Real Estate & AI · Field Notes · Part 2 of 2

The Big Bet on Data-Informed Design

Corporate real estate has no data foundation for the AI era. Microsoft may have already built one, almost by accident.

Mark Cunningham · Founder, Insights² · Published · 8 min read

Every office designed over the next few years is a decade-long bet on how people will work. That is what property is: capital committed once, lived with for a long time. Right now, across most of the industry, that decision is being made blind.

This is what I actually care about, and it isn’t analytics for its own sake. We design today, build tomorrow, and live with the result for the next ten years. Evidence only changes the outcome at the first step. Miss that window, and the only lever left three years after occupation, when the fit-out budget is spent and the lease is signed, is retrofitting what should have been right from the start. Front-load the decision with evidence, and you spend once. Skip it, and you spend twice: once to build it wrong, again to fix what you should have known the first time.

Not for lack of ambition. For lack of a foundation. Ask a real estate or workplace leader what evidence informed this year’s space plan, and you will get benchmarks, utilisation surveys, an architect’s brief built on the last cycle’s assumptions. In the conversations I have had, ask what evidence exists for how the AI era specifically should change that plan, and that is where it stalls.

I work at the intersection of data and corporate real estate, and this is the gap I keep coming back to. This is Part 2 of two pieces. Part 1, “Are We Designing the Workplaces of the Future?”, asks the harder question: whether the paradigm the industry is designing towards is even the right one. This piece is the follow-on: I think the data to inform a decision like that already exists, sitting inside a platform most real-estate teams have never thought to treat as a design instrument.

The Insights² robot studying a glowing holographic floor plan of an office building.
Designed from signal, not instinct.

The stakes: locked in for a decade, either way

None of us has a crystal ball on exactly how AI will redefine the human-to-machine interface. Nobody needs one to know that it will change how we work. That is exactly why it matters now: offices being designed today have to get the workplace of the future right, because that is the only way the capital being committed gets spent once instead of twice.

Whatever the industry eventually decides about the shape of the AI-era office, more enclosure or less, it will not be a decision anyone gets to revisit next quarter. That is worth establishing before anything else.

Property is a slowly changing dimension

For the data people reading this, I mean that precisely. Property is a Slowly Changing Dimension, Type 2. It does not update in place. It changes state by adding a new row: a new lease, a new fit-out, a new floor plan, and the old row stays valid for years after it was written. You live with what you signed.

A commercial building is typically committed on a lease of seven to ten years, and that number is not really a real estate habit, it is an accounting one. Fit-out costs get capitalised as leasehold improvements and amortised over the shorter of their useful life, commonly assumed at around a decade, or the remaining lease term, under both IFRS 16 and US GAAP. Exit early and you write off whatever is left unamortised as an immediate loss, so finance sets the floor on the lock-in before real estate even opens the brief. I have seen it across every organisation I have worked in, and it holds the same way across most large ones.

The space is then fitted out on a five to ten year cycle and designed against a standard someone wrote for the way people worked when the brief was set. Hold that against the clock the technology runs on: the interface shift we are living through is measured in quarters. What we draw on the plans this year commits us to a way of working in 2035, based on assumptions from 2024. The two clocks are wildly out of sync, and property is the slow one. Get it wrong and you do not patch it next sprint. You carry it for a decade.

I made the case for what I think that decision should actually weigh in Part 1: that voice-first, human-plus-agent collaboration is more likely to need more enclosed space than less, backed with real evidence rather than just conviction. Whichever way that argument lands for you, it depends on data that mostly does not exist yet inside a typical real-estate team. This piece is about where that data already sits, hiding in plain sight.

The strategic bet

Here is my strategic bet: Microsoft Places, or more precisely, the stack Microsoft has assembled around it. Not a product endorsement so much as a data thesis, one I want to state precisely, because the imprecise version does not survive scrutiny. It is my opinion, not a settled fact, but it is the clearest answer I have found to where the evidence for getting this design right already sits.

The point-solution problem

Plenty of large design and real-estate firms already sell some version of this. The more advanced ones use “data-informed design” as a genuine draw, and for firms with real reach, curated data across a meaningful share of the world’s workplaces, that draw is not empty. But ask the obvious follow-up: what data are they actually using to inform that design? Most of what is on offer is a point solution built on an old promise: hand over your data, and an outside platform will find the magic in it.

That promise keeps running into the same wall. Large organisations are in no position to hand all of their data to an external vendor, and the direction of travel is making that harder, not easier: as governance gets applied to AI specifically, sharing data with an external AI system is going to get stricter, not looser. A model built on pooling everyone’s data with an outside platform is fighting that current, not riding it.

Microsoft does not have that problem, and not because its data is better. It is because Microsoft is usually already inside the building. Most large organisations have already put Microsoft through years of IT and CISO scrutiny just to run Outlook and Teams. Extending an already-vetted vendor into workplace design data is a far smaller ask than clearing that same bar for a brand-new platform. The barrier here was never really the data. It is the trust, and Microsoft already spent it.

How people work

Microsoft’s own mission is to empower every person and organisation on the planet to achieve more, and Microsoft Graph is the infrastructure that mission actually runs on: to make an organisation more productive, Microsoft first has to understand how it works. That is how Microsoft ended up owning the richest behavioural signal of that in existence: Graph, the model underneath Microsoft 365, mapping meetings, documents, collaboration, and the flow of work across an organisation. This is not speculative. Microsoft already markets Graph as a source of workplace insight, down to analysing meeting requests to understand conference-room utilisation. On this specific axis, the depth of the organisational-collaboration graph itself, nobody else is close: no space-analytics vendor holds anything approaching it, though that settles this question, not the wider one.

Where people work

In November 2024 Microsoft brought Microsoft Places to general availability: a workplace app that layers occupancy and utilisation data, interactive floor plans, and portfolio-level space insight on top of that same Microsoft 365 fabric. But Microsoft did not build that spatial layer natively, and it is worth being precise about that, because it changes what the thesis actually is. It partnered the spatial layer in. Archilogic markets itself as Microsoft’s official global mapping integrator for the product, and for what it’s worth, I like what they’re building; Mappedin and Pointr convert floor plans into Places-ready maps at similar scale. VergeSense feeds occupancy sensing and predictive space planning straight into the floor plans customers already manage inside Places, no separate onboarding required.

Licensing changed too, and it is worth calling out because it changes how big the addressable footprint actually is. Until 1 April 2026, most of what makes Places useful sat behind Teams Premium, a per-user add-on priced around £7.70 a month, so adoption was gated by how many seats an organisation chose to license. From 1 April 2026, the core of Places, work schedules, colleague availability, the Places card, hybrid RSVP, is bundled into standard Microsoft 365 licences at no extra cost, and the advanced layer, desk booking, check-in, utilisation analytics, moves to a new per-space licence, Teams Shared Space, a rename of the earlier Teams Shared Device licence, priced at $8 for every four desks, against the desks and rooms being managed rather than the people using them. Microsoft’s own framing is that desks, not users, are the scarce resource in a downsized hybrid estate. Whatever the motivation, the effect is structural: Places stopped being an opt-in add-on for whichever seats a company chose to pay for, and became close to the default state of a Microsoft 365 tenant. The addressable footprint just went from however many Teams Premium seats an organisation had bought to essentially every Microsoft 365 tenant there is.

Why not a specialist, or build it yourself?

The honest answer is that a specialist vendor can beat Microsoft on spatial precision. Archilogic’s floor-plan intelligence and VergeSense’s occupancy sensing are both genuinely strong products, sold to anyone, Places customer or not. VergeSense goes further and does its own version of behavioural fusion, cross-referencing calendar data against its own occupancy sensors to catch no-shows and ghosted bookings. If the question were purely “who has the best geometry and the best sensor data,” a specialist stack might win.

But that is not the question that matters for design decisions locked in for a decade. The organisational-collaboration depth only exists inside Graph, and building it yourself means re-implementing what these vendors already sell, plus carrying the hardware, integration, and data-science headcount to do it, without ever reaching Graph’s view of actual collaborative work. Worth noting too: the most credible challenger in this space is not competing with Places, VergeSense spent 2024 to 2026 plugging deeper into it instead. That could just be normal go-to-market, integrating with the dominant platform is what any enterprise vendor would do. But it is at least consistent with where the leverage sits, not evidence against it.

The join

Put the two together and the picture is still striking, just not for the reason I first reached for. Microsoft says as much itself: its own Places roadmap material describes spatial data and location context as now “an integral part of the Microsoft 365 Graph & Copilot,” sitting alongside the messages, meetings, files and tasks Graph already tracks. This is not Microsoft uniquely sitting on a data mine nobody else can touch. It is Microsoft being the only party assembling the full stack: genuine collaboration-behaviour depth it owns outright, a best-of-breed spatial layer bought in through partnership, and the productivity-suite seat penetration to make the combination the default rather than an integration project. The mapping partners feeding Places have digitised well over fifteen billion square feet of interior space between them, across their whole businesses, not a Places-only figure Microsoft has ever published, but real evidence of the scale they operate at. No architect, no REIT, no facilities team assembling its own stack has anything remotely like that combination.

Microsoft 365 alone counts more than 450 million paid commercial seats. Imagine even a fraction of those organisations eventually pointing their own floor plans at Places: the fifteen-billion-square-foot base the mapping partners already claim would look like a rounding error.

That is the data that could inform the design of the AI-era office. Not opinions about what a good office feels like. Signal.

The facilities layer

One more piece is worth flagging, because it closes the loop back to Part 1. Facilities ticketing is a named category on Microsoft’s own extensibility roadmap for Places, the kind of partner integration that would let a reported problem become a logged ticket through the Teams apps marketplace, without anyone leaving the tool they already use for everything else. Worth being precise about where this actually sits, though: Microsoft’s own roadmap material places facilities ticketing in the “future” column of its integration patterns, alongside visitor management and food-and-beverage, distinct from the spatial-data and presence-signal integrations that are already live inside Graph. It is a stated direction, not a shipped feature.

Where I think this goes next is my own extrapolation, not something Microsoft has said outright: Places becoming the front end for a far more mundane class of interaction. Not the facilities system itself, which stays in the back end, but the front door to it. You talk to the room, the way Part 1 argued we are all about to do far more of, and a broken thermostat or a stuck blind becomes a ticket without opening a separate app. That matters for two reasons: it keeps people inside the flow of work they are already in instead of adding another app to remember, and it is a small, concrete version of the exact shift Part 1 argued for, voice becoming how we handle the ordinary friction of a room, not just the meetings that happen inside it.

The catch, before someone else says it

Say the obvious risk out loud. The same join that could design a better building can just as easily run a worse one. Fuse how-you-work with where-you-are and you have a surveillance engine as readily as a design tool, and the criticism has already started: journalists have flagged the newer presence-tracking features as a return-to-office enforcement mechanism dressed as convenience. Microsoft’s current answer is that the feature is off by default for the tenant, though whether an individual gets a true opt-in or just an opt-out depends on how the admin configures it. But the signal it produces is person-level, and whether it is ever aggregated to the building rather than used to monitor individuals is a choice, not a technical guarantee. That distinction is exactly the one that matters.

Aggregate signal, used to design better places for people, is a gift. Per-person signal, used to monitor them, is a trap. Design leadership does not get to be neutral about which one it is building towards. If we are going to use this data to shape the workplaces we lock in for a decade, we have to insist, loudly, on the first and refuse the second.

The conclusion

Let me separate what I am sure of from what I am not.

I am sure the office is a slow, capital-locked asset, and that we are designing right now for a voice-first, human-plus-agent way of working that is arriving faster than the property cycle can absorb. I am sure that we are right-sizing our portfolios against the world that is leaving and not the one that is coming. And I am sure the data to do this properly largely already exists, sitting in a stack most real-estate teams have never thought to treat as a design instrument.

What I am less sure of is the answer itself. Whether the future floor needs more enclosure, different ratios, a reversal of the densification of the last ten years. I have strong instincts, but instincts are exactly what this decision cannot run on, which is the whole point of this piece.

The real work is unglamorous, and it comes back to who is actually looking at this, and how. Leadership that owns the question, not delegates it to whoever happens to hold the AI brief. Standards rewritten for how people are actually going to work. And data, used honestly rather than exploited quietly, to inform decisions we only get to make once a decade.

The clock is already running. We design today, build tomorrow, and live with it for a decade, whether or not anyone used the evidence at the only point it could have mattered. The only real question is which version of that sequence we choose: deliberate, with the evidence that already exists, or found out the hard way, three years after occupation, retrofitting what should have been right the first time.

I want to connect with people already working through this: not the theory, the practical implications of how these spaces get redesigned and operationalised. If that is you, reach out.

Frequently Asked Questions

What does data-informed workplace design mean in the AI era?

It means making space decisions, how much, what type, where, on evidence of how work actually happens, rather than on instinct, last cycle's benchmark, or an architect's brief written for a world that has since moved on. The AI era raises the stakes because the way people work is changing faster than the property cycle that has to house it.

Why is corporate real estate not ready for the AI era?

Because property is locked in for a decade or more, both by the lease itself and by how fit-out capital is amortised under lease accounting rules such as IFRS 16 and ASC 842, and today's design standards were written for how people worked when the brief was set: typing, occasional calls, human-to-human collaboration. The technology interface is shifting in quarters, not decades. Almost no design standard, space metric, or planning principle has been rewritten to account for a voice-first, human-plus-agent way of working.

What is Microsoft Places, and why does it matter for workplace design?

Microsoft Places is Microsoft's workplace app, generally available since November 2024, that layers occupancy and utilisation data, interactive floor plans, and portfolio-level space insight on top of Microsoft 365. Microsoft did not build that spatial layer natively: it partnered it in, through vendors like Archilogic for floor-plan mapping and VergeSense for occupancy sensing. What Microsoft does own outright is Microsoft Graph, the organisational-collaboration signal of how people actually work together. My argument is that the combination, genuine behavioural depth plus a best-of-breed spatial layer assembled through partnership, is currently a stronger data foundation than any single specialist vendor offers on its own, though nobody has yet shown this pipeline driving a real capital or design decision, so treat it as the strongest current bet, not a proven track record.

What does it mean to say property is a Slowly Changing Dimension?

It is a data-modelling term applied to the built environment. A Slowly Changing Dimension, Type 2, does not update in place: it changes state by adding a new row, a new lease, a new fit-out, and the old row stays valid for years after it was written. Property behaves the same way. What gets designed and signed this year is locked in for a decade, which is why getting the AI-era brief wrong is expensive in a way a software mistake is not.

Does using workplace data like this create a surveillance risk?

Yes, and it is worth naming directly. Fusing behavioural signal, how people work, with geospatial signal, where they are, can build a better workplace or run a more intrusive one, depending entirely on how it is used. The distinction that matters is aggregate versus person-level: signal used to design better places for everyone is a legitimate design instrument, signal used to monitor named individuals is not, and design leadership has to be explicit about which one it is building towards.

Notes

Mark Cunningham is the founder of Insights². He has spent more than a decade building data and analytics products at the intersection of data and corporate real estate. He writes at insights-2.com about how to make the meaningful measurable.