REAL ESTATE

REAL ESTATE

© prah / Adobe Stock


WHAT ARE THE KEY TAKEAWAYS?

  • Real estate innovation in 2026 will centre on better, earlier decision‑making, with stakeholders shifting from static reports to actionable, financially‑linked, engineering‑grade insights that guide capital allocation and decarbonisation
  • Performance verification, large‑scale retrofit, operational digital twins, and climate‑resilient design will dominate as owners and investors focus on closing the design‑to‑operation gap and managing whole‑life performance
  • Emerging tools including AI‑driven clean‑energy assessment, ultra‑precise occupancy analytics, and engineering‑grade climate‑risk simulations will help owners optimise operations, target retrofits, and manage growing regulatory and physical‑risk pressures

© prah / Adobe Stock

What are the experts saying?

About Optimi

Optiml is a real estate decision intelligence company defining a new category for how institutional real estate decisions are made. Launched just 1.5 years ago, the platform is already used by leading owners, asset managers, and investors across Europe, the UK, and North America, including firms such as PATRIZIA, Catella, CTP, Empira, Longevity Partners, Telesto Strategy, Westbridge/agradblue, and pom+. Optiml has also emerged as the most awarded innovation in its space, with recognitions including the ULI Europe PropTech Innovation Challenge, the ZIA PropTech of the Year Award, and multiple leading industry awards. By moving the industry from backward-looking reporting to forward-looking, decision-grade intelligence, Optiml addresses the sector’s most pressing challenge: how to allocate capital, decarbonise portfolios, protect value, and increase internal rate of return (IRR) under regulatory, financial, and climate uncertainty.


Nico Dehnert, Co-Founder and CCO, Optimi

What themes will be important in sustainable real estate innovation in 2026?

By 2026, sustainable real estate innovation will be defined less by new metrics and more by who has the authority to make better decisions, earlier. Across owners, investors, consultants, and lenders, six shifts are becoming decisive.

First, the industry will move from systems of record to systems of action. Backward-looking reports and PDFs will give way to forward-looking decision environments that test scenarios, trade-offs, and consequences before capital is committed.

Second, ESG will fully transition from compliance obligation to value driver. Decarbonisation will no longer be treated as a parallel reporting exercise, but as a lever influencing IRR, refinancing risk, exit value, and portfolio resilience. Sustainability strategies that cannot be linked to financial outcomes will lose relevance.

Third, innovation will move from benchmarks and estimates to financial- and engineering-grade decisions. Investors, banks, and regulators will increasingly require evidence that transition plans are bankable, auditable, and grounded in physical reality – not averages or proxies.

Fourth, the industry will shift from static reporting to radical transparency and shared data environments. Data silos between owners, asset managers, consultants, and lenders will erode as collaboration becomes necessary to execute complex, multi-year transition strategies.

Fifth, the focus will move from decision transparency to decision authority. It will no longer be enough to “show the numbers”; leading organisations will be those that can act on them with confidence, governance, and accountability.

Finally, value creation will increasingly come from operational alpha rather than financial leverage. As leverage-driven returns compress, competitive advantage will be created through better capital allocation, smarter retrofit sequencing, and superior execution across portfolios.

In short, sustainable real estate innovation in 2026 will not be about more data – but about better decisions, made earlier, by the right stakeholders.

About IES

IES is a global climate-tech firm delivering software and consultancy to decarbonise the built environment. Over the past 30 years, it has built a strong reputation as a leading innovator in integrated, performance-based building analysis, and is home to the world’s largest building physics analytics team. IES supports energy-efficient, healthy, and cost-effective places by providing whole-lifecycle performance modelling for the design, retrofit, and operation of buildings – helping teams test scenarios, reduce risk, and make smarter, more sustainable decisions with confidence.


Laurie McKelvie, Technical Delivery Lead, IES

What themes will be important in sustainable real estate innovation in 2026?

In 2026, sustainable real estate innovation will be about verifying and optimising performance – proving, in operation, that buildings are delivering the energy, carbon, and comfort outcomes promised at design stage. The performance gap between building design and operation remains one of the sector’s biggest blind spots, but regulatory and public scrutiny is only on the up. With this in mind, expect more owners, investors, and occupiers to prioritise whole-life performance – from modelling and scenario testing, through to post-occupancy evaluation and ongoing measurement and verification.

First, retrofit at scale will dominate the innovation agenda. With around 80 per cent of the buildings that will exist in 2050 already standing, asset strategies must increasingly focus on upgrading what we have – intelligently, and with minimal disruption – rather than relying on new-builds to hit net zero plans.

Second, operational digital twins of buildings will move from ‘nice to have’ to practical decision-making tools. The most useful approaches combine physics-based simulation with real operational data, so teams can identify what’s driving energy use, test interventions before spending, and then track whether savings actually show up on the meter. Through projects like our collaboration with The University of Liverpool, we’re already seeing how live, calibrated models can support meaningful reductions in energy use and running costs when paired with targeted operational and retrofit measures.

Third, climate resilience and occupant experience will continue to rise up the priority list. Buildings must cope with more extreme and ever-evolving conditions while maintaining safe, productive, and comfortable internal environments – and that requires better modelling, better controls, and better feedback loops.

Finally, none of this scales without improved data governance and handover. Real estate innovation in 2026 will be as much about standardising how performance data is created, shared, and maintained as it is about new technology – because you can’t improve what you can’t accurately measure.

Three Innovations to keep an eye on

INNOVATION ONE:

Can AI streamline clean energy adoption in commercial real estate?

© allvision / Adobe Stock

US startup Station A has developed software that helps owners of commercial and industrial buildings adopt clean energy solutions.

The platform makes it easier for property owners and managers to evaluate their entire building portfolio at scale, using AI and geospatial analysis to provide environmental and financial insights and sustainability report cards across hundreds or thousands of buildings simultaneously. Armed with just an address list, the platform analyses and grades each building in a portfolio to identify the best sites for solar, battery, and EV charging installations.

The company also offers a marketplace that connects qualified buyers with vetted clean energy providers, streamlining the procurement process from initial evaluation to project completion. The marketplace facilitates transactions by allowing providers to bid on projects, explore market trends, and connect with qualified buyers, while giving property owners access to a curated network of trusted installers.

Station A has already worked with major real estate portfolio owners including Goldman Sachs, Nestlé, Walmart, and Wayfair.


INNOVATION TWO:

Can we make occupancy management ultra-precise?

Open-plan offices are now the dominant workplace layout, yet designers and facility managers still lack reliable data on how these spaces are actually used. Most occupancy systems only measure large-scale activity, missing the fine-grained patterns that shape a successful office environment.

In response, researchers at the University of Osaka have developed an AI framework that measures occupancy at the level of individual functional zones within open offices, offering a more precise basis for evidence-based workplace design.

The system uses existing cameras and computer vision to track people’s positions through multi-view, multi-person 3D pose estimation. Rather than simply counting occupants, it identifies whether individuals are present within predefined micro-zones such as desks, circulation areas, or shared workspaces.

During prototype trials, the model achieved 100 per cent precision and an F1 score (a metric to measure machine learning accuracy) of around 89 per cent.”

© wakhid saiful anam / Adobe Stock

By aggregating this information over time, the framework reveals detailed patterns of use, including how long zones are occupied, how frequently they are used, and how activity shifts throughout the day. During prototype trials, the model achieved 100 per cent precision and an F1 score (a metric to measure machine learning accuracy) of around 89 per cent.

Conventional measurement approaches often focus only on large areas of space, and depend on dedicated sensors, wearable devices, or constrained user behaviour, which limits their practicality in real offices. By contrast, the Osaka team’s framework operates passively using standard cameras to monitor smaller zones, without requiring staff to change how they work.

INNOVATION THREE:

Can simulations help us to quantify climate risks to property?

© jamesteohart / Adobe Stock

A growing number of organisations that operate, own, or invest in properties want to protect their people, assets, and businesses from catastrophic events, but are hampered by the lack of data and the cost of high-quality engineering assessments.

Class 3 Technologies has developed a proprietary simulation engine that delivers engineering-grade risk assessment and evaluations of resilience strategies. Spun out of the global engineering and built environment consultancy Arup, Class 3’s Iris platform combines up-to-date hazard data with detailed engineering models to simulate how climate extremes will impact buildings.

The Iris platform can quantify the probability and severity of climate-related damage and translate this into the risk of financial loss, downtime, and occupant health and safety. The platform can also map hazard intensity to each building or building component.

Traditional property risk platforms tend to rely on high-level projections or insurance-based loss averages. Iris, by contrast, models risk based on engineering methodologies, helping decision-makers with risk assessments, site selection, and construction decisions. Iris is already being used by tech companies, investors, developers, real estate owners, insurers, and more.