Within three years, your biggest competitor won't be the firm across the street—it will be a company that thinks about real estate in a fundamentally different way. While most of us are learning to use AI as a tool, they're using it to build a new kind of engine. Here's how to make sure you're the one building it.

Warning: This issue is not a snack—it’s a full meal. If you’re pressed for time, start with the Executive Summary below. If you’re crafting your firm’s AI strategy, read it all.

Executive Summary

Artificial Intelligence (AI) is rapidly shifting from an optional efficiency booster to an essential competitive foundation in commercial real estate. Currently, proficiency with AI tools like Large Language Models offers significant productivity gains—but only temporarily. Within 18–24 months, AI fluency will become commonplace, and this initial advantage will fade.

Long-term strategic advantage requires moving beyond merely adopting AI tools toward fundamentally rethinking and restructuring your business model. This involves a three-step strategic framework:

• Unbundling: AI breaks apart traditional, integrated workflows (investment management, brokerage, development, property operations) into discrete automated tasks, boosting efficiency but creating complexity.
• Emerging Constraints: Automation introduces new challenges—coordination of fragmented workflows, data interoperability and quality, trust in AI outputs, regulatory and ethical risk management, cognitive overload, and maintaining crucial human judgment and intuition.
• Rebundling: Progressive companies address these new constraints by strategically "rebundling" around three key areas:
• Data & Asset Integration: Build proprietary data platforms acting as a single, trusted source of truth integrating people, buildings, ESG, and operational insights.
• Workflow Orchestration: Create intelligent orchestration layers to manage fragmented AI-driven workflows and optimise human-AI collaboration across the organisation.
• Decision Support & Trust: Position the firm as a trusted advisor by embedding rigorous governance, transparency, and human oversight into automated decision-making processes.

Ultimately, CRE firms must choose between remaining mere "tool-users," destined to face commoditisation, or becoming strategic “engine-builders" - architects of new business systems and orchestrators of value creation in an AI-native landscape. This shift will create an unprecedented bifurcation within the industry, with profound competitive implications.

Forward-looking firms must start now. Those who navigate this rebundling effectively will dominate future markets, redefining industry leadership for the next era of commercial real estate.

Today a Super Power, Tomorrow a Commodity

Less than 10% of knowledge workers are daily users of LLMs. Circa 18% use them weekly, but if you are not using them daily they have not become part of your workflow. And if they are not part of your workflow, you’re not yet a power user. And won’t be enjoying their edge.

I think power users, or those seriously leaning in to using LLMs, have 18-24 months to ‘make hay’. They will be dramatically more productive than their peers and will be able to do the work of 2-10 people. We’ve written about ‘​Fast, Agile, Ultra-Productive Superteams​’ before and the evidence is mounting of companies generating $1,000,000+ of revenue per employee. This productivity boost from generative ai is very much a known known now.

This edge though will diminish over time, as the mainstream catches up and adopts the same tools. So the smart people in real estate need to be thinking beyond just the technology - they need to be thinking how this technology will change the fundamentals of our industry?

So with that disclaimer, that for now the fruit is low hanging, let’s look at how real estate is going to change.

Beyond Tools: Building a New Operating System for Real Estate

The current discourse often focuses on AI as a means to achieve incremental efficiencies, such as automating tasks like marketing copy generation or lease abstraction. However, this "tool view" is strategically incomplete and risks long-term commoditisation. The true power of AI in CRE lies in its capacity to act as a "coordination engine", fundamentally restructuring roles, firms, and competitive dynamics by radically reducing the friction inherent in knowledge work.

This transformation is characterised by a three-part dynamic: unbundling, emerging constraints, and strategic rebundling.

AI unbundles traditional CRE workflows across asset and investment management, brokerage, development, and property operations (in fact, all workflows), fragmenting what were once integrated roles into discrete, often automatable, activities.

This unbundling, however, is not frictionless; it introduces a new set of complex systemic constraints. Imagine that the old way of doing things in CRE had certain "frictions" or difficulties, often due to manual processes and scattered information. When AI steps in, it "unbundles" these tasks, meaning it breaks down traditional jobs into many smaller, automated pieces, which can make things more efficient. However, this fragmentation creates a new set of difficulties that the industry must navigate.

The most progressive CRE firms will not just use AI, but will actively "rebundle" capabilities around these emergent constraints to establish new control points where they can regain influence and competitive advantage by becoming indispensable in overcoming these new constraints.

1. The Great Unbundling: Fragmentation of CRE Workflows

Generative AI is actively re-architecting every major function within CRE, disaggregating bundled tasks into fragmented, AI-driven workflows.

Asset & Investment Management is seeing AI-driven analytics perform market research, deal sourcing, valuation, underwriting, and due diligence with unprecedented speed and accuracy, shifting roles from manual data processing to interpreting AI-generated insights.

Brokerage & Leasing workflows are being peeled off through AI-generated marketing materials, virtual staging, and AI chatbots handling initial client communication and routine inquiries. Lease administration tasks like abstraction, which once took days, can now be completed in minutes using AI, commoditising junior roles.

Development & Construction is being unbundled by generative design tools that rapidly produce feasibility studies, site plans, and building designs. AI also assists with project management, site monitoring, and compliance checks, moving tasks from manual creation to AI-assisted curation.

Property Operations & Facilities Management is shifting towards an "autonomous building" model. AI powers tenant service chatbots, optimises energy management and HVAC systems, and enhances security and reporting, reducing the need for large on-site staff.

Workplace Design & Operation (from the occupier perspective) leverages AI to generate office layout options, provide virtual assistants for room booking and help desk support, and analyse employee experience data for space optimisation.

This pervasive unbundling leads to increased efficiency but also creates a more complex ecosystem of tools and stakeholders.We may not, mostly, be here yet but the direction of travel is very clear. All this is coming.

2. Emerging Constraints: The New Bottlenecks

Before AI, the CRE industry was characterised by "high-friction silos" and fragmented information, where critical data was scattered across many disconnected systems and manual processes. This created "coordination costs" – an immense overhead of time, labour, and cognitive effort needed to align people and synchronise workflows, leading to delays, duplicated work, and communication breakdowns. We all used to pay this "coordination tax”.

In an AI-mediated world, unfortunately, this ‘coordination tax’ doesn’t disappear, but rather it gets transformed. As we ‘unbundle’ tasks we make them intrinsically way more efficient, but we end up with many unbundled, super efficient workflows that need to be co-ordinated and managed.

And this fragmentation created by AI introduces new systemic challenges that become the "bottlenecks of a fragmented world". This though is where new competitive advantage will arise. Companies that can effectively manage this "new coordination tax”, which won’t be a trivial pursuit, will be in a very strong position.

There will be a lot to do to get there:

A. Coordination Frictions: With work spread across multiple AI tools and providers, orchestrating end-to-end workflows becomes a significant challenge. AI's high "clock-speed" can outpace human coordination, leading to breakdowns if not managed. When one part of the business runs much faster than another, trouble can follow.

B. Data Interoperability & Quality: AI thrives on data, but CRE data is notoriously siloed, non-standard, and often poor quality. Integrating disparate data sources and ensuring data governance and common standards are critical, as AI amplifies bad data. It’s hard to see how any real estate company will succeed without, at last, sorting out its data.

C. Trust & Transparency: As AI takes over more decision-making, ensuring trust in AI outputs becomes paramount. The "black box" nature of some models and instances of "hallucinations" can undermine confidence, requiring transparency. Firms that build a reputation for responsible AI use can turn trust into a competitive advantage.

D. Risk Management (Bias, Errors, Liability): AI introduces new risks, including algorithmic bias, outright errors leading to financial loss, and cybersecurity vulnerabilities. Regulations like the EU AI Act will impose constraints on high-risk AI uses, making robust risk management a non-commoditisable capability and a potential competitive moat.

E. Decision Complexity & Information Overload: Paradoxically, AI's ability to produce vast amounts of information can lead to "analysis paralysis" and decision fatigue. The new bottleneck is human cognitive capacity to process information effectively, making the simplification of choice a valuable service.

F. Loss of Tacit Knowledge & Human Intuition: As AI automates grunt work, there's a risk of losing the "human connective tissue" and intuition gained through hands-on experience. Over-reliance on AI could lead to homogenised strategies and a loss of diverse perspectives, making human judgment scarcer and more valuable.

G. Human Judgment Gaps & Ethical Oversight: Highly automated processes risk bypassing critical human judgment points, potentially leading to undesirable outcomes (e.g., an AI optimising for a single metric like NOI at the expense of tenant experience). Deliberately inserting human judgment ensures quality and sustainability, even if it introduces "positive friction”.

3. The Rebundling Playbook: Architecting the Next-Generation CRE Firm

The above are all new problems that we’ve not had to deal with in real estate before. But they will be real, and significant. And a major impediment. So we need to think about how to ‘rebundle’ our workflows to address them.

This will mean moving beyond merely adopting AI tools to architecting an entirely new system of value creation. And this will be the super power of the new winners in real estate. Most CRE companies will adopt an assortment of AI tools, but few will push on through to this rebundling. It’s just too much of a leap for the ‘average’ company. Too much of a break with ‘the way we do things here’.