operating-model design, and change management.

AI Adoption Is No Longer the Hurdle

Leaders still approach AI adoption the same way: buy the tool, train the users, and wait for results. That approach breaks down for four reasons:

• AI changes work one task at a time.
• Tools only work when people and machines keep feeding each other data.
• Every employee uses AI differently.
• A tool anyone can buy doesn’t give anyone a competitive advantage.

The result is a paradox: AI investment keeps rising, but returns don’t follow.

Learning Velocity as the Advantage

Learning velocity is how quickly a company spots a change, decides what to do, and acts. What slows it down is the Latency Gap: the time between seeing a problem and fixing it. AI can flag a supply chain problem in seconds, but if it takes three weeks of meetings to move inventory, that speed is wasted. The fix is to give the people closest to the work the authority to act on what AI surfaces.

Six Pillars of AI Operating Model Transformation

In our work at Council Advisors and SSA & Co., we use an integrated, end-to-end model that closes both the execution chasm and the latency gap by putting strategy, operating-model design, and change management under one team:

• Strategic Clarity: Define quantified outcomes tied to the P&L before any investment.
• Operating Model Design: Restructure workflows, roles, and decision rights around AI.
• Tech & Data Foundations: Rectify data quality to ensure models run on accurate institutional data.
• Talent & Change Enablement: Conduct role redesign and upskilling in parallel.
• Governance & Risk Frameworks: Establish oversight and guardrails from day one.
• Scale & Sustain: Implement stage-gating and Plan-Do-Check-Act (PDCA) cadences so the system keeps learning.

Frequently asked questions

Why isn’t AI investment paying off for most companies?

Most companies have adopted AI without changing how they operate, creating the execution chasm: the gap between investing in AI and seeing measurable returns. Companies spend on what is easy to buy, such as models and licenses, while the workflows, roles, and decision rights that determine results stay the same.

What are successful companies doing to get value from AI?

Companies that are seeing visible returns are treating AI as a tool to help change how the business runs. They put effort and investment into people and processes instead of additional technology. They view AI as a cyclical system that requires constant refining, measuring and improving.

How can companies close the execution chasm?

Closing the execution chasm requires combining strategy, operating-model design, and change management under one accountable team. The six-pillar model developed by SSA & Co. is a blueprint for closing this gap.