The dual nature of risk
The corollary of these advancements isa new—and, therefore, unpredictable—risk landscape.
Agentic AI introduces unique challengesthat existing governance frameworksweren't designed to address such as:
Operational risks:
Agents making decisions that create unforeseen business consequences
Failure modes that can cascade across interconnected systems
Degradation of performance as operating conditions change
Human and artificial agent coordination problems
Compliance risks:
Regulatory requirements that weren't drafted with autonomous systems in mind
Challenges in demonstrating appropriate oversight to regulators
Attribution of responsibility when multiple agents interact
Documentation and explainability expectations that traditional AI already struggles with
Ethical risks
Agency delegation questions around appropriate human oversight
Potential bias amplification through autonomous decision loops
Trust erosion if agents act in unexpected or unexplainable ways
Stakeholder concerns about displacement and autonomy
The governance challenge is more than mitigating risks. The real challenge—and opportunity—is driving governance while preserving the agility and innovation that make agentic AI valuable in the first place.
Organizations that strike this balance will gain a competitive advantage through both the capabilities AI agents provide and the trust they maintain with stakeholders.
