The AI world is getting ‘loopy’

AI agentic loops—where multiple AI agents continuously iterate and improve outputs autonomously without human intervention—represent a fundamental shift in AI capability, moving from human-coded to agent-coded to agent-prompting-agent workflows. While this technology promises substantial productivity gains for complex iterative problems like code optimization, it comes with significant cost implications due to exponential token consumption with no spending ceiling. CIOs must prepare for managing new operational risks around AI drift, oversight, and cost control while evaluating whether the benefits justify the potentially substantial compute investments required.