This week, much of the real estate world will converge on Cannes for MIPIM, Europe’s largest industry conference. Historically, the conversations have focused heavily on investment, particularly on market sentiment and the relative outlook among asset classes. Technology has often been a niche topic in recent years, an interesting diversion for companies to talk about while they were waiting for the investment market to come back.
Over the last year or two, however, technology, and AI in particular, has become a priority topic. I wrote last year that conversations were moving into “What should we do to succeed in this new normal?” I was struck that questions around AI were no longer about whether or even when AI will impact real estate, but more about how to execute and drive value.
One recurring topic has been what McKinsey calls the “AI paradox,” with leaders reflecting that they’re seeing AI everywhere except the bottom line. In real estate, this felt particularly relevant, especially among the investor community, which has a small and highly skilled workforce who are often conducting comparatively bespoke and complex activities.
Over the last 12 months, the landscape has changed fast. AI entrepreneur and investor Matt Shumer’s essay “Something big is happening” has gone viral in the last month, and the sentiment in his piece reflects what we’ve seen with clients across all sectors, and particularly real estate given that it has been comparatively slow to adopt AI. Agentic AI is a step change for the industry, for both investors and operators, because it can enable automation of even relatively complex workflows to get work done faster, cheaper, and more effectively.
AI is now set to reshape operating models across the real estate industry. For a couple of years, real estate companies have focused on sensible generative AI experiments: summarize a lease; draft a memo; answer a question faster; make reporting cleaner. These have yielded modest but often hard-to-bank benefits. You might free up five minutes for workers, or probably (but not provably) make slightly faster and better investment decisions, but the benefits are challenging to chase to the bottom line.
But Agentic AI is about more than helper tools that are adjacent to core activities. It’s about creating a set of systems with agency to decide and carry out actions across entire workflows, with humans maintaining authority in the loop. The big question for the industry now moves from “What are the use cases for machine learning and generative AI?” to “Which workflows should we redesign for agentic automation?”
To deliver transformative impact with agentic AI, real estate leaders should focus on domains as the unit of change. A domain is larger than a single use-case (e.g. churn prediction or memo writing), but smaller than an enterprise transformation. It’s an end-to-end set of activities with clear owners and workflows that run from clear input to measurable outcomes. Critically, it’s large enough to move the dial economically but small and contained enough to reinvent without disrupting the entire company.
“Reinvention” is key here, because real impact comes not from inserting AI into a process as a standalone step, but from redesigning an end-to-end process to enable constant iteration and improvement through a self-training feedback loop. Otherwise you end up with the familiar roadblock of the AI process getting stuck at “not quite as good as a human,” which does not deliver the confidence to progress beyond a pilot.
By focusing on domain redesign, you can run the agentic process in a “clean room,” side by side with the existing process until you prove that it works. Then you can progressively tip activity into it until you can shut down the old process entirely. These domains can include operational FM activity such as complaint handling, work-order processing, or service charge management; asset management activity such as renewals or reporting; investment activity such as opportunity identification; or capital activity such as procurement or schedule optimization.
Automation at this scale opens up the possibility of entirely new operating systems that enable work to be done faster and more accurately - and to get better over time.
It will also accelerate the shift we’re already seeing in thinking of real estate as more of a product than an asset, as competitive advantage increasingly comes from driving outperformance at asset level through active management as a differentiator – beta to alpha return. While falling cap rates and rising valuations drove returns in the last cycle, that tailwind is fading. This cycle will be defined by strong execution, with agentic AI becoming an increasingly critical ingredient.
Historically, many organizations have viewed real estate as primarily a financial asset, with success driven by good allocation. Now, success will increasingly come from managing a property to outperform a similar one across the street, by making day-to-day decisions better and faster, and satisfying customers with a high-quality product. In other words, the winning property managers of the future will use agentic workflows to transform from asset managers to product managers, spending their time thinking about how to continually evolve their products (assets) to give their tenants the best possible experience.
Of course, some managers have been thinking like this for a while. But in an industry where there are multiple handoffs and laborious processes, for many managers it has been easier to outsource day-to-day interactions and forego detailed understanding of the tenant and asset, especially in a world of compressing yields and growing rents. Agentic AI now offers them the chance to upend long-standing operating models. 2026 will be the year that leaders can start to create transformative new ways of working. It’s a question of how, not if. And I’m looking forward to debating it in MIPIM this week!
Jules Barker is an associate parter at McKinsey & Company. A digital transformation leader in McKinsey’s European Real Estate practice, he helps investors, operators, and service companies navigate disruption and advises on digital transformation, new operating models, growth strategies, and shaping McKinsey’s thought leadership
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