AI is quietly reshaping how decisions are made across the commercial real estate (CRE) industry.

The market has been flooded with companies claiming to use AI and large language models (LLMs) to streamline processes. Startups and public companies recognize that positioning themselves as an “AI-driven company” has the potential to lead to higher valuations and more investment. It’s a powerful buzzword that can attract capital.

However, I find that some of these claims amount to rebranded features with minor AI components added to stay relevant. As business leaders, we need to be proactive in evaluating clients, vendors and property technology (proptech) firms that flaunt the use of AI and ensure they can point to specific and measurable outcomes.

That said, beneath the hype, a genuine and powerful transformation is underway. According to a Dealpath survey of 100 commercial real estate investors (registration required for full report), “institutional investors see AI not as an optional experiment, but as a foundational capability for competitive advantage.”

How AI Is Impacting Real Estate Operations

Broadly speaking, AI adoption is accelerating across many industries. According to McKinsey, 31% of C-suite leaders across industries expect more than a 10% revenue uplift via AI over the next three years, and 92% of companies are planning to increase their AI investments. Large language, general-purpose models that have the ability to understand and generate language represent the “cutting-edge” capabilities many are talking about. I believe these tools have the potential to meaningfully reshape the future of real estate investment management (e.g., valuation, underwriting, property analytics) as proptech firms embed LLMs in their platforms.

In real estate, AI is increasingly acting as a creative co-pilot, handling the tedious parts of the workflow and amplifying human creativity. It’s putting pressure on traditional office-centric roles by creating efficiency in repetitive document-heavy tasks. It can be used to help accelerate deals by streamlining lease abstraction and legal review, transaction due diligence, tenant communications, predictive analytics, marketing copy generation and routine document automation.

Tasks that have traditionally served as the “proving ground” for junior analysts in commercial real estate, such as writing simple property descriptions and analyzing data, can now be done instantly by AI. As a result, I believe fewer entry-level jobs may be available, as one senior analyst using AI may be able to produce the output that previously required a small entry-level team. While this doesn’t eliminate the need for talent, it does signal a shift in how organizations structure their teams and deploy resources.

AI is also playing a role in compliance. At my company, for instance, we are currently piloting a private enterprise solution that fits into our compliance framework to align with our broader strategic objectives, ensure we meet regulatory obligations and actively embrace responsible business practices.

AI’s Impact on the Broader Market

As AI reshapes internal real estate operations, it’s also impacting external market dynamics. AI-related companies are driving a meaningful share of today’s overall leasing momentum. CBRE reported that AI-related companies are projected to take up to 16 million square feet in San Francisco by 2030. Tech giants and startups alike are expanding their AI infrastructure, leasing office and research and development (R&D) space to house their teams.

“Larger and more established firms are typically hunting for class A space, while startups that need flexibility to accommodate growth or a potential acquisition want short commitments in class B space ready for immediate occupation,” according to the National Association of Real Estate Investment Trusts. This highlights how AI-driven companies are shaping demand across building classes, each with very different space needs.

Positioning Assets for the Future

Long term, the most enduring effects of AI on office real estate are likely to be structural, rather than temporary. Efficiency and automation in back-office functions, from leasing and contract review to day-to-day operations, are quickly becoming the norm, streamlining workflows and reducing friction across the industry.

At the same time, AI will continue to reshape tenant expectations. Every day, I see tenants increasingly looking for flexible infrastructure, from adaptable floor plans to plug-and-play power and cooling systems, allowing them to scale and reconfigure as their needs evolve. This shift coincides with a growing tenant mix weighted toward technology, AI, R&D and other data-intensive sectors that demand specialized, resilient and adaptable space. Layered onto this is the rising premium on “smart building” capabilities, where AI-driven systems such as predictive maintenance tools, energy optimization and overall building intelligence are often expected standards.

In the future, demand may continue to grow for “intelligent lab/office hybrids,” modular R&D environments and densified layouts. AI-heavy tenants may demand low-latency power, fiber connectivity, cooling and hyper-flexible floorplates rather than classic office configurations.

Lessons for Real Estate Leaders

Having successfully navigated multiple market cycles and technology shifts, we at my firm view the rise of AI not as a disruption to the fundamentals of real estate but as another inflection point – one that requires thoughtful integration to ensure office assets continue to meet evolving tenant needs and the culture of work well into the future.

First, adopt a test-and-learn approach: Pilot AI tools with a single asset before implementing a broad rollout. Be judicious and data-driven. For owners, incorporate flexible, “future-ready” floor plans that can adjust to tenant growth or contraction. Offer plug-and-play infrastructure (e.g., power, fiber, cooling) to attract AI, R&D and other data-intensive users. For operators, explore and embed AI into property operations, including tenant helpdesk chatbots, predictive maintenance and energy optimization tools to help reduce costs and improve service. Underwrite for flexibility, upgrade potential and the resilience of the tenant mix.

It’s also important to note that AI won’t replace the profound and innate human need for connection, collaboration and community. People need face-to-face connection, mentorship and cultural cohesion. In my view, this means the office is not dead. Instead, its purpose is being redefined. I believe the most successful companies will use AI to empower flexible work, while simultaneously investing in high-quality, purpose-driven physical spaces designed for the human interactions that technology cannot replicate.

Finally, while AI has the potential to introduce unprecedented speed and scalability, its use must be balanced with strong leadership. The most effective strategies will combine AI-driven efficiency with the human insight necessary to maintain brand identity, authenticity and breakthrough innovation.

Originally posted Feb 19, 2026, 07:30am EST on Forbes.com