Commercial real estate is being forced to confront a simple reality: the way people use space has changed faster than the buildings themselves. Rising operating costs, volatile energy prices, labor shortages, and mounting ESG pressure have exposed the limits of static assets. In a market where nearly 40 percent of global energy consumption is tied to buildings, standing still is no longer an option.

A new generation of human-centric, autonomous buildings is beginning to take shape. These are not just “smart” properties chasing isolated efficiency gains, but integrated environments that sense, learn, and act. Powered by AI, digital twins, IoT networks, and predictive analytics, they move beyond reporting problems to resolving them in real time—balancing comfort, cost control, and carbon reduction across an asset’s lifecycle.

The shift from smart to autonomous is not about novelty. It is about survival and competitiveness. Owners who orchestrate systems, data, and human oversight into a unified operational layer are unlocking resilience, flexibility, and measurable tenant experience gains. Those who hesitate risk watching their portfolios drift toward obsolescence as autonomy becomes the new benchmark for performance.

Real estate services stocks slid after investors folded the sector into the broader AI scare trade that has already hit consulting, insurance brokerage and parts of finance. The logic is straightforward. Generative AI tools can now draft marketing materials, summarize lease comps, build valuation models, and scan zoning or market data in seconds. For firms like CBRE, JLL, and Cushman and Wakefield, which rely on large teams of brokers, analysts, and support staff, that raises a question about how much human labor is really required to execute a deal.

The timing amplified the concern. Commercial real estate transaction volumes are still recovering from higher interest rates and a slower capital markets environment. When revenue growth is uneven, equity markets become more sensitive to any factor that could pressure margins. Investors began asking whether clients will use AI as leverage in fee negotiations, especially for standardized services like valuation, research, and portfolio analysis. The result was a repricing of companies whose business models are built on advisory fees and commissions.

But real estate is not software or retail trading. Brokerage and advisory work remains deeply relationship-driven. Large office leases, portfolio sales, and complex debt placements are negotiated across networks built over years. Local knowledge, trust, and access to capital still matter in ways that cannot be fully automated. AI can speed up underwriting and improve data accuracy, but it does not replace the broker who knows which landlord will bend on concessions or which buyer can close in a volatile market.

In the near term, AI is more likely to reshape cost structures than eliminate the need for service firms altogether. If deployed well, it could allow brokers to handle more deals with leaner teams and better analytics. That may ultimately protect or even expand margins. The market’s reaction reflects uncertainty about how that transition plays out. The bigger question is not whether commercial real estate services survive AI. It is how quickly they adapt and who captures the efficiency gains.

The D.C. attorney general has filed a sweeping civil lawsuit against landlord Ali “Sam” Razjooyan and two family members, accusing them of running what prosecutors call a fraudulent real estate empire that exploited tenants and government programs while leaving properties in dangerous disrepair. The complaint alleges the Razjooyans acquired more than 70 mostly rent-controlled buildings and took in more than $16 million from housing subsidy programs by submitting false certifications and misleading lenders and city agencies about occupancy and habitability. Tenants reportedly endured rodent infestations, mold, faulty wiring, and other serious code violations, prompting years of enforcement actions and mounting fines before the new lawsuit was filed.

What makes this action unusual is the decision to sue under the Racketeer Influenced and Corrupt Organizations Act (RICO), a federal statute most often used against organized crime and long-running fraud schemes, not negligent landlords. Local attorneys general and housing departments typically pursue code violations, consumer protection claims, or false claims under state housing laws when confronting slumlords. In contrast, the RICO claim frames the Razjooyans’ alleged conduct as a coordinated pattern of fraud involving shell companies, falsified documents and a web of deceptive practices designed to sustain a profitable but unlawful enterprise.

For the broader housing and landlord enforcement landscape, the use of RICO signals a shift toward more aggressive legal strategies when landlords’ conduct appears systemic rather than isolated to one building or property. Traditional housing code enforcement can require repeated actions, property by property, and often yields incremental remedies like fines, injunctions or orders to repair. The RICO approach bundles many properties and many alleged violations into a single civil racketeering framework, potentially allowing the city to pursue damages, restitution, penalties and even a ban on owning rental properties if a court agrees the enterprise constituted a corrupt organization.

Propmodo Daily is written and edited by Franco Faraudo with contributions from readers like you and the Propmodo team.

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