.The Middle East’s built environment is undergoing a significant transformation as artificial intelligence (AI), Building Information Modelling (BIM), digital twins and other advanced technologies become increasingly integrated into the real estate lifecycle. From optimising construction schedules to improving building performance and enabling more informed investment decisions, these tools are changing not only how projects are delivered, but also how assets are operated and maintained over time.

For JLL, one of the most important developments is the ability to make better-informed decisions earlier in the process, when changes can be made more easily and their implications assessed before significant capital is committed.

“The biggest change is when decisions get made. In planning and design, AI lets teams test many layouts and servicing strategies against cost, carbon and operational criteria before a client commits capital,” says Dr. Matthew Marson, Managing Director, EMEA & APAC – Technology Consulting at JLL.

The impact is particularly tangible during construction, where project teams must coordinate multiple work packages, resources and suppliers while responding to changing conditions. Marson points to ALICE Technologies, a company in JLL Spark’s venture portfolio, which uses AI to generate and compare alternative construction sequences from the same project data.

“It varies skills, equipment, phasing and methods to find the plan that best balances time, cost and risk,” he explains. “A planner traditionally builds one schedule and then defends it. With ALICE, the team can test what happens if a second tower crane arrives, a delivery slips or a zone opens early, before committing to a plan.”

This ability to test different scenarios enables teams to assess the implications of potential disruptions before they occur. When site conditions change, schedules can be re-optimised rather than rebuilt from scratch. On complex projects with numerous packages running in parallel, this means risk becomes something teams can plan around instead of simply reacting to, he says.

Rachael Jones, Head of Specialist Services, KSA – Project & Development Services at JLL, highlights a practical example from a giga-project in which JLL is involved.

“When a key supplier reported a multi-week shipping delay for specialised components, the project team input the new timeline constraint into the AI platform, which processed the downstream impacts and generated an optimised revised schedule within hours,” she explains.

“The system re-sequenced tasks, adjusted resource allocations, and updated supply chain schedules to minimise disruption – enabling the team to maintain project momentum through a fast, data-driven response,” Jones adds.

While BIM has been widely adopted across design and construction, its potential to support building operations remains underexploited. Models are often developed to coordinate the construction process, only for much of their value to be lost when an asset is handed over to its operator.

“BIM was built to coordinate design and construction, and on most projects its value ends there. The model is handed over, the operator receives files they never asked for, and the building is run from spreadsheets,” says Marson.

JLL’s focus, he explains, is on closing that gap by defining operational requirements before design begins. These may include asset registers, maintenance requirements, spatial data and other information needed to manage the building effectively.

“The model is then built for operations rather than adapted to them later, with more cost,” he says.

When BIM data is connected to live feeds from building management systems, IoT sensors and work order histories, AI can analyse building performance and identify opportunities for intervention.

“It can spot equipment drifting out of performance, link a comfort complaint to a specific plant item, or forecast which assets are likely to fail first. The model becomes the spatial index that gives operational data its context. Without that structure, AI is guessing. With it, facilities teams can act on evidence,” Marson explains.

The approach is particularly relevant to the Middle East, where the scale of new developments creates opportunities to embed digital infrastructure and consistent data standards from the outset.

Technologies shaping the next decade

Beyond BIM and AI, Marson identifies digital twins, robotics, automation and computer vision as technologies likely to have a substantial impact on the region’s built environment over the next 5 to 10 years.

“Three stand out,” he says. “The first is digital twins, used as operational tools that combine live building data with a structured model of the asset rather than as 3D visualisations.”

With entire districts and cities being developed across the region, he believes there is a rare opportunity to establish the right data architecture from day one. “The region is building whole districts and cities from scratch. That is a rare chance to design the data architecture in from day one instead of trying to fix it later. Combine it with processes and you’ve got a city-wide operating system,” he explains.

The second major opportunity is robotics and automation in building operations. Cleaning, security, inspection and logistics remain labour-intensive activities across large estates, and greater automation could improve efficiency and consistency.

“Buildings will increasingly need to be designed for robots as well as people, from lift integration to floor finishes and connectivity,” Marson says.

Computer vision is the third area he highlights, particularly its potential to turn existing cameras into sensors for occupancy, site safety and asset condition. IoT will underpin many of these applications, but Marson stresses that interoperability will be just as important as the technologies themselves.

“The technology that will matter most, though, is the least glamorous –  common data standards will let these systems talk to each other,” he says.

Jones agrees that connected information is becoming increasingly important as projects grow more complex and delivery pressures intensify.

“While the industry increasingly recognises the importance of becoming more data-driven and connected, levels of data maturity still vary across organisations and projects,” she says.

This creates challenges when information is spread across different systems, teams and supply chains. In an environment characterised by supply chain disruption, cost volatility and programme pressures, the ability to access reliable information and respond quickly can make a significant difference.

“As projects become more complex and interconnected, the focus is shifting from simply collecting data to creating reliable, standardised and connected information that enables better coordination, stronger forecasting and more informed decision-making across the full asset lifecycle,” Jones explains.

Better decisions from the outset

AI and advanced modelling can also help clients evaluate development options earlier, when design decisions have the greatest influence on cost, programme and
long-term performance.

“The cost of changing a decision rises sharply as a project progresses. Yet the information needed to make good decisions has traditionally arrived late. AI and parametric modelling reverse that,” Marson says.

At concept stage, teams can test options against capital cost, programme, energy performance and operating cost simultaneously, rather than optimising one variable and discovering the consequences for others later.

“A façade choice, for example, can be assessed for its effect on cooling loads, maintenance access and replacement cycles before it is drawn in detail,” he explains.

This is especially important in the Gulf, where cooling requirements have a significant influence on operational costs and carbon emissions. The emphasis must therefore extend beyond construction expenditure to the long-term cost of owning and operating an asset.

“For clients, the question shifts from ‘what will this cost to build?’ to ‘what will this cost to own over its life?’” Marson says. “Whole-life asset value is largely decided by a few early choices. Modelling makes those choices visible, comparable and defensible to decision makers.”

Digital twins offer another opportunity to connect design and construction information with the operational phase, but Marson believes their success depends on whether they answer practical questions for building owners and operators.

“The greatest practical value is in operations, where most of a building’s lifetime cost sits,” he says.

A useful twin answers operational questions. Which assets are underperforming? What will a failure affect? How is space actually being used? What will a change in operating strategy do to energy and comfort?”

The value diminishes, however, when digital twins are developed primarily as visual showcases without being connected to live building systems.

“On readiness, the Middle East is ahead of most regions in ambition but further from routine use than many expect. Many flagship developments include digital twins in their brief. The constraint is rarely the technology. It is information requirements that aren’t defined early, handover data that arrives incomplete, and operators who weren’t involved in specifying what they need,” Marson explains.

To move from isolated implementations to routine use, digital twins must be embedded in project requirements, supported by complete handover information and assigned to an accountable business owner.

“Routine use will come when twins are written into contracts as an operational requirement with a named business owner, rather than a bonus, ‘digital extra’,” he adds.

Managing complexity through collaboration

The scale and pace of development across the Middle East make coordination between owners, consultants, contractors, operators and other stakeholders increasingly important.

“Speed and complexity make a familiar problem worse … too many parties working from different versions of the truth,” Marson states.

He believes a common data environment, supported by clear rules governing information ownership, approval and exchange, is essential. Integrated dashboards can provide owners with a consolidated view of cost, programme and risk, while AI can analyse large volumes of project correspondence and change requests to identify emerging problems.

Bringing operators into the design process is equally important, helping teams avoid costly changes when operational requirements are only recognised at handover.

“The most effective tool needs to go beyond just a single piece of software. A common data environment with clear rules about who owns which information, when it is approved and how it flows between parties is key to project success,” shares Marson.

The challenge extends across the entire asset lifecycle. Design information does not always reflect what was built, construction records may arrive in formats operators cannot use, and systems from different vendors often require bespoke integration.

“The industry’s data problem is less about volume and more about continuity,” he states.

Although standards such as ISO 19650, the open IFC model format and Brick for building systems data provide a foundation, adoption remains uneven. Marson believes information management must be treated as a means of creating value rather than simply satisfying compliance requirements.

“The underlying issue is ownership,” mentions Marson. “Data quality improves when someone is accountable for it across the whole lifecycle, and when contracts specify information requirements as clearly as they specify materials.”

For all the potential benefits, adopting technology does not automatically deliver improved productivity or financial returns. Marson argues that organisations must first establish the business outcomes they want to achieve and how these will be measured.

“A gap usually exists because technology is bought as a product rather than introduced as a change to how work is done,” he says.

JLL’s approach begins by identifying the decision, cost or risk that a technology is expected to change, establishing a baseline and assigning responsibility for measuring the result.

“We track a small set of operational measures and link them to financial outcomes the client already recognises,” Marson says.

These include the ratio of reactive to planned maintenance, energy intensity, time spent on reporting and space utilisation. The clearest measurable benefits are currently emerging in building operations, particularly through energy optimisation, predictive maintenance and the automation of reporting and document review.

“Benefits in design and delivery are real but harder to isolate, because a problem avoided has been successfully avoided and you can’t prove what didn’t happen,” he comments.

Evolving skills and the intelligent asset

As AI takes over more routine analysis and administrative tasks, professional roles across the built environment will increasingly focus on judgement, interpretation and decision-making.

“Automation will take over much of the work professionals least enjoy, compiling reports, checking documents and reconciling data from different systems,” Marson says. “What remains is the work that needs judgement, which is where their value lies.”

Architects and engineers will spend more time evaluating options, project managers will be able to act earlier on emerging risks, and facilities teams will need to manage building systems and data alongside contractors. Real estate professionals will increasingly use portfolio information to inform investment decisions.

“The new skill all of these roles need is data literacy – knowing what good data looks like and where AI can and can’t be relied on,” he explains.

Looking towards 2030, Marson anticipates buildings with digital services will be accessed through conversational interfaces and connected devices help systems respond more intuitively to occupants’ needs.

“The intelligent buildings of 2030 will have captured the advantages they afford to owners, operators and occupants by building on industry expected devices, connectivity, applications and governance procedures,” he states.

He expects mobile applications to evolve towards text- and voice-based interaction, while connected devices such as watches, phones and rings could help link people’s needs with their location. As AI becomes better at interpreting information and context, the distinction between a conventional building and an intelligent one may eventually disappear.

“In fact, we’ll stop calling them intelligent buildings as we expect their capability as standard,” he says.

The Middle East has the ambition and investment to lead this transition, but achieving it will require more than adopting the latest technologies. Consistent data standards, reliable information, clear governance and investment in professional skills will be essential to ensuring that digital innovation translates into measurable value.

“The Middle East has the ambition and the investment to set the pace. The technology is ready, and the industry’s habits need to catch up,” Marson concludes.

.

.

.