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Insights on Generative AI for Real Estate Professionals

From Pilot to Practice

GenAI pilots are widespread across real estate, but few teams have moved from individual experimentation to repeatable practice. Thomas examines what separates the organisations making that transition, and why the answer lies more in workflow design, team capability, verification and governance than in the choice of tool.

Theory & Concepts

Use Cases

Welcome to the RAG Problem (Or, Why Chatting With Your Data Disappoints)

A practical reflection on why “chat with your data” tools often disappoint: they can produce confident, polished answers while missing the evidence that actually matters. This piece explains how RAG works, why retrieval is not the same as reasoning, and how common failure modes show up in professional workflows: compound questions, niche topics, and answers that require combining sources across files, spreadsheets, and emails. A useful read for anyone using tools like M365 Copilot and trying to get more reliable, evidence-based answers from their own data.

Theory & Concepts

Real Estate Applications

AI is now universally consequential

AI is no longer a novelty or a side tool. It is becoming part of the operating system of professional work. In this post, I explain why the latest models, agents and deployment tools feel like a major shift: AI is moving from answering questions to doing work. For real estate firms, that means practical use cases in investment memos, lease extraction, DCF checks, market research, ESG reviews, file clean-up and recurring internal briefings. The real challenge is not just buying access to AI. It is redesigning workflows, training people properly, and translating tacit professional knowledge into clear instructions that agents can follow. AI does not replace judgement, but it now affects almost every activity involving text, data, documents, spreadsheets, research, analysis or decision support.

Use Cases

Real Estate Applications

Investor Archetypes meet GenAI

A practical exploration of how GenAI can support real estate professionals in understanding investor archetypes, researching institutions and individuals, and tailoring communication more effectively. The piece shows how combining structural frameworks with AI-driven preparation can improve pitching, underwriting, and negotiation, while also highlighting the limits of the technology and the need for verification.

Theory & Concepts

AI automation is misunderstood and it’s an opportunity.

A thoughtful take on why AI automation is often misunderstood and where the real opportunity lies. As visual AI becomes genuinely useful and easier to deploy, the conversation is shifting from automation to delegation. This piece explores how the real value of AI is not in replacing work entirely, but in redesigning workflows so AI can handle parts of the process, while humans provide judgment, context, and oversight. A practical perspective for professionals looking to move beyond the hype and start using AI in a way that actually works in a commercial setting.

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VARi Newsletter

Insights on Generative AI for Real Estate Professionals

Expert insights, updates, and practical AI guidance for the real estate industry.

From Pilot to Practice

Welcome to the RAG Problem (Or, Why Chatting With Your Data Disappoints)

AI is now universally consequential

Investor Archetypes meet GenAI

AI automation is misunderstood and it’s an opportunity.

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