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CivilEngineers.com

Owner Q&A · Technology and AI

What AI tasks should an engineering firm avoid automating?

An engineering firm should keep decisions that require professional judgment, a responsible licensee, or direct accountability with a qualified person. Do not let an AI system set final design criteria, seal documents, decide code compliance, resolve safety questions, or approve a construction change. Staff may use AI to gather and organize information for these tasks, but the responsible engineer must verify the evidence, make the decision, and record it through the firm’s approved process. Licensed PE judgment and local codes govern.

Owners can set a practical boundary by listing decisions that require a named engineer’s review. Ask the technical principal to identify which work needs direct licensee involvement, including design exceptions, life-safety concerns, code interpretations, and field changes that could affect scope or performance. Put those requirements in the workflow, so staff know when to stop and whom to contact.

AI may locate a contract clause, but the project manager or attorney must interpret its effect. It may summarize field notes, but an engineer should compare the summary with the original record, drawings, and site context before relying on it. It may flag a possible drawing discrepancy, but the responsible engineer must determine whether it matters, what action is needed, and who should be notified. Keep the original records with the review notes so another team member can trace how the decision was reached.

Some information should not be entered into an AI tool until the firm has approved the service and confirmed that sharing is permitted. This can include client-confidential files, personal data, credentials, and controlled project information. Assign an owner to approve tools and define what categories of information staff may submit. Give employees a clear place to ask before uploading a file, and a simple reporting path for mistaken disclosures. Ask counsel or the client contact to check contract restrictions and applicable confidentiality terms.

Before an AI-supported workflow goes live, the owner should require a written process that names the reviewer, lists the evidence needed to check the output, and explains what to do when results are uncertain, incomplete, or conflicting. Have staff test the process on representative work and record review findings. If a user cannot explain how a result was verified, the workflow is not ready for reliance. Revisit the process when project requirements, tools, or firm policy change.

This is general education, not legal or engineering advice.

Richard C. Wilson

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