Why do AI investments fail to show up in company financial results?

Most organizations treat AI as a technology rollout rather than an operating-model change, so pilots stall after proving a concept instead of scaling. The barrier is organizational, not technical — use cases built in one business unit rarely transfer to another without a mechanism designed to carry them across.

What percentage of companies struggle with cross-team collaboration on AI?

ADAPTOVATE's Agile Diagnostic found 63% of organizations identified poor cross-team collaboration as their single biggest constraint on speed. The same pattern is now showing up in AI initiatives, where teams solve identical problems in parallel without any of it scaling.

Who is this AI research based on, and how was it conducted?

The research draws on ADAPTOVATE's engagement history building more than 100 Centers of Excellence across financial services, energy, retail, government, healthcare, and technology, including its structured Agile Diagnostic benchmarking tool. Download the full report for the complete methodology and findings.

Why does the gap between AI leaders and everyone else matter right now?

Research from BCG and others shows a small group of "AI leaders" is already outpacing competitors on revenue growth and shareholder returns, and that advantage compounds each cycle. Organizations that delay building the right operating discipline risk falling further behind with every quarter that passes.

What is an AI Center of Excellence, and how is it different from a typical AI task force?

An AI Center of Excellence is a permanent operating mechanism that builds the capability, cadence, and standards for AI adoption across a business — it is not a volunteer knowledge-sharing group or a place where pilots quietly stall. It sits between central strategy and local execution, aligning work across business units without becoming a bottleneck itself.

The AI Transformation Is Repeating a Pattern We Have Already Solved

Download full paper below.

Most large organizations have approved AI budgets, launched pilots, and signed vendor contracts — yet few can trace that investment to a line in the P&L. This research argues the gap isn't technological. It's organizational: pilots that prove a concept and then stall, use cases that never travel between business units, and investment that can't be measured against outcomes.

The findings draw on ADAPTOVATE's decade of experience building more than 100 Centers of Excellence for large organizations navigating major operating-model shifts — including its structured Agile Diagnostic, run across client organizations to benchmark business agility maturity. That diagnostic found that 63% of organizations identified poor cross-team collaboration as their single biggest constraint on speed — the same disconnect now surfacing in AI programs, where business units solve the same problem in parallel with nothing that scales.

The stakes are rising as this plays out: AI leaders are already pulling measurably ahead of the rest of the market on revenue growth and shareholder returns, and that gap is compounding with every cycle rather than closing.

The report sets out why most AI strategies stall, what a decade of comparable transformations reveals about fixing it, and what leadership should expect to see from the operating model that does — the AI Center of Excellence.

Download the full report to see the complete findings and framework.

Download