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10/16/25, 1:05 PM Infrastructure AI takes off - Utilities Middle East
AI is also reshaping business models, and Beaumont noted a transition from traditional time-based
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AI innovation takes center stage at Bentley Systems’ Year
“Clients increasingly expect integrated solutions that combine expertise, frameworks, and technology
in a seamless package. AI enables us to move from purely time-focused models to outcome-driven
in Infrastructure 2025
approaches, where value creation is more transparent.”
Industry leaders at Bentley Systems’ Year in Infrastructure 2025 reveal how AI is moving from pilot projects to transforming
He cited Turner & Townsend’s collaboration with Google Airports as an example.
engineering, project delivery, and business models.
“We are automating post-contract commercial administration, reducing the manual effort required,
By Simone LiedtkeOctober 15, 2025
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and moving towards subscription-based technology solutions. This shift is transforming the way
commercial teams operate and the value clients receive.”
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Governance, Skills & Unlocking Value
Anne-Marie Friel, Partner in Infrastructure at Pinsent Masons, meanwhile stressed that AI adoption
comes with risks that cannot be ignored.
“The main risk is failing to deliver the purpose of a project. If AI outputs are unreliable,
untrustworthy, or non-compliant, stakeholder engagement suffers and projects underperform. Legal
compliance, governance, and ethical considerations must be embedded from day one.”
Friel highlighted that focusing solely on technology can derail AI initiatives.
“Too often, organisations get caught up in clever AI solutions without considering why stakeholders
should participate or what value the data generates. Strong data governance, ethics, and clarity of
purpose are the foundation of any successful AI project.”
Mark Biagi, Senior Director, Energy, added that auditability and accountability are key. He explained
that a good AI audit trail includes user approval for actions, logs of prompts and versions,
continuous monitoring, and validation of outputs.
“Maintaining human oversight ensures AI remains reliable, transparent, and aligned with high-risk
infrastructure environments.”
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Biago also facilitated the panel discussion.
Looking ahead, Kim emphasised that organisations are increasingly investing in data quality and
Artificial intelligence (AI) is beginning to redefine how projects are planned, delivered and managed,
workforce skills.
especially as global infrastructure demand continues to grow and engineering capacity remains
limited. In this instance, AI promises to improve efficiency, reduce risk and create measurable value,
“Many companies are standardising data schemas, tagging project information consistently, and
a panel discussion at Bentley Systems’ Year in Infrastructure 2025 conference found.
enhancing interoperability. Automation of data validation ensures quality is maintained
continuously, enabling AI to unlock maximum value.”
At the conference, the infrastructure engineering software company unveiled new AI capabilities and
announced an Infrastructure AI co-innovation initiative, inviting engineering firms and asset owners
Upskilling remains a priority. She explained that “project professionals don’t need to become data
to collaborate on the next generation of AI workflows.
scientists, but they must be data-literate. Embedding AI experts into project teams and creating
functional working groups allows knowledge transfer and practical application, strengthening
Bentley CEO Nicholas Cumins emphasised the company’s vision: “AI is poised to transform
organisational AI maturity.”
infrastructure. At Bentley, our vision is for AI to empower infrastructure engineers; not replace them.
Trustworthy AI, built on infrastructure context, can improve engineering productivity and transform
Friel and Beaumont agreed that AI adoption requires more than technical expertise, though Friel
workflows across project and asset lifecycles.”
stressed the importance of collaboration and economic valuation.
The role of AI in infrastructure is expanding rapidly, and a global survey of infrastructure
“Aligning behaviours across stakeholders and demonstrating measurable benefits are critical. CEOs
professionals, released at the conference and conducted by Bentley in collaboration with Pinsent
want to see tangible returns from AI projects, not just technical governance.”
Masons, Mott MacDonald, and Turner & Townsend, found that about half of respondents are either
piloting AI or have already implemented it, with plans to scale its use across their organisations.
Beaumont added that human expertise will become a premium resource, as he anticipates that in
the next two years, “humans will be the luxury, not AI technology”. Additionally, skills in managing
Key focus areas include boosting design and engineering productivity and automating
change, critical thinking, and creativity will become even more valuable.
documentation processes. Cumins underscored the urgency: “The greatest challenge to delivering
“Technically, AI solutions are easier to build than to implement effectively, so investing in human and
better and more resilient infrastructure is engineering capacity. The reality is, there simply aren’t
technical capabilities is essential,” he added.
enough engineers in the world to do all the work that needs to be done. AI promises a step change
in productivity that can help close this capacity gap.”
The panel discussion highlighted that while AI adoption in infrastructure is still in its early stages, the
opportunities are substantial.
These insights were further explored during a panel discussion at the conference, where YJ Kim, AI
Technical Lead at Mott MacDonald, highlighted where AI is already delivering tangible results.
From improving efficiency and productivity to enhancing risk management and sustainability, AI is
beginning to shape how projects are delivered and valued. However, success requires careful
“If we define AI broadly, including statistical learning and analytics, its use has extended beyond
attention to governance, ethical use, data quality, skills development, and business model
predictive modelling to document automation, natural language processing, and large language
models,” she explained.
innovation.
As Beaumont stated: “It’s not just about deploying AI—it’s about doing it responsibly, scaling it
She noted that these technologies are relatively mature, tested across many use cases, and provide
practical value that integrates easily into existing workflows. However, Kim emphasised the
effectively, and embedding it in ways that create real value for both organisations and the
communities they serve.”
importance of traceability in AI outputs.
“By understanding the semantic and grammatical layers, AI outputs become readable and actionable
for humans, broadening the perspective for decision-making.”
SIMONE LIEDTKE
Guy Beaumont, Digital Lead for Infrastructure at Turner & Townsend, reinforced the challenge of
Based in Dubai since 2025, Simone is a seasoned features writer with nearly a decade of
experience in technical writing. Previously penning stories for a engineering and a mining
scaling AI from pilot projects to production. “Many organisations are stuck in the piloting cycle. T o
magazine in South Africa,... More by Simone Liedtke
scale effectively, companies need to invest in data readiness, strengthen data architecture, and
ensure infrastructure can support production-grade AI solutions. It’s about building the foundations
so AI can deliver reliable value,” he said.
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