Artificial intelligence has moved from an emerging technology to an operating reality across commercial real estate. For sponsors and investors, the open question is no longer whether AI could affect investment sourcing, asset performance, and portfolio strategy. It is how quickly, and where the effects are likely to show up first. Various shifts stand out as especially relevant to CRE investors over the next several years: underwriting speed, autonomous vehicles’ effect on land use, the future of office and coworking space, and demographic forces layered on top of it all. Here is Realberry’s perspective of where each is likely to matter most.

AI in Underwriting and Investment Selection

AI’s clearest, most immediate impact on CRE investing so far is speed. Tasks that used to consume days of analyst time, extracting data from rent rolls, operating statements, and offering memoranda, now run in a fraction of the time. A 2025 JLL survey found that 61% of institutional investors were already using AI for market analysis, roughly triple the 22% share reported two years earlier. One underwriting platform, Blooma, reports that its own users can close roughly four times as many investments with the same team.

That efficiency can change who wins investments, but it doesn’t replace judgment. The firms seeing the clearest advantage are using AI to widen the top of the funnel while keeping human underwriters focused on site selection, sponsor evaluation, and structuring, the parts of the process AI still can’t do well. In Realberry’s view, that distinction matters more than the raw speed gain. A tool that lets every sponsor analyze the same fifty investments in minutes does not, by itself, create an edge; it raises the floor for the whole industry. The edge increasingly comes from what a sponsor does with the extra time, and where it chooses to point its underwriting capacity in the first place.

Autonomous Vehicles and the “Parking Dividend”

Of all the AI-adjacent shifts facing real estate, the buildout of autonomous vehicles may carry some of the largest long-term land-use implications. Many of us can attest that private vehicles sit idle the vast majority of the time, yet a great investment of development still sets aside considerable square footage, garages, surface lots, structured decks, to store it. As autonomous fleets mature and reduce the cost of vehicle ownership, that dedicated parking could become a candidate for redevelopment.

Cities are already acting on this. Thousands of cities worldwide have already reformed or eliminated parking mandates, according to NAIOP, with more than one hundred removing minimums entirely. Denver is a recent example: the city eliminated parking minimums citywide in August 2025, building on an exemption that already applied downtown, where buildings were exempt from minimum parking requirements even before the broader citywide reform. A federal analysis found that removing parking minimums in Colorado could unlock 41 percent more housing overall in the areas studied.

For developers underwriting projects that will deliver five or more years out, that reform trend may be worth building into base-case assumptions rather than treating as a footnote. Sites that can be developed with less parking today, or none at all, may prove more valuable than the underwriting model assumed at acquisition.

Remote Work, Entrepreneurship, and the Office Footprint

AI is also changing how much office space companies need, but the direction of that change is not uniform. On one hand, AI tools let smaller teams accomplish more, which argues for leaner footprints as new, AI-native companies form. On the other hand, AI itself is a major new source of office demand: AI and technology firms alone now account for roughly a fifth of all U.S. office leasing activity, up from about a tenth just a few years earlier, helping offset the vacancy pressure created by remote work.

Cushman & Wakefield’s 2026 research frames this as a bifurcation rather than a simple contraction. In its base-case scenario, the firm’s single most likely outcome, it expects office demand to concentrate in higher-quality, well-located, flexible buildings rather than disappear altogether, while older, less adaptable office stock faces continued pressure. Coworking operators describe a similar dynamic: International Workplace Group’s CEO points to the company’s network growing at its fastest-ever rate as companies hedge between full office commitments and remote arrangements, a trend that favors well-located, amenity-rich space over generic square footage.

Margin Compression Versus the Flight to Quality

As AI tools for underwriting, market research, and investment sourcing become widely available, they narrow the informational edge that used to separate sophisticated sponsors from everyone else. In Realberry’s view, broadly available efficiency tends to compress margins over time, a pattern seen in other automation-driven industries. We would expect that pattern to show up first in the most standardized, easiest-to-replicate real estate product. That is consistent with what operators are already reporting heading into 2026, where underwriting discipline will matter more than financial engineering. Realberry’s own development pipeline reflects this thesis: Avenue South, a Whole Foods-anchored, mixed-use project within the Centerra master-planned community in Loveland, Colorado, is the kind of well-located, difficult-to-replicate product this argument favors over generic new supply.

Third-party research is picking up a related, more nuanced signal. Cushman & Wakefield’s economists describe an AI-driven “K-shaped” divergence in which AI-driven equity gains are supporting demand at the top end, while fading concessions and affordability pressure are expected to benefit affordable and workforce-oriented housing even as they weigh on commodity-like Class A product. In Realberry’s view, this reinforces the case for owning real estate that is difficult to commoditize, whether through location, positioning, or a basis built below replacement cost, rather than new, generic product that a well-capitalized competitor with the same AI tools could replicate at scale.

Demographic Tailwinds: Discretionary Income and Longevity

Autonomous vehicles could reshape household budgets in an underappreciated way, as well. As adoption grows over the next decade or more, costs to use these vehicles may fall, reducing the fixed expense of financing, insuring, and maintaining a car. That frees up discretionary income for housing, travel, leisure, and retail spending, indirectly affecting that asset class.

A separate demographic shift is reshaping long-term CRE demand: the U.S. population is aging rapidly, driving unprecedented demand for senior housing. Eighty six percent of surveyed investors plan to grow their senior housing allocations in 2026.

Together, these trends point to two effects worth watching. First, AI-driven advances in health technology could extend healthy life expectancy, letting more people age in place and changing how communities plan senior living and how long a home needs to serve its residents. Second, falling transportation costs could free up household income for housing, travel, leisure, and experience-driven retail.

Taken together, these five shifts point to the same underlying conclusion: AI is not eliminating the value of underwriting judgment, location, and patient capital in commercial real estate — it is redistributing it. Speed and data access are becoming table stakes, while the durable edge is shifting toward sponsors who can turn that efficiency into sharper site selection, better-positioned assets, and disciplined execution across a full cycle. In Realberry‘s view, the practical takeaway for investors is less about identifying an “AI winner” and more about favoring real estate, and real estate partners, built to hold up in a market where information advantages are increasingly available to everyone.