The 3 Levels of AI Maturity in CRE | QCI Ep 33

Powered by HqO - Learn more and join the Quantum City Initiative here: https://www.hqo.com/the-future-of-cities-begins-now/ AI in commercial real estate has moved from “we should probably look at this” to “why don’t we have a plan yet?” That was the feeling coming out of our CAB in Los Angeles. We had owners, operators, and executives from LPC, Hines, LBA, ARE, Piedmont, Swig, MetLife, and Hudson Pacific in the room. Closed-door conversations. A few dinners. A World Cup match at SoFi. And somewhere between the meetings and the traffic leaving the stadium, one thing became pretty obvious. CRE is splitting into three groups. Some companies still don’t have an AI strategy. Some are paying for ChatGPT, Claude, or Copilot and hoping experiments turn into a plan. A smaller group gets it: the real advantage will come from operations, building-level data, and the people who know how the work actually gets done. We’re still figuring out the cleanest way to describe this. But “buy more tools” is not the answer. In this episode, we talk through the 3 steps we think every CRE company needs to take: find the operational experts, identify the AI-curious people already testing things, and create incentives so adoption doesn’t feel like a threat. Because if the person who knows the building best thinks AI is coming for their job, you’ve already lost. We also get into China’s $300 billion AI compute plan, why land with energy, water, and fiber may be wildly underpriced, how export controls could change data center underwriting, KKR’s $10 billion Helix platform, Manhattan hitting 4.2 million square feet of office leasing in May, and why hospitality may be turning into infrastructure. In this episode: Why CRE is falling into 3 stages of AI maturity The 3 steps we’d take before buying another AI tool Why building-level data is becoming the constraint How operators and AI-curious employees can build the internal engine Why incentives matter more than most teams want to admit China’s $300 billion compute plan and the U.S. permitting problem Why energy, water, and fiber are becoming real estate’s AI premium How model risk could show up in data center underwriting KKR’s $10 billion Helix bet on AI infrastructure Why 4.2 million square feet of Manhattan leasing doesn’t mean every office building is back The thread running through all of it: AI will reward the companies that know their buildings, know their data, and can turn all that messy operational knowledge into systems. Not someday. Now. Sponsored by HqO, the leading tenant experience platform for commercial real estate. TIMESTAMPS:   00:00 Intro + CAB in Los Angeles 03:30 What CRE leaders are actually saying about AI 09:30 The 3 stages of AI maturity in commercial real estate 18:30 How to build a real AI strategy inside a CRE organization 23:00 China’s $300B AI compute plan 27:00 Why energy, water, and fiber are becoming AI’s real estate premium 30:00 Fed rates, inflation, and energy risk 33:30 Anthropic, export controls, and data center underwriting risk 37:30 SpaceX, Cursor, and the speed gap in infrastructure 40:30 KKR Helix and AI infrastructure as a service 43:00 Manhattan office leasing and the K-curve 45:30 Hospitality as infrastructure 47:00 World Cup 2026 as an infrastructure stress test 48:45 Meta morale, snacks, and leadership misses