The AI Interview: Julien Moutte, Bentley Systems

2026-06-17 · Source: AI Magazine · Field: Construction & Real Estate — Construction Technology & Building, Infrastructure & Civil Engineering, Artificial Intelligence & Machine Learning · Depth: Intermediate, medium

Summary

Julien Moutte, CTO at Bentley Systems, details how AI agents are transforming infrastructure engineering by acting as a force multiplier for civil engineers amidst a growing demand and shortage of professionals. Bentley Systems' software, used on projects like London's Crossrail (Elizabeth line, 2022) and Heathrow Airport expansions, now integrates AI to enhance collaboration and efficiency. AI agents can connect to common data environments to run quality validations faster than humans and automatically recompute construction schedules in real-time, as seen with Synchro Plus at Heathrow. Bentley's approach involves "giving an engineering licence to AI," where AI outputs are validated by proven engineering tools, ensuring accountability. AI also automates time-consuming tasks like generating technical drawings, reducing engineer time spent on annotation by 30-50%, and supports open standards and APIs for long-term data accessibility.

Key takeaway

For CTOs or Directors of AI/ML in infrastructure, integrating AI agents into your engineering workflows can significantly address the civil engineer shortage and project demands. You should prioritize AI solutions that augment human expertise, automating tasks like quality validation and drawing generation while ensuring outputs are rigorously validated by established engineering tools. This approach allows your engineers to focus on higher-value decisions, improving project efficiency and accountability.

Key insights

AI agents can act as a force multiplier in infrastructure engineering, enhancing efficiency and collaboration without replacing human oversight.

Principles

• AI outputs require validation by proven engineering tools.
• Open standards, APIs, and source are crucial for infrastructure data longevity.
• AI should augment engineers, not replace their decision-making.

Method

AI agents connect to common data environments, perform automated quality validations, recompute schedules, and generate technical drawing annotations, all validated by engineers.

In practice

• Deploy AI agents for automated design quality checks.
• Use AI to dynamically re-sequence construction schedules.
• Train AI models on proprietary engineering drawings for automation.

Topics

• AI Agents
• Infrastructure Engineering
• Common Data Environment
• Construction Scheduling
• Open Standards
• Engineering Automation

Best for: CTO, Director of AI/ML, Domain Expert

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Magazine.