Raw compute is never defensibility
The real value unlock never comes from dropping a chatbot onto a legacy process. It comes from redesigning operational workflows around proprietary ground truth.
How does a computational neuroscientist end up friends with a private equity titan from KKR? On paper, our worlds look completely different.
When I first sat down with Ming, we were scheduled for a brief introductory chat. Ming spent roughly two decades helping build KKR, joining in 2006 before the IPO, working alongside Henry Kravis, and serving as Executive Chairman for Asia Pacific. Today he is a Senior Advisory Partner.
We blew straight past the calendar invite. We bonded over our origin stories, our roots, and how we look at human systems. That first meeting stretched so long he had to push his next commitment, handed me his phone number, and asked to meet again the following day. He has become a valued mentor and a dear friend.
Ming just published an exceptional piece on the Innovation Paradox in technology adoption. His core question hits hard: why are we innovating faster while productivity growth slows down?
Everyone in Silicon Valley preaches that AI is transforming the global economy. Yet per McKinsey data Ming highlights, 88% of enterprise CFOs report that AI has barely moved their bottom line.
Consumer adoption hit 53% in three years, but true enterprise deployment sits near 10%. Even more striking, only 6% of enterprises see more than a 5% EBIT impact from AI.
Ming points out that this 82-point gap comes down to workflow redesign. Most companies try putting a jet engine onto a horse carriage. Only 21% of adopters have actually rebuilt their operational workflows from scratch.
Ming's operational private equity lens mirrors exactly what I see in biotech and AI. Algorithms and foundation models are commoditizing by the month. Raw compute is never defensibility.
The real value unlock never comes from dropping a chatbot onto a legacy process. It comes from redesigning operational workflows around proprietary ground truth.
Watching a leader who spent decades operating at the highest levels of global finance bring that level of clarity to AI is refreshing.
Grateful for Ming's mentorship, his sharp mind, and his generosity to the next generation.
Originally posted on LinkedIn.
