Enterprises tighten governance for agentic AI: emerging risks

Enterprises, payments firms, and analysts are tightening governance and security as agentic AI moves into production. Axios reports that Mastercard is moving to set rules for AI in commerce (Jan 20, 2026). Forbes published four predictions for business leaders that emphasize human oversight, execution boundaries, and technical controls for autonomous agents (Jan 13, 2026). TechRadar notes companies admitting agentic AI goals are faltering because of limited trust and weak controls (Jan 14, 2026).

Industry guidance centers on layered controls: define clear execution boundaries for agents, require human-in-the-loop accountability, and apply runtime technical controls such as rate limits, intent verification, and auditable logs. Sources warn of specific risks, including agent misuse, new fraud vectors in commerce, and cascade security incidents when agents access enterprise systems. Forbes groups these into four business priorities, while TechRadar links failed projects to missing trust and governance.

Expect more vendor and industry rules, tighter procurement requirements, and new security mandates for agent workloads. Security and compliance teams should map agent permissions, add runtime observability, and update incident playbooks for agent-driven fraud and lateral-movement scenarios. Mastercard’s move suggests payments and commerce may be an early focus for formal rules.

Why It Matters

• Map agent permissions and limit execution scope now — agents with broad API access increase lateral-movement and fraud risk.
• Enforce human-in-the-loop checkpoints and maintain auditable decision logs to preserve accountability and support compliance.
• Apply runtime controls (rate limits, intent verification, anomaly detection) to reduce exploitation of autonomous workflows.
• Treat agent deployments as production services: add observability, run chaos and abuse tests, and update incident response playbooks for agent-originated fraud and cascading incidents.