AI in the Arabian Gulf: How AI-powered smart cities can lead the world forward

When it comes to smart cities, it should be no surprise that the Gulf states already lead the world. With their stunning growth powered by the advances of the 20th century, from energy to air conditioning, they are keenly aware of the critical importance of innovation. The region is a crucible for advanced technological progress, especially in the built environment, where its population overwhelmingly resides.

Confident in new technology, willing to experiment, and unencumbered by the density of historical population centers, the Gulf is in many ways the ideal laboratory for implementing the smart, cognitive advancements to urban life. Yet despite its clear advantages, it too must adapt. Climate change in particular is a growing threat as the climate grows more volatile. In 2024, the Gulf states experienced flooding far beyond anything in living memory - in the UAE more than a year’s worth of rain fell in under 24 hours.

AI can enable the region’s cities to strengthen their resilience, efficiently, and at speed - while improving quality of life, too. Machine learning can analyze a range of datasets to model climate change scenarios, enabling informed decision-making to negotiate challenging trade-offs. Embedding AI models within city infrastructure can gather real-time data, which in turn can better model individual and group behavior, enriching the city’s ongoing design and management. And, by synthesizing datasets from across the different layers, functions, and communities within a city, AI can ensure that the emergent, higher-level outcomes are safeguarded.

Yet none of this is a matter of course; it depends not just on the technology itself or the funding to deploy it, but on how it is implemented. Complexity at this scale, with such a novel range of implementation challenges, can confound even the best-funded visions.

That’s why leaders’ approach to AI-powered smart cities matters. Modular, place-led, and outcomes-focused efforts reduce the risk of delays, setbacks, and unintended consequences, while enabling rapid rollout and intelligent iteration. In turn, this approach also safeguards deeper, cross-functional resilience - all the region’s economic, technological, and cultural advantages may ultimately depend on the extent to which it can protect its urban communities from the extremes of heat, flood, and drought that climate change will bring.

Robot-ready

AI enables better processes, better processes enable AI: this virtuous cycle can propel cities forward, but establishing it is tricky. Attempting a top-down, city-wide, cross-functional machine learning application is fraught with risk. The multiplicity, volume, and sheer scale of the data alone is enough to stymie progress and ensnare well-intentioned projects in a thicket of complexity. Instead, cities should learn from the tech industry and adopt a product lifecycle management approach.

Short sprints, rapid feedback loops, and iterative testing reduce the risk of suboptimal outcomes or misalignment with user needs. Validating assumptions on smaller tasks can compound learning into significant gains and momentum; smaller projects can be built, tested, and released faster, allowing decision-makers to gain valuable insights faster, enriching subsequent projects. In turn, this contributes to a ‘kit of parts’, the modularity of which makes it easier for human teams and AI models to interface together by taking anomalous, discretionary elements out of the process.

Manufacturing shows what this modular, kit-of-parts assembly line can achieve. Repeatable processes drive down cost and risk, attracting more investment. Individual, modular approaches are easier to measure and manage, reducing the inevitable roadblocks that major projects inevitably entail. Together, this allows futuristic cities to be built iteratively on modular components, simplifying the design and supply chain, and making it easier to build, run, and maintain each element.

A product lifecycle management approach enables another innovation: robotics. Expedited by modular, repeatable processes, robotics speeds up construction by reducing error and accelerating design. By reducing the need for people on production lines, they improve safety while also reducing the need for labor, which is growing more acute through the skills shortage. AI enables intelligent robotic elements that are capable of working within human cognitive systems, ensuring more efficacy and faster adoption, driving further efficiencies and powering growth.

From insights to impact

Similarly, the attainment of amorphous city-wide outcomes like livability, community, and quality of life must be nurtured from the ground up. Cities are complex, adaptive, and ever-evolving systems. Yet AI models can synthesize cross-functional data for better outcomes. Its capabilities in throughput, modelling, sentiment analysis can help to detect deeper insights, unearth flaws in design or management, and equipping urban leaders to predict and optimize with less risk of incurring unexpected consequences. 

Longer term, these advancements can turn cities into self-sufficient circular economies, ensuring that they are built and run in the most efficient way so that they are as adaptable and resilient as possible. Short term, that begins with using machine learning for better scenario modelling; first within single neighborhoods or against individual threats, and then by combining these capabilities to yield insightful city-wide decisions that mitigate trade-offs and maximize utility. Scenario modelling can enable predictive, preventative interventions that avoid problems from arising in the first place, freeing up resources that are usually absorbed by reactive management. Through improved scenario modelling, AI can empower cities to anticipate and avoid potential problems - and adapt smartly to those that they can’t.

Crossing the Gulf

Urbanization, population growth, and an increasingly unstable climate: the global megatrends for the next decades are clear. Here in the fast-growing and disproportionally urban Gulf, these challenges are pressing. Yet AI can enable efficient, holistic navigation of these issues, helping city leaders to chart a course through the challenging conditions and to cultivate cities that thrive. AI-powered smart cities are about ambition, aspiration and achieving the previously unimaginable, but they’re also about necessity. To survive, our cities must adapt.

Cities seem to magnify the problems of human civilization - so much so that it’s easy to condemn urbanization as the cause of our problems. But cities are a core part of the solution. High-density settlements supercharge prosperity, intensify innovation, and compound efficiencies. They’re the surest path to sustainability and the engines of economic equity. As frustrating as they can no doubt be, they’re our best chance of thriving together, even as the global population approaches 10 billion.

Moreover, cities – even in this pioneering and future-focused region - are still relatively early in their digital development. They have become smarter, but now they are challenged to go beyond smart and become cognitive. AI and machine learning can dramatically enhance the intelligence, scale, and adaptiveness of our cities, if we’re able to apply it wisely and integrate it with diverse human needs. Whether it’s vertical urban farming, smart mobility, or wetland drainage ecosystems, so much potential has yet to be unlocked. AI can reveal how best to reduce air pollution, decrease stress, and restore the sense of community upon which so much of human collaboration depends.

Yet this is only possible if we learn from the past. Where the 20th century belonged to linear, top-down standardization, innovation in the 21st will instead belong to user-led, locally focused hotbeds of sustainable growth. If we use AI to integrate city systems, the often competing and apparently zero-sum demands of neighborhoods, nature, and policy makers alike can contribute to holistic, informed and insightful decisions that harmonize this multiplicity of diverse needs, so that cities nourish what we value most about life on Earth, and bypass what we don’t.

Ultimately, innovation must empower the wellbeing of human communities. Only then can it propel us to safe, thriving, and more prosperous communities - overcoming the challenges of the 20th century, and surpassing the expectations of the 21st.