AI adoption isn't a technology decision, it's a leadership decision.
You can select the best platforms, hire the smartest vendors, and allocate significant budgets. But if your organization isn't prepared to work alongside AI, you'll plateau fast.
The fastest-moving companies are the ones where AI fluency spreads organically - where employees experiment with new workflows, where managers spot automation opportunities in friction areas, and where teams iterate without waiting for executive permission.
The CEO’s role in this is critical. This isn’t about mastering prompt engineering or understanding AI architectures. Your role is to set the organizational tone that makes AI adoption inevitable rather than optional.
The reality is simple: your attitude toward AI becomes your company's attitude toward AI.
This article draws from our white paper, Real Estate AI: A CEO’s Guide to What Matters Now. It tackles the most important AI questions facing real estate leaders and lays out a clear path to adoption. Download the full guide.
What’s the CEO’s Role in Navigating the AI Shift?
It’s the CEO’s job to make AI part of the company’s culture. Not by knowing all the technical details, but by making sure teams have the space and support to start using it in their day-to-day work.
Build AI Fluency Through Action
The fastest path to organizational AI adoption isn't through formal training programs or courses. It's through experimenting with AI and seeing where it adds value in daily workflows.
Get your teams using AI tools, like ChatGPT, Claude, Jasper etc. But make sure they’re only using enterprise accounts instead of personal ones. It helps keep company data secure, prevents accidental data sharing with public models, and gives access to more advanced features.
Encourage experimentation with daily tasks like:
Creating meeting summaries and action item lists
Summarizing complex lease documents and due diligence reports
Creating property descriptions and investor communications
Identifying pricing trends
The goal here isn't perfection, it's familiarity. Teams need to understand how AI actually works, its strengths and limitations, before they can identify where it adds genuine value.
Remove Organizational Barriers
The biggest obstacles to AI adoption in real estate aren't technical, they're organizational. Legacy approval processes, risk-averse cultures, and siloed thinking create friction that kills momentum.
Your job is to actively remove these barriers, but this goes far beyond simple cheerleading. It requires intentionally designing the systems, teams, and processes that make AI adoption possible:
Equip your internal AI champions with the right tools and send them to relevant industry conferences and peer meetups. They need to stay sharp on AI trends and know how to bring those insights back into the real estate context.
Create cross-functional AI committees with real decision-making authority, not just advisory roles. Give them budgets for experimentation and the authority to bypass SOPs when running pilot projects.
Normalize rapid iteration by celebrating learning, even when things don’t go as planned.
Protect early adopters from organizational resistance → “that's not how we've always done it."
This structural work takes time to get right, but it is what separates companies that successfully scale AI adoption from those that get stuck in pilot stages.
Make Timely Strategic AI Decisions
While your teams handle day-to-day AI experimentation, certain decisions require CEO-level attention. These choices will determine whether your AI initiatives drive lasting impact across the business or remain isolated productivity improvements.
Weigh Your Options: Build, Buy, or Partner
Building AI solutions internally requires significant investment in AI talent and infrastructure. This is a long, expensive path best suited for companies with the resources, time, and specific needs to justify it.
You may think buying existing AI software is the more practical option. But not all AI tools are the same. Choosing between AI-native and AI bolt-on products will shape whether you see small gains or real change.
Partnering with a venture studio like Stackpoint often provides the fastest path to meaningful results, as a full-stack team with deep AI capabilities seamlessly collaborates with you to co-build a solution that solves your pain points.
Reallocate Capital Strategically
AI adoption isn't just about adding new tools - it's about fundamentally redesigning how work gets done. This often means moving resources away from manual processes and legacy systems toward AI-enabled workflows.
These decisions affect budgets, headcount, and operational priorities. They require executive-level commitment and clear communication about why the changes matter.
Champion Major Workflow Redesigns
The biggest AI opportunities often require rethinking entire processes. This might mean restructuring how your team operates, removing extra steps, or changing how performance is measured.
Major workflow changes challenge established norms and require sustained leadership support to succeed.
Evolve Your Talent Strategy
AI doesn't just change how work gets done, it changes who thrives and succeeds in your organization.
The most valuable team members in an AI-enabled company aren't necessarily those with the deepest AI expertise. They're the ones who adapt the fastest and imagine new possibilities.
Look for people who:
Spot opportunities to improve workflows through AI integration
Collaborate effectively across functions to test new approaches
Build hybrid human-AI systems that deliver better results than either could alone
Maintain quality standards while moving at increased speed
Make AI fluency part of what high performance looks like in your organization. Create career paths that reward adaptability and systems thinking, not just tenure or historical expertise.
Identifying High-ROI AI Opportunities
As CEO, you also need to guide where your teams focus their AI experiments. The instinct is often to look at roles: "Can we automate parts of what our analysts do? Our leasing agents? Our loan officers?"
But that's the wrong lens. AI doesn't replace people, it replaces workflows. The biggest gains come from identifying repeatable, high-friction processes and using AI to make them faster, smarter, and more consistent.
Look for or direct your teams to search for processes that are:
High-friction - manual, error-prone, or painfully slow
High-volume - performed frequently across teams or locations
High-impact - tied to revenue, cost, speed, risk, or customer experience
Your role is to help teams think workflow-first: Where are we losing time, consistency, or leverage? What's the cost of that friction? What's preventing us from creating more value faster?
Move Fast, Learn Faster
One of the costliest mistakes real estate CEOs can make is over-planning AI adoption. A detailed strategy and roadmap may feel safe, but while you're perfecting the plan, your competitors are already testing, learning, and adapting.
You don't need a perfect plan to start. Just pick a team. Pick a process. Pick a tool. Run a two-week test. Learn from the results. Then iterate with slightly more ambition and better information. The momentum builds from there.
If you want to learn more about where AI adds real value, where it falls short, and how to choose the right solutions, download our white paper: Real Estate AI: A CEO’s Guide to What Matters Now. It’s built on lessons from building and scaling successful real estate companies and insights from speaking with nearly 100 industry leaders.
