Research, analysis, and commentary on workforce intelligence, AI adoption, and human capital strategy from the Levos AI team.
Why AI ROI Studies Contradict Each Other, and Which One Your CFO Should Believe
Deloitte says most AI initiatives are meeting ROI expectations. MIT found 95 percent of pilots showed no P&L impact. Same year, same firms, opposite answers.
The AI Proof Gap
78 percent of executives could not pass an independent AI governance audit in 90 days. The problem is not policy. It is numbers no one can stand behind.
Subtraction Is Not a Strategy: Why AI-Driven Layoffs Are Failing the ROI Test
Gartner's May 2026 data shows roughly 80 percent of organizations deploying autonomous AI have cut workforce, and those cuts are not generating returns. Here is why headcount math without a measurement layer is the most expensive mistake CFOs are making this year.
The AI ROI Gap: What Uber's CTO Couldn't Answer
Uber exhausted its full-year 2026 AI budget by April. The cause was not infrastructure or a vendor contract. It was internal adoption no one had modeled. Here is why every enterprise will face the same gap, and what an AI Impact intelligence layer actually has to measure.
From Experimentation to Scale: The Four Operational Shifts AI Programs Need to Make
Most organizations are stuck running AI experiments without the cross-functional measurement to know which ones are ready to scale. Here are the four operational shifts required to graduate AI from pilot to production.
Counting Agents Is Not a Strategy: How CFOs Should Actually Measure AI Investment
Mid-market CFOs are being asked to justify AI spend. Agent counts do not answer the question. Here is the four-number framework that does, with the math a CFO can put on a board slide.
