Raoul Thomas has watched enough capital move across enough continents to know when a quiet shift is becoming a structural one. The Miami-based executive chairman, whose career has spanned banking regulation, international capital markets, and large-scale asset strategy across North America, the Caribbean, Africa, and the Middle East, is not someone who reaches for hyperbole.
When he says the criteria by which assets are evaluated are changing with increasing speed, it is worth pausing to understand what he means and why the implications surpass any single sector.
A New Input That Did Not Exist a Decade Ago
The traditional variables, such as location, quality, tenant base, revenue, and replacement cost, still matter, but a new input has entered the underwriting equation that did not exist a decade ago: how intelligently an asset is actually being operated.
A hotel running on a modern operating system, with real-time data flowing across pricing, labor, maintenance, and guest experience, is now a categorically different asset than the same building managed conventionally. The same logic holds for office buildings, logistics facilities, and financial platforms. The physical envelope no longer tells the whole story.
Thomas draws a distinction that experienced operators will recognize. The quality of the people running an asset has always been the dominant input. What AI changes is whether their judgment gets amplified by the systems around them — or wasted on tasks software should be handling quietly in the background.
How Institutional Capital Is Beginning to Underwrite Differently
The shift Thomas describes is not yet universal, but he believes it is closer than most owners recognize. Within the next few years, he expects institutional buyers to begin underwriting assets based on the quality of the operating platform as much as on the underlying real estate.
“Within the next few years, I think institutional buyers will start underwriting assets on the operating system as much as on the underlying real estate,” Thomas says. “That is a quiet but quick change in how capital evaluates value, and most owners are not yet positioned for it.”
Owners who have invested in intelligent infrastructure are building something that reads differently on a due diligence checklist than it does today. Those who have not are holding a less competitive asset, and Raoul Thomas believes the market will begin pricing that gap before most of the industry is ready.
The Real Cost of Operational Friction
Numbers matter in asset management, but Thomas consistently returns to something less quantifiable: the human cost carried by the operators inside these assets every day. Property management systems, accounting platforms, maintenance logs, vendor invoices, customer feedback streams, payroll data, utility consumption records, and leasing CRMs all exist in separate systems with separate logins.
The people responsible for operating the asset spend enormous amounts of time reconciling information that should have reconciled itself overnight. The result is inefficiency and erosion.
“The cost of operational friction is not only financial,” says Thomas. “It is human. The teams I have watched run hotels and offices and infrastructure assets carry a weight that doesn’t show up in any dashboard…late nights, fragmented information, the same problems handled by hand month after month, the slow erosion of people who care too much about a job that is structurally harder than it should be.”
Coming from someone who has operated at the highest levels of global finance and real estate, Thomas has watched the pattern repeat across asset classes and geographies. AI, deployed well, gives the best operators something simple and overdue: their evenings back.
Beyond Automation: The Case for Consistent Operating Quality
A common misconception is that AI’s value in asset management is primarily about cutting costs. Thomas sees the larger opportunity on the revenue and capital side — better pricing, sharper risk controls, improved allocation, and scalability that does not require adding headcount proportionally.
There is also a misconception about what digital transformation in operations actually involves. Most organizations buy software without changing the workflows or accountability structures it was meant to support. The result is more complexity, not operating leverage.
The more fundamental question Thomas encourages leaders to ask is how the business should operate if intelligence were genuinely embedded in every layer of it, end to end — a question that requires thinking about data architecture, governance, and cultural change, not just procurement.
The Human Element Remains the Point
Thomas has genuine regard for the operators who built these industries by hand, like the hotel managers who knew every regular, the property managers who could sense a building’s condition walking through the door. The goal of AI is not to replace that craft. It is to remove the parts of the work that waste it.
“AI should not remove the human element. It should free the human element to focus on what people actually do well,” says Thomas.
In hospitality, workspace, and financial platforms alike, the qualities that matter most, including warmth, judgment, and earned transparency, are not automated. They become more valuable as transactional work gets handled in the background. The assets that perform best will be the ones where technology does its work invisibly, and the people inside them are freed to do theirs.
Defining the Next Generation of Best-in-Class Assets
Three qualities in Thomas’s framework will define best-in-class assets in the years ahead. Intelligence, meaning the asset can generate and interpret its own operating data in real time, is the first, followed by adaptability, which allows the operating model to respond to shifting demand, costs, and market conditions without a lengthy replanning cycle. Execution entails the organization converting insight into action repeatedly and at an acceptable cost.
The next generation of owners will expect dashboards, predictive analytics, automated workflows, and AI-supported decision-making across every asset they hold. Value will be increasingly tied to the quality of the platform behind the asset. Location will always matter, but intelligence, as Raoul Thomas sees it, is becoming the variable that separates ownership from leadership, and assets from legacies.