Reading the Market Data: How AI Is Influencing Luxury Real Estate Buyer Behavior
Palm Beach, FL - December 23, 2025. Florida is entering peak selling season, and the signals are encouraging. Luna at Marina Pointe on Tampa Bay is showing momentum, and Kolter Urban just delivered Selene Oceanfront Residences on Fort Lauderdale Beach. The headline across the state: demand for quality product is healthy, but buyer visibility is changing.
The signal: demand is strong, visibility is shifting
Affluent buyers from the Northeast, California, Texas, and abroad continue to move capital into Florida for lifestyle, tax, and long-term investment reasons. Cotton & Company's work across multiple markets points to a clear shift: interest hasn't faded, it's just harder to spot in the early funnel.
Historically, the path was linear-search, browse, register, engage, tour. Now, many prospects skip the "introductions" and step in late with intent. Page depth, early registrations, and casual inquiries can understate true readiness.
"The risk for developers is not weakening demand. The greater risk is misreading the data and assuming interest has declined, when in reality the buyer's path has simply become more efficient," said Laurie Andrews, President of Cotton & Company.
AI is compressing the research phase
Affluent buyers are early adopters. They're using AI to compare markets, communities, and product-quietly-before ever contacting a sales team. That means the first time you see them, they've already narrowed their options.
- Using AI to evaluate lifestyle, location, and carry costs
- Comparing developments through conversational, data-driven queries
- Arriving with short lists and clear must-haves
- Spending less time browsing, more time validating decisions already in play
As one executive put it, "AI is not replacing human decision-making. It's compressing the path to conviction."
Why luxury feels it first
High-end buyers value speed, clarity, and trusted information. When tools reduce friction, adoption happens fast. The first change developers feel isn't softening demand-it's reduced visibility in legacy metrics.
What to track now
- Late-funnel indicators: qualified tours, broker-driven appointments, proof-of-funds received, unit-specific inquiries, contract cycles, and close rates
- Validation behaviors: downloads of floor plans and spec sheets, saved units, configurator saves, pricing confirmations, HOA/fee lookups
- Broker influence: deal origin by agent, referral velocity, and appointment-to-offer ratios
- Offline-to-online ties: call tracking, QR codes at events, unique URLs in print, and CRM fields for "entered with shortlist"
Make your project discoverable to AI systems
- Publish clean, machine-readable facts: unit mix, square footage ranges, pricing bands, HOA/condo fees, amenities, pet policies, parking, and delivery timelines
- Use structured data so facts can be interpreted consistently. Start with schema markup and keep it updated as pricing and inventory change. Search documentation
- Eliminate contradictions: align website copy, brochures, press releases, listing portals, Google Business Profile, and broker collateral
- Create comparison pages against true comps. AI tools surface side-by-sides-give them accurate, current data to work with
- Centralize canonical facts in a single source of truth and link to it from every channel
Equip brokers and sales teams
- Broker kits: AI-ready fact sheets, amenity matrices, fee tables, and one-page comparisons to key competitors
- Sharable data rooms with current floor plans, inventory, and approved renderings
- UTM-based referral links and QR codes for every broker campaign
- CRM updates to capture: "How many options on your shortlist?" and "Which comparables are you weighing?"
- Weekly signal reviews: late-funnel KPIs, broker feedback, and pricing sensitivity by plan
Operational playbook for Q1
- Rebaseline KPIs around late-funnel behaviors; stop over-weighting top-funnel vanity metrics
- Audit every public fact for accuracy and consistency across all channels
- Ship structured data and a public spec hub with canonical details
- Publish two high-signal pieces: "How we compare to [Comp A/B]" and "Total monthly cost by plan"
- Stand up broker microsites with live inventory and sharable links
- Instrument appointments: source, time to offer, objections, and document requests
- Tighten media targeting to in-market signals; reduce spend on broad awareness that doesn't convert
- Set a 14-day cadence to refresh inventory, pricing bands, and FAQs
- Host focused tours for pre-qualified prospects with direct pathways to reservation
- Review pricing power weekly; maintain value signals with real deliverables and proof (views, finishes, services, and brand equity)
Context on current momentum
Positive indicators at Luna at Marina Pointe and the completion of Selene Oceanfront Residences show well-positioned product is still moving. The takeaway for developers across Florida: treat "less visible" as a data problem, not a demand problem.
Looking ahead
Technology is changing how buyers do their homework. Deep market expertise still wins, but it now needs clear, consistent data and late-funnel measurement to match how decisions are actually made.
The opportunity isn't just to watch the market; it's to read what it's quietly telling you-and adjust your playbook accordingly.
Further reading on AI's buyer impact: GenAI adoption and decision speed. For teams building practical skills, see AI courses by job.
Your membership also unlocks:
