{"id":81249,"date":"2026-09-18T14:53:33","date_gmt":"2026-09-18T17:53:33","guid":{"rendered":"https:\/\/a3aengenharia.com\/?post_type=articles&p=81249"},"modified":"2026-09-18T14:53:33","modified_gmt":"2026-09-18T17:53:33","slug":"ai-governance-engineering-iso-42001-risk-technical-responsibility","status":"publish","type":"articles","link":"https:\/\/a3aengenharia.com\/en-us\/content\/technical-articles\/ai-governance-engineering-iso-42001-risk-technical-responsibility\/","title":{"rendered":"AI Governance in Engineering: ISO 42001, Risk, and Technical Responsibility"},"content":{"rendered":"\n

AI governance in engineering<\/strong> is the set of policies, responsibilities, processes, controls, and evidence used to ensure that artificial intelligence systems are selected, developed, integrated, used, and monitored in a manner consistent with technical and organizational risk. In engineering companies, governance needs to connect the AI lifecycle with the lifecycle of projects, documents, and assets.<\/p>\n\n\n\n

The ISO\/IEC 42001:2023<\/strong> provides one of the main references for this structure. The standard specifies requirements to establish, implement, maintain, and continually improve an Artificial Intelligence Management System \u2014 AIMS. Its focus is not to teach a specific algorithm, but to create a management system capable of defining policies, roles, risk assessment, controls, monitoring, and improvement for organizations that develop or use AI.<\/p>\n\n\n\n

This framing is especially relevant to engineering because an AI application may operate in activities with very different consequences. Summarizing an internal meeting carries a different risk from classifying a requirement, suggesting a design change, supporting technical acceptance, or executing an action on a system. Governance means recognizing this difference and adjusting autonomy, validation, records, and accountability to the potential impact.<\/p>\n\n\n\n

The Artificial Intelligence in Engineering pillar presents the technologies across the lifecycle. This article focuses specifically on the governance layer: how to structure roles, system inventories, impact assessment, data, suppliers, validation, incidents, monitoring, and continual improvement.<\/p>\n\n\n\n\n

What ISO\/IEC 42001 organizes<\/h2>\n\n\n\n

ISO\/IEC 42001 is a management system standard. Like other management system standards, it establishes an organizational structure for turning principles into repeatable processes. Within the cluster, the Artificial Intelligence in Engineering pillar<\/a> maintains the broad view of technologies, while this article goes deeper into the governance system.<\/p>\n\n\n\n

The objective is to allow the organization to treat AI as a governed capability rather than a collection of isolated experiments.<\/p>\n\n\n\n

The structure can be understood through the Plan-Do-Check-Act<\/strong>:<\/p>\n\n\n\n

AI management cycle inspired by ISO\/IEC 42001<\/title>