AI to power Middle East's next infrastructure leap amid trillion dollar investment gap | TahawulTech. com
For years, conversations about artificial intelligence (AI) have focused on copilots, chatbots and workplace productivity. These applications have dominated headlines, yet AI’s most transformative impact may be unfolding more quietly across infrastructure, with far greater long-term significance. AI is …
Dave Philp, Chief Value Officer, Bentley Systems. Foryears,conversations aboutartificial intelligence (AI) havefocused oncopilots, chatbots and workplace productivity. Theseapplications havedominatedheadlines,yetAI’s most transformativeimpact may beunfolding more quietlyacross infrastructure,withfargreater long-term significance. AI is transforming how infrastructure is conceived, delivered, operated and improved. Forthe first time,theindustrycanturn decades of fragmented engineering knowledge into intelligent decision-making capabilities thatimproveoutcomesover time. From roads, railways, airports and metro networks to power grids, water systems and data centres, AI is moving beyond the digital workplace and into the assets that support economies and societies. This is more thananother wave of digital transformation. It marks a fundamental shift in how infrastructure is delivered at a timeofmountingpressure. Why infrastructure needs AI nowDemand for infrastructure continues torise, while investment, skilled engineeringtalentand delivery capacitystruggleto keep pace. According to an industry report, global infrastructure needs are expected to reach USD 97 trillion by 2040, leaving a projected investment gap of approximately $15 trillion. Projects are alsobecoming larger, more interconnected andmorecomplex, while valuable engineering dataremainsfragmented across disconnected systems. The challenge extends beyond finance. Much of the world’s infrastructure expertise sits with an ageing workforce, and many organisations face significant knowledge-transfer risks as experienced engineers retire. AI offers a way to capture institutional knowledge, engineering rationale and lessons learned before they are lost. Modern infrastructure projects also generate far more data than organisations can interpret through traditional methods. Engineering models, sensors, reality capture, schedules, asset records and operational systems produce information at a scale that exceeds human capacity to analyse effectively. These challenges cannot be solved simply by working harder. The industry needs a different approach to decision-making, where AI helps engineers gain better insights and make more informed decisions. Building smarter infrastructure with AIAcross the infrastructure lifecycle, AI is emerging asa powerfulengineering partner. During planning, it can analyse decades of project data to identify risks, highlight relevant precedents and improve early-stagedecisions. In design, AI-powered copilots and generative design tools allow engineers to interact with complex models using natural language,evaluateoptionsquicklyand optimise outcomesagainstproject objectives. As projects move into delivery, AI can automate repetitive quality assurance and quality control (QA/QC) processes, streamline multidisciplinary design reviews and improve coordination across teams. Once assets become operational, AI can support predictive maintenance, improve asset performance andunlockinstitutional knowledge that would otherwise remain inaccessible. Beyond automation, AI is creating a new generation of decision intelligence. Rather than speeding up existing processesalone, AI can reveal relationships, risks andoptimisationopportunities hidden within vast engineering data sets. Thiscanimprove outcomes across cost, carbon, resilience, safety and asset performanceat the same time. The real value of AI lies in helping engineers spend less time searching for information or performing repetitive checks, and more time applying judgement, solving complex problems and driving innovation. Infrastructure intelligence becomes the new competitive advantageHistorically, infrastructure organisations have competed on engineering expertise, capital investment and operational scale. Increasingly, the differentiator will be the ability to convert infrastructure data into intelligence. Organisations that connect engineering, operational and performance data in AI-enabled environments can make faster, more informed decisions than those relying on fragmented information sources. In this sense, AI is more than another technology layer. It is becoming the mechanism through which infrastructure organisations learn, adapt and continuously improve. Those that establish these capabilities first may gain a lasting advantage in project delivery, asset performance and resilience. The Middle East’s AI advantageThis evolution isespeciallyrelevant for the Middle East. Regional governments are investing heavily in smart cities, renewable energy, advanced transport networks, digital infrastructure and next-generation urban development. From the UAE’s digital transformation agenda to Saudi Arabia’s Vision 2030 and giga-projects, infrastructure is becoming more connected, data-rich and technologically sophisticated. Thesedevelopments generate enormous volumes of engineering and operational data. AI can turnthat data into actionable intelligence, helping teams improve collaboration, accelerate delivery,strengthenoperational resilience and enable smarter asset management throughoutthe infrastructurelifecycle. For a region seeking to build some of the world’s most advanced infrastructure,AIshouldbe viewedas a strategic capability that can improve productivity, resilience and long-term competitiveness. TheMiddle East iswellpositioned to become a global leader in AI-enabled infrastructure. Whilemany mature economies mustmoderniseageing assets and fragmented systems, the region is often building at unprecedented scale with digital delivery, smart operations and data–drivenasset management embedded from the outset. Why trusted AI will define the future of infrastructureInfrastructurepresents a very different challenge from consumer AI applications. When AI influences decisions affecting transport systems, utilities, public buildings or energy networks, the stakes are considerably higher. These decisionsaffectpublic safety, regulatory compliance, operational reliability and long-term asset performance. That is why trust must become the foundation of AI adoption in engineering. AI-generated recommendations shouldavoidopaque ‘black box’ outputs. Whether identifying design conflicts, automating compliance reviews or recommending engineering solutions, every recommendation must be transparent, explainable and supported by a clear audit trail. Human expertise must remain central to every critical decision, with AI serving as an intelligent assistant rather than an autonomous decision-maker. Organisations that establish strong governance frameworks, ensure accountability and prioritise responsible AI deployment will be best positioned to realise its benefits while maintaining the confidence of engineers, regulators, asset owners and the communities they serve. The next chapter of AI willbe shapedby how responsibly we apply intelligence to the physical infrastructure that powers economies, connects communities and shapes everyday life. For the Middle East, where infrastructure is central to long-term economic transformation, the opportunity is to embed trusted, transparent and human-centric AI into the foundations of the future built environment. This opinion piece is authored byDave Philp, Chief Value Officer,Bentley Systems.