{"id":162724,"date":"2026-06-08T13:40:00","date_gmt":"2026-06-08T12:40:00","guid":{"rendered":"https:\/\/www.pbctoday.co.uk\/news\/?p=162724"},"modified":"2026-06-08T13:40:00","modified_gmt":"2026-06-08T12:40:00","slug":"precision-over-plausibility-ai-in-infrastructure-demands-a-different-standard","status":"publish","type":"post","link":"https:\/\/www.pbctoday.co.uk\/news\/digital-construction-news\/precision-over-plausibility-ai-in-infrastructure-demands-a-different-standard\/162724\/","title":{"rendered":"Precision over plausibility: AI in infrastructure demands a different standard"},"content":{"rendered":"

Julien Moutte, chief technology officer at Bentley Systems, examines AI and the trust problem in infrastructure<\/h2>\n

Every time you drive over a bridge, turn on a tap for a glass of water or flip a light switch, you are placing your trust in a complex system of infrastructure. You trust that the engineering was sound, the materials were correct and the analysis was precise. This trust is the silent, foundational contract upon which modern society is built. It is also why the conversation about AI in infrastructure must be fundamentally different from any other domain.<\/p>\n

The rise of generative AI has been astonishing, but it introduced the concept of \u201cAI slop\u201d – outputs that are plausible-sounding but imprecise, inconsistent or flat-out wrong. In many fields, this is an acceptable trade-off for speed. A door the wrong shade of blue won\u2019t hurt anyone.<\/p>\n

The reality of the infrastructure sector, however, is that there is no room for approximation, let alone hallucination. A model that is 90% right is a useful start; a structural analysis that is less than 100% right is a catastrophic liability. Would you drive across a bridge that is \u201chopefully\u201d designed right?<\/p>\n

The gold standard of AI in civil engineering is not to provide a creative starting point but to deliver precise designs for real-world delivery. At Bentley, we are building AI-supported workflows<\/a> grounded in the strict principles of engineering discipline. This creates a powerful partnership: AI acts as a tireless partner exploring design alternatives a human might not have time to investigate. The engineer, freed from repetitive calculation, focuses on their most valuable assets: judgment, experience, and intuition.<\/p>\n

Giving AI an engineering licence<\/h3>\n

The key to enabling this partnership is the Model Context Protocol<\/a> (MCP), an open standard governed by the Agentic AI Foundation. MCP works across any AI platform and has quickly become the industry standard for connecting AI agents directly and reliably to external applications.<\/p>\n

By building MCP servers for our core products, we give AI programmatic access to the validated engineering and simulation power Bentley has built over 42 years.<\/p>\n

We are not generating text about engineering; we are executing real, verifiable engineering workflows.<\/p>\n

Because structural engineering tolerates no approximation, STAAD – one of the most widely used tools by civil engineers – was a logical place to begin. We published our STAAD MCP server to the MCP Registry, and the results are transforming our vision into reality:<\/p>\n