Retail real estate has always depended on a mix of data and instinct. Today, AI is balancing the scales, making psychographic and persona data more available and actionable, while human observation remains essential for reading emotion, context, and intent in the moment. For retailers, it’s not a question of choosing one over the other but learning how to combine them to make better site decisions and stronger leasing commitments.

As AI becomes more abundant and sophisticated, the competitive advantage for brokers and lease agents may shift from accessing information to interpreting it. Recent research from Reddit and WPP Media on how human conversations build consumer confidence reinforces this point: in an increasingly data-rich environment, understanding the human factors that influence decision-making across all sectors remains critical.

Recent industry research suggests this balance is already taking shape in commercial real estate. A joint study by First American Data & Analytics and DealGround found that while nearly two-thirds (65.9%) of CRE professionals use AI weekly or daily, only 5.1% fully trust it for decision-making. More than half (53%) use AI strictly as a support tool rather than a decision engine, underscoring the continued importance of human expertise in evaluating risk, context, and opportunity.

From Data Points to Human Context

Traditionally, site selection leaned heavily on demographics, traffic counts, comp sets, and broker-driven market knowledge. Those inputs are still relevant, but they can miss critical information: who actually shops where, why they come, and what emotional state they are in when they arrive.

AI now helps retailers layer behavioral and psychographic signals onto location data, which gives a much more precise view of demand. A market may look strong on paper, but if the customer base does not align with the brand’s true persona, the location may underperform. At the same time, human site visits remain the best way to detect what no dashboard can fully capture: friction, energy, service quality, shopper mood, and the lived reality of a trade area.

Why Site Visits Still Count

Site visits are no longer just about checking visibility, parking, access, and co-tenancy. They are also about reading the customer experience in real time. A person on the ground can notice whether a center feels premium or tired, whether staff are engaged, whether shoppers seem rushed or relaxed, and whether the environment matches the brand promise.

That human layer of emotion shapes retail behavior. AI can identify patterns, but it cannot fully sense the nuance of a neighborhood, a center, or a property the way a trained human observer can. The strongest retailers are using AI to narrow the field, then using site visits to validate whether the property truly fits the brand’s personality and customer expectations.

What Changes in Leasing

Lease decisions are also becoming more strategic. If AI and psychographic data show that a retailer’s highest-value customer is concentrated in a certain type of trade area, the lease conversation becomes less about securing space and more about whether the property can support long-term brand fit and sales productivity.

That affects how retailers think about rent tolerance, term length, co-tenancy, and flexibility. A lease in the wrong location can become an expensive mismatch, even if the center looked good in a traditional demographic screen. On the other hand, a property that aligns with customer behavior and emotional fit may justify a stronger commitment because the brand is better positioned to convert traffic into loyalty.

All of which elevates the advisory role for brokers and lease agents. In a market where most CRE professionals still rely on AI as a support tool rather than a decision-maker, the ability to translate data into actionable market insight, validate assumptions in the field, and apply local knowledge may become an even more important differentiator.

What Retailers Should Do Now

Retailers should treat AI as a filter, not a replacement. Use it to identify the markets and trade areas most likely to align with your customer persona, then use in-person visits to test the on-the-ground experience. The combination of data intelligence and human intuition leads to better underwriting, better site selection, and smarter lease decisions.

The practical takeaway is simple: the best site is not always the best-looking site, and the best lease is not always the cheapest one. In fact, traditional real estate metrics alone may not reveal the full picture. As of Q2 2026, retail vacancy rates were relatively tight across property classes, with Class A centers at 4.1%, Class B centers at 5.1%, and Class C centers at 4.6%. While these figures point to a generally healthy demand, they do not explain the qualitative differences that drive long-term performance: shopper behavior, brand alignment, customer experience, and emotional connection to place. As AI expands the ability to analyze markets and trade areas, retailers still need human insight to determine whether a location truly fits their customer and brand strategy.

Retailers that understand both the analytical and emotional dimensions of a location will be positioned to choose spaces that support actual demand.

If you are looking to align your real estate strategy with evolving consumer behavior, connect with a Colliers retail expert to discuss how data, local market expertise, and human insight can inform smarter site selection and leasing decisions.

For more on the evolving relationship between data and retail performance, listen to Retail Recorded Episode 32 featuring Ricardo Belmar, Founder of Retail Razor.