Rahul Jindal
Most enterprises have an AI strategy. Few are getting AI transformation. The gap between the two is the most expensive operational mistake of the decade.
I write and build at the intersection of strategy, automation, and AI at the scale of a 200,000-person organization. Senior Director at Google. Co-author of The Scale Imperative (Routledge). IIM Ahmedabad. Kellogg.
The frameworks on this site come from that vantage point. Not from outside, advising. From inside, building.
Connect on LinkedIn/rahuljindal
The Thesis
The story of enterprise AI is going to be written one way: who absorbed it fast, and who didn't. Most large organizations have all the technology they need. They have all the capital they need. What they don't have is the metabolic speed to convert capability into operating reality before the market does it for them.
Every framework on this site exists to answer one variant of one question: where is your organization losing speed, and what would you have to change to get it back?
“The technology had evolved. The organism hadn't.”
The Frameworks
Six live diagnostics, more in development. Each names a specific shape of the absorption problem.
Organizational Metabolism Index
The first framework. Measures how fast an enterprise can absorb AI across six dimensions: leadership, process, talent, data, technology, culture. Not capability. Speed. Benchmarked against 12 industries.
The Margin Thesis
Four-plus trillion dollars of committed AI capex forces a margin-compression cycle on every exposed firm, regardless of whether the capex bet itself pays off. Five firm-level factors predict whether you absorb the squeeze or get absorbed by it.
Why I Built This
A career inside Google running operations and transformation at scale taught me one thing the strategy decks miss. AI transformation fails at the speed of organizational absorption, not at the level of organizational capability. Large enterprises have most of what they need to win. What they lack is the metabolism to convert capability into outcome before the market does it for them.
Consulting firms sell capability assessments. Nobody measures absorption speed. So I built the diagnostic that should have already existed. OMI was the first. The others followed when I kept seeing other shapes of the same problem.
These frameworks are free to use. The diagnostics are free to take. If they sharpen the question your team is asking, that is the win.
What Comes Next
The next decade will produce a small number of operators who built durable competitive advantage in the AI era, and a much larger number who explained why they couldn't. Everything on this site is for the first group.