Technology and Innovation Community

Latest report from the Team @ McKInsey & Co. on tech infrastructure for agentic AI.

report

Key takeaways:

For CTOs:

• Redesign targeted processes. Select one area with high volume, clear performance pain points, and strong potential for repeatable execution, such as service desk operations and incident management. Deconstruct the workflow into its component tasks and redesign the process so that routine tasks are executed automatically within defined boundaries, while engineers intervene when judgment or creativity is required. This redesign often simplifies the process itself.
• Strengthen operational data. Agents cannot compensate for inconsistent system records or unclear ownership. A practical starting point is to clarify the source of truth for assets, configurations, and dependencies. Standard naming conventions, consistent schemas, and explicit ownership reduce ambiguity. Determine if the underlying data and knowledge about the infrastructure are structured and consistent enough for machines to interpret and reuse.
• Establish strong operating and governance practices. Before agents are allowed to execute changes in production environments, CTOs need a clear framework that defines permissible actions, escalation thresholds, and accountability. Each agent should have a named owner, with clarity around which decisions can be made autonomously and which require review. Logging and audit capabilities must be comprehensive (see sidebar "The human and operating model shift behind agentic infrastructure").
• Put in place explicit agent management practices. A formal registry that documents each agent's purpose, scope, and performance prevents fragmentation. Life cycle management ensures that outdated or redundant agents are retired. Visibility into performance and cost helps the organization understand where value is being created.