What Do Digital Twins Hold for 2026: From Visualisation to Smart Building Operations

As digital twins move from experimentation into everyday building operations, 2026 is shaping up to be a pivotal year for the sector. To explore what’s genuinely changing and what remains more hype than reality, we sat down with one of the Directors at Twinview, Neil Hancock, for a fascinating conversation on the future of digital twins and smart building operations.

This interview captures an honest, practical discussion on where adoption is really happening, what operators actually need from digital twins and how the market is maturing.

Q: Digital twins are moving from hype to real investment. Which sectors will translate that growth into true operational adoption in 2026 and what will separate the leaders from the followers?

NH: I think in 2026 we’ll see the strongest operational adoption in sectors where buildings are either mission-critical or operationally complex.  Think sectors such as higher education, healthcare, social housing or large CRE portfolios.

These environments have all the drivers in play, such as ageing estates, constrained budgets, regulatory pressure, high occupant expectations and a strong need for performance transparency.

What separates leaders from followers won’t be who has the best 3D model or the most sensors; it will be who makes digital twins useful to the people running the building.

You'll find leaders will treat a digital twin as an operational layer: integrating live systems, linking assets to workflows, supporting compliance and delivering measurable outcomes, rather than seeing it as just another innovative tool.

And at Twinview, we’ve seen adoption accelerate fastest when the digital twin is directly aligned with operational teams and designed around the actions those teams need to take, not just the data they could theoretically see.

Q: In 2026, what will matter more: AI intelligence layered on top of a digital twin or real-time integration with live building systems, and what will that change in practice for operators?

NH: I’m going to be slightly controversial here, but I think the industry is getting distracted.

Everyone wants to jump straight to AI, because it’s exciting and it sounds like a shortcut. But in reality, AI is only as good as the data you feed it. And in building operations, most organisations still don’t have clean, reliable and connected data.

So, before we even talk about “AI-powered digital twins”, we need to be honest about where the market is: a lot of estates teams don’t have normalised asset data, consistent naming, integrated systems or even a trusted single view of what’s happening across the building. You’ve got data sitting in the BMS, in spreadsheets, in CAFM, in energy portals and half of it doesn’t line up.

And that’s the problem. Because building AI isn’t like generic AI. It needs to be building specific. The quality of insight you can get from AI correlates directly with the quality and structure of your building data and if that foundation isn’t there, you’re basically just generating plausible-sounding answers.

You can’t expect AI to do magic or to “predict the lottery numbers” when the underlying data is fragmented and unreliable.

So, for me, 2026 needs to be the year we stop obsessing over AI outputs and start focusing on getting AI-ready: centralising the data, integrating systems, cleaning the asset structure and making sure the digital twin reflects the building’s real operational reality.

Because once you’ve done that, AI becomes genuinely powerful, not as a gimmick, but as a tool to prioritise issues, interpret trends, reduce noise and support operators in making better decisions faster.

And that’s very much the approach we take at Twinview. The real unlock is getting the operational layer right first then intelligence becomes meaningful.

Q: Many organisations are still stuck in pilot mode, with static models, limited live data and siloed systems. Why does the gap between digital twin theory and real-world implementation remain so large?

NH: Because the theory is seductive and the reality is messy.

A lot of digital twin programmes start with a vision that’s technology-led: create a “single source of truth”, build a model, layer in sensors, add dashboards and the value will follow.

But we know buildings don’t work like software. Data isn’t clean, systems aren’t integrated, asset registers aren’t reliable and it's rare the operational team has the time or desire to reshape processes around a new platform.

The gap also exists because many pilots optimise for proof of concept rather than proof of value. They look impressive but aren’t embedded into everyday operations. If it doesn’t connect to real workflows, such as work orders, compliance tasks, daily checks, it won’t scale beyond a demo.

The successful deployments we see are the opposite: start with operational problems, design the digital twin around the processes, then integrate the right data sources.

That’s why Twinview positions itself around Smart Building Operations first, because adoption happens when the platform becomes part of how the building is actually managed.

Q: Looking into 2026, which emerging digital twin capabilities will deliver meaningful business impact in the next 12–18 months and which do you think are more hype than reality?

NH: Yeah, it’s a good question, because there’s definitely still a lot of noise in the space.

If I look at what’s actually going to deliver value in the next 12 to 18 months, it’s not the flashy stuff. It’s the practical capabilities that help operators run buildings better day to day.

So things like, digital twins that connect directly to existing workflows. So, not just “here’s the dashboard”, but “here’s the issue, here’s the asset, here’s what we’re doing about it, and here’s the work order.” That’s where the value really lands.

I also think we’ll see big impact from smarter fault detection and prioritisation.  SO again, not just identifying faults, but helping teams understand the wider context to be able to make more informed decisions. Because if you’re managing a portfolio, the challenge isn’t a lack of data, it’s deciding what to focus on.

And then there’s asset optimisation, things like improving data completeness, context and consistency across a portfolio. It sounds boring, but it’s basically the foundation for everything else.

Where I think the hype still exists is around the more extreme promises, like fully autonomous buildings or digital twins that can predict everything without proper data foundations. It’s not that those things won’t happen eventually; it’s just they’re not happening at scale in 2026.

At Twinview, the lens we apply is always: Does this capability reduce friction in operations? Does it make building ops teams work faster, work more confidently, or work more proactively? If it doesn’t, it tends to remain a nice-to-have.

Q: What does a ‘good’ digital twin look like in 2026 and what should building owners and FM teams expect it to do day-to-day?

NH: Honestly, the simplest way I’d describe it is, a good digital twin in 2026 should feel less like a model and more like an operating layer.

If you’re a building owner or an estates team, day-to-day, you should be able to open it and immediately answer questions like: what’s not working, what’s wasting energy, what needs attention today and what’s going to become a problem next week.

And it shouldn’t take five systems and three spreadsheets to figure that out.

I think the biggest shift is this: we’re moving away from digital twins being seen as a “visualisation tool”, which is where the market started and towards digital twins being something operational teams actually rely on.

And when it’s working well, you see it in behaviour. People stop saying “that system over there” and they just go straight into the twin because it’s the fastest way to understand what’s happening and what action to take.

That’s what we focus on with Smart Building Operations, the digital twin isn’t the end goal. It’s the interface that makes the building understandable and manageable.

Q: As digital twins become business-critical, what governance, data standards and operating models will organisations need to put in place to scale safely?

NH: This is a really important question, because governance becomes a big deal as soon as digital twins move out of “pilot” phase and into “we rely on this” phase.

Because if it’s business-critical, you can’t treat it like an innovation project anymore.

The first thing organisations need is clear ownership. And I mean real ownership, not “IT owns the platform” and everyone else sort of uses it occasionally. It needs operational ownership across estates, FM, energy, and compliance, depending on the organisation.

Second is data structure and standards. That’s the unglamorous part, but it matters. Asset naming, hierarchies, metadata and consistent tagging.  If that stuff is messy, everything downstream becomes harder, especially once you start wanting to doing automation and AI-driven insight.

And then the third one is changing control and auditability. Because once you’re triggering actions based on data, you need to know: what changed, why it changed, what rule fired, who approved the process. That’s where organisations get nervous and rightly so.

So, for me, scaling safely is really about treating the digital twin as part of the operational management system, not as a standalone tech product.

Q: What do digital twin platforms need to prioritise over the next few years to become genuinely operational and how is Twinview responding to that shift?

NH: I think the whole market is being forced to grow up a bit, to be honest.

For a while, digital twins were judged on how impressive they looked, the interface, the 3D model, the concept. But now customers are asking: does this actually help my teams run buildings better?

So, platforms need to prioritise a few things.

One is deep integration, because if you’re not connected to the systems that run the building, you’re just a layer of reporting.

Another is usability for operational teams. Because the day-to-day users aren’t data scientists, they’re engineers, FM teams and helpdesk.  You also need to consider the building's everyday users and how they interact with data from the twin.

Then there’s automation. Not automation for the sake of it, but the ability to translate insight into action. And that’s where things like workflow integration and “twin-to-ticket” become fundamental.

And I’d also add: platforms need to be able to prove outcomes. Energy reduction. Less downtime. Faster response. Better compliance evidence. That’s how buyers will assess value going forward.

With Twinview, that’s exactly why we are repositioning around Smart Building Operations. The digital twin is still core, but we focus on it to operational improvement, not as a visual output. And we’re continuing to build out that operational layer, so it connects data, assets and workflows into one working environment.

The Takeaway

As digital twins become embedded in the day-to-day management of buildings, the focus is shifting away from visualisation and towards measurable operational outcomes. As Neil highlights throughout the conversation, the organisations seeing real value are those treating digital twins as an operational layer, connecting data, assets and workflows to support better decisions, faster responses and safer scaling.

For building owners, estates teams and FM leaders looking ahead to 2026, the message is clear: the future of digital twins isn’t about more technology, but about making building operations simpler, clearer and more effective.