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How sustainable materials and AI are shaping NEOM, Masdar City, and Dubai’s new developments

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The Dubai Beach EDITION Hotel and Residences at Dubai Harbour by Shamal Holdings



NEOM, Masdar City and Dubai, cities that have long been a symbol of wealth and ambition, are not just building new skylines, they’re attempting to redefine what a city can be. With construction sector being one of the largest contributors to global emission, Middle East, flush with capital, ambitious projects, and new masterplans is testing a simple hypothesis: Can the region radically lower the carbon and resource footprint of entire cities through sustainable materials and Artificial Intelligence (AI)?

Dr. Vahid Razaviarani, Global Programme Director,
MSc Global Sustainability Engineering
Heriot-Watt University

Governments and developers, in the Gulf, are shifting policies and procurement practices toward low-embodied-carbon alternatives: recycled aggregates, low-carbon concrete, engineered timber, high-performance insulation and off-site modular systems that dramatically cut waste. According to Grand View Research, in 2024, the global green building materials market was estimated to be worth hundreds of billions of dollars, and it is forecast to grow. Moreover, the GCC green building materials market alone reached an estimated USD 10.6 billion in 2024 and, according to an IMARC Group report, is expected to grow significantly as demand for sustainable inputs scales up.

NEOM’s energy and utilities arm, Enowa, explicitly emphasises circular systems and positions the project as a 100%renewables-powered ecosystem that integrates water, energy and industrial systems from the outset. It combines Industry 4.0 technologies with circular economy principles that force the choice of materials toward those that can be reused or easily recycled, while promoting off-site fabrication techniques that shrink construction waste.

For more than a decade, Masdar City has been offering a working prototype of what happens when sustainable material choices meet a systems approach, translating low-carbon urban design into practice. It pairs demonstrable clean energy capacity with district cooling systems, solar generation, and energy-efficient building envelopes with planning that reduces transport demand. Masdar’s broader organisation, its parent group, has also been scaling fast. Its report highlighted growth in clean energy capacity and an organisational push into integrated, low-carbon urban projects. The Masdar model is a reminder that reliable renewable supply makes higher-embodied, energy-intensive solutions (for example, electric construction equipment charged by renewables).

But materials alone won’t be enough, this is where AI becomes a multiplier. AI tools now enable topology optimisation for material efficiency, predict and prevent waste by logistics algorithms (supply chain forecasting, demand matching). In operations, machine learning drives HVAC optimisation (manage buildings in real time, predictive maintenance). For projects on the scale of NEOM or Masdar, with thousands of buildings, millions of square meters and complex infrastructure, AI systems can turn millions of data points into continuous efficiency gains.  NEOM and related initiatives are already integrating AI for water, energy and materials planning, while Oxagon’s industrial model assumes broad adoption of automation and AI in production.

Dubai’s trajectory shows how regulation and market amplify these technological shifts and incentives accelerate adoption. Municipal green building regulations, alongside certifications such as LEED and local green building systems, have driven a rapid uptake of sustainable construction practices, pushing developers to pursue energy-efficient envelopes, reduced water use, and green materials. According to Dubai Municipality, the city’s policy environment, paired with developers’ appetite for premium assets that offer lower operating costs and resilience to climate risk, creates an ecosystem where sustainable materials and smart building systems are not only environmentally desirable but financially sensible.

The Grand View Research estimates show the Gulf’s green-building sector and related materials markets expanding rapidly, with market valued in the mid-to-high tens of billions of dollars and forecast to double-digit compound annual growth rates in the coming five years. That inflow of capital matters because sustainable materials often carry higher up-front cost but deliver lower lifecycle costs, while AI and automation substantially reduce construction and lifecycle operating overruns. In other words, together they improve the return profile for long-term investors.

Yet ambition collides with practical constraints. Supply chains for low-embodied materials must scale quickly; while those in the region remain sensitive to cost, logistics, and local standards. Skilled labour in advanced assembly and data-science expertise to drive AI systems are limited and must be cultivated. Governance questions are also pressing: who owns the data generated by smart urban systems, how is privacy protected, and how do we ensure that AI allocates resources such as water, energy and mobility fairly. These are governance design problems, solvable, if tackled deliberately.

There are three pragmatic approaches for solving them. First, governments and project sponsors can accelerate local manufacturing of green materials through incentives and public-private partnerships. Second, procurement rules should favour lifecycle carbon and circularity over the lowest upfront price; that shifts incentives toward durable, reusable materials and off-site fabrication. Third, data-governance frameworks must be established from the outset: transparent rules about ownership and enable third-party innovation without commercial capture.

If NEOM, Masdar City and Dubai’s new districts can scale these approaches, the payoff will be tangible: lower lifecycle emissions, less construction waste, healthier indoor environments, and long-term savings for investors and taxpayers. The Middle East can move beyond being a market for imported technology to becoming a global crucible for sustainable urban practices, provided policymakers, developers and technologists align incentives and share data and best practices.

NEOM, Masdar and Dubai’s new districts are more than national statements; they are testbeds whose lessons could reshape how cities are built globally. If they get it right, prioritising lifecycle outcomes, scaling green materials, and embedding AI from design to operations, Middle East will be measured not only in square metres and skylines, but in the tonnes of embodied carbon avoided and the megabytes of intelligence that keep cities efficient and humane. The world will, for once, be watching not only to admire, but to learn.

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WHY EXCEPTIONS, NOT INVOICES, ARE COSTING FINANCE TEAMS THE MOST

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By Ionut Valentin Sas, SVP Finance, UiPath

Across the GCC, processing standard invoices has become relatively straightforward. Routine invoices are no longer the problem. The real bottleneck begins the moment an invoice falls outside the expected workflow, whether that is a mismatched PO, a missing approval, incorrect coding or a supplier query. From there, the process spills into email threads and spreadsheets, and finance teams pay for it in delayed cash flow, missed early payment discounts, strained supplier relationships and tied-up working capital. The invoice itself was never really the problem. The problem is what happens when it does not follow the usual pattern.

The Trouble with Exceptions

Straight-through processing, where an invoice moves from receipt to payment without human intervention, has been one of finance teams’ most effective ways to handle higher invoice volumes at lower cost. Companies like Canon have reported up to 90 percent STP for certain invoice types.

Yet according to Ardent Partners’ State of ePayables report, even top-performing AP teams only reach around a third. That gap reflects a shift already under way in accounts payable. As routine invoices increasingly process themselves, less time goes into verifying standard transactions, and more of the team’s effort shifts toward judgment, coordination and resolving what falls outside the pattern, such as invoices missing a PO, mismatched purchase orders, supplier follow-ups and approval bottlenecks.

Most automation was built for the predictable majority of transactions. The remaining cases still get routed back to people, with no system designed to resolve them faster or more consistently. Resolving an exception often means pulling information together from ERP systems, procurement platforms, contracts, past transactions and supplier communications before a decision can be made. The challenge is rarely a lack of information. It’s that the information sits across multiple systems and requires someone to piece it together before a decision can be made. That’s where most of the time is lost.

Invoicing in the UAE

The UAE’s move toward mandatory e-invoicing is one of the clearest signals of this shift. For many organisations, this transition will expose processes that have remained largely hidden while invoices were handled manually. Standardised, machine-readable invoices make routine processing easier, but they also shine a light on the exceptions that continue to require human intervention. As a result, organisations have an opportunity to redesign how those exceptions are managed, rather than simply digitising existing processes. The mandate requires structured, machine-readable invoices in place of the PDFs and spreadsheets many finance teams still rely on, and it is pushing organisations to take a hard look at how they handle exceptions today.

Compliance is only the starting point. The bigger opportunity is using this transition to modernise broader finance operations and rethink how exceptions get managed, not just to meet the regulatory deadline.

The Importance of Governance

As more of this resolution work shifts to AI agents, visibility, auditability and control become essential. Governance is not there to slow decisions down. It is what gives organisations the confidence to automate lower risk work while keeping higher risk decisions transparent, explainable and subject to human oversight. Done well, orchestration keeps people in charge of decisions, not just faster at processing them. That becomes increasingly important as finance teams automate larger parts of the invoice lifecycle. Confidence in AI comes not from removing people altogether, but from knowing when human judgement should remain part of the process.

The UAE’s e-invoicing mandate makes this need for governance harder to ignore. But governance should not be seen as a brake on AI adoption. It is what makes that adoption trustworthy.

The Shift Finance Leaders Must Make

The old mindset was to automate invoices. The new one is to resolve exceptions.

That is the shift finance leaders now need to make, treating exception management as the next frontier in finance automation rather than an afterthought bolted onto invoice processing. The foundation for that shift is orchestration, bringing people, systems and AI agents together around each exception instead of simply flagging it for someone to pick up later.

AI agents can do much of the groundwork before a person is even involved, gathering supporting information, analysing how similar cases were resolved in the past, recommending next steps and drafting supplier communications. That does not replace judgment. It means the judgment that does happen is faster and better informed. The organisations that gain the greatest advantage will not necessarily be those processing the highest number of invoices automatically. They will be those that can resolve exceptions quickly, consistently and with the right level of oversight, turning what has traditionally been a source of delay into a competitive advantage. The GCC built its reputation in digital government and public services by fixing what was not working, not by polishing what already was. Finance now has the same opportunity in front of it. The invoices were never the hard part. The exceptions are, and the organisations that get ahead of them will be the ones setting the pace for the next phase of digital invoicing in the region.

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Tech Features

THE BEAUTIFUL GAME, FOR EVERYONE: HOW TECHNOLOGY REWROTE THE RULES OF FOOTBALL FANDOM

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By: Jason Ou, President at Hisense MEA

As the FIFA World Cup 2026 final approaches this week, we reflect on a tournament that transformed how millions experienced the sport, from living room stadiums to quiet spaces in packed arenas

As we count down the final hours before this week’s showpiece final, the FIFA World Cup 2026 has delivered 103 matches across 16 cities, and with it, a reimagining of what “experiencing football” means.  Hisense served as the official and exclusive Video Assistant Referee (VAR) Review TV Provider for the entire tournament across the United States, Canada, and Mexico. Every controversial offside call. Every penalty review that had fans screaming at their screens. Every red card confirmation that shifted the momentum of a knockout match. The technology referees used to make those match-defining decisions ran on Hisense RGB MiniLED displays. The Video Operation Room in Zurich was upgraded specifically with these screens because VAR officials needed “clear and authentic restoration of live match footage.”

And it delivered.

Two parallel revolutions unfolded across this tournament: one that transformed homes into legitimate viewing destinations, and another that finally opened stadium doors to millions who’d been locked out for decades.

Hisense made an argument before kickoff: the home viewing experience could, in some ways, surpass what you’d get at the stadium itself. If the technology was precise enough for officiating decisions scrutinized by billions and debated across social media within seconds, it was good enough for living rooms worldwide.

For those who invested in the L9Q TriChroma Laser TV, everyday living spaces became premium match-day destinations throughout the tournament. With ultra-large displays up to 200 inches, fans followed every run, pass, tackle, and goal with remarkable clarity.

The flagship UXS RGB MiniLED TV, powered by breakthrough RGB MiniLED technology that delivers exceptional color accuracy, brightness, and contrast, brought fans closer to every moment on the pitch and created a more immersive and lifelike viewing experience for sports, entertainment, and gaming.

The Party Everyone Could Finally Join

For millions of fans living with autism, PTSD, dementia, anxiety, and other sensory processing conditions, the stadium experience had remained firmly out of reach, a party they could hear from outside but never truly join. This tournament changed that.

At this year’s tournament, all 16 host stadiums featured dedicated sensory rooms, making this the first-ever Sensory Inclusive FIFA World Cup. Hisense collaborated with FIFA and KultureCity to install these spaces across every venue in the United States, Canada, and Mexico, and they were used.

As Hisense continues pushing boundaries, making every match feel bigger, every celebration more immersive, and every memory more unforgettable, one truth has emerged from this tournament: the hierarchy of World Cup viewing has been expanded, making room for everyone who loves the beautiful game.

This week, as billions watch the final from living rooms with 300-inch screens and fans with sensory needs take their seats in the stadium, football’s promise will be fulfilled. The beautiful game. Finally, for everyone.

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HOW AI IS RESHAPING HIGHER EDUCATION, AND WHY UNIVERSITIES MUST REINVENT THEMSELVES

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By: Prof. May El Barachi, Dean & Full Professor, University of Wollongong in Dubai

Artificial intelligence is no longer a future technology. It has become part of our everyday lives almost overnight. Whether we are writing emails, analysing data, generating code, creating presentations, or conducting research, AI has fundamentally changed how knowledge is created and consumed.

For higher education, this represents one of the biggest disruptions since the arrival of the internet.

Much of today’s conversation revolves around a simple question: Will AI replace educators?

I believe we are asking the wrong question.

The real question is whether universities can reinvent themselves quickly enough to prepare graduates for an AI-first world.

Having worked extensively with generative AI technologies, I see AI not as a replacement for education, but as an extraordinary opportunity to redefine it. From One-Size-Fits-All Learning to Personalized Education.

Traditional education has largely been built around standardized delivery: one lecturer, one classroom, one pace, and one curriculum for every student.

AI changes that equation.

For the first time, every learner can potentially have access to an intelligent learning companion available 24 hours a day. AI tutors can explain difficult concepts, generate additional practice exercises, adapt explanations to different learning styles, provide immediate feedback, and support students until genuine understanding is achieved.

Instead of asking students to adapt to education, education can finally adapt to students. This has important implications for accessibility, allowing high-quality learning experiences to reach individuals regardless of geography or socioeconomic background.

In many ways, AI has the potential to become the great equalizer in education.

Teaching Students How to Think; Not What to Memorize

At the same time, AI forces universities to rethink their educational philosophy.

When information is instantly accessible, memorization becomes less valuable.

Future graduates will be judged less by what they know, and more by how effectively they can solve problems, evaluate evidence, think critically, collaborate, communicate, and exercise sound judgement. This means assessment methods must evolve as well.

Rather than rewarding students for reproducing information that AI can generate in seconds, universities should increasingly emphasize authentic projects, real-world problem solving, teamwork, creativity, ethical reasoning, and applied learning. Ironically, AI may push higher education to become more human, not less.

Educators Are Becoming AI-Enabled Mentors

There is growing concern that AI will eventually replace lecturers. I see the opposite happening.

The educator’s role is becoming even more important; but it is changing.

Rather than acting primarily as transmitters of knowledge, educators are evolving into mentors, coaches, facilitators, and critical thinking partners who help students interpret information, challenge assumptions, and develop professional judgement.

To do that effectively, universities must invest heavily in AI literacy. Faculty need more than basic familiarity with AI tools. They must understand how these systems work, their limitations, their biases, and how they can be integrated responsibly into teaching, assessment, and research. AI literacy is rapidly becoming as fundamental as digital literacy was twenty years ago.

Preparing Graduates for an AI-First Workforce

Perhaps the biggest transformation is happening outside the classroom. Virtually every profession; from healthcare and finance to engineering, education, law, and government; is being reshaped by AI.

Graduates entering the workforce will collaborate with intelligent systems every day. This requires a new combination of technical and human capabilities. Understanding AI, data, automation, and digital technologies will become essential across disciplines. Equally important will be creativity, emotional intelligence, leadership, adaptability, ethical decision-making, and lifelong learning. The most successful professionals will not compete against AI. They will learn how to work alongside it.

Looking Ahead

The future university may look very different from today’s institution. Degrees are likely to become more modular and flexible, complemented by stackable micro-credentials that allow professionals to continuously update their skills throughout their careers.

Immersive technologies such as virtual and augmented reality will create richer learning experiences, while learning analytics will enable institutions to identify struggling students earlier and provide personalized support. Education will become increasingly global, connected, and lifelong.

The Human Advantage

Despite all these technological advances, one thing remains unchanged. Education has never been solely about transferring knowledge. It is about inspiring curiosity, building confidence, developing character, nurturing empathy, and preparing individuals to make meaningful contributions to society.

No algorithm can replace the inspiration of a great teacher or the mentorship that shapes a student’s future.

AI should not diminish the human element of education. It should amplify it.

The universities that thrive over the next decade will not be those that simply adopt AI tools. They will be those that successfully combine technological innovation with the uniquely human qualities that no machine can replicate. Because ultimately, the future of higher education is not about artificial intelligence. It is about human intelligence; enhanced by AI, guided by educators, and applied to solve the world’s most complex challenges.

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