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AI ROI advisory

Most enterprises measure AI adoption. Almost none measure AI return.

We identify where AI creates real economic value, implement it with cost and risk controls, and prove the return in the language of the CFO.

  • Pilots multiply. Few reach production, and fewer still get measured once they do.
  • Inference spend rises steadily. Almost nobody can explain which workflows are driving it.
  • Legal and risk teams are asked to approve AI use cases they were never shown the economics for.
  • The board asks for a return figure. What comes back is an adoption figure.

Our framework

The ROAI Method

A repeatable path from a long list of ideas to a governed, measured deployment.

1Measure2Prioritize3Implement4Govern

Every engagement moves through the same four stages: measure what AI is actually costing and returning today, prioritize the workflows worth automating, implement with cost and risk controls built in, and govern the result so legal and risk do not shut it down six months in.

See the full method

What makes us different

We will tell you where AI should not be used

Every AI vendor and systems integrator is incentivized to find a reason to deploy. We are not. Part of every engagement is naming the workflows where the cost of getting AI wrong exceeds the value of getting it right, and saying so plainly, before you spend the budget finding out yourself.

Research

Executive-level research on AI return

Full papers on model economics, governance, and workflow automation. The executive summary is always free to read.

Browse the research library

Daily AI briefing

What enterprise AI leaders need to know, every morning

A short, opinionated read on the AI news that actually affects budgets and governance. Free, and always public.

Read the latest issue

PLACEHOLDER REMOVE BEFORE LAUNCH: client results and metrics will appear here once real engagements are complete. Nothing is published in this section until it is real and client-approved.

Know what your AI spend is actually returning.