Before you build agentic AI, understand the confused deputy problem Analysis Report

5W1H Analysis

Who

Key stakeholders involved include technology companies, AI developers, cybersecurity experts, and organisations implementing multi-agent generative AI systems. HashiCorp is a major entity discussing the issue.

What

The issue at hand is understanding the “confused deputy problem” in the context of agentic AI systems. This problem pertains to security risks and decision-making errors when multiple AI agents operate with overlapping authorities and unclear boundaries.

When

The discussion and awareness around this issue have been gaining traction in the tech community throughout 2025, focusing on preparations organisations are making for agentic AI deployment.

Where

This is a global issue affecting technology markets worldwide, especially in regions heavily investing in AI development like North America, Europe, and Asia.

Why

There is increasing concern over the security vulnerabilities introduced by multi-agent AI systems, which could exacerbate the confused deputy problem. Understanding and mitigating these risks is crucial for safely implementing advanced AI technologies.

How

Mechanisms include improving organisational risk assessment frameworks, developing clear-cut authority protocols for AI agents, and enhancing cybersecurity measures specifically targeted at mitigating multi-agent AI risks.

News Summary

Organisations are being urged to rethink their risk assessment strategies as they prepare to integrate multi-agent generative AI. The primary concern is the confused deputy problem, a security risk where overlapping authorities among AI agents can lead to decision-making errors and vulnerabilities. As these technologies are being adopted globally, understanding and addressing these issues are critical for harnessing their full potential safely.

6-Month Context Analysis

Over the past six months, there has been a significant surge in discussions around AI ethics, safety, and security, highlighted by numerous global conferences and publications. Companies like HashiCorp have focused on the security challenges of AI, anticipating risks associated with increased AI adoption. This aligns with parallel developments in AI legislation and ethical frameworks being formulated worldwide.

Future Trend Analysis

One emerging trend is the development of specialised AI risk management frameworks. There's also a growing emphasis on AI ethics and security in technology curriculums, reflecting a proactive shift towards safer AI practices.

12-Month Outlook

In the next year, expect increased investment in AI safety tools and an upsurge in collaborations between tech companies and cybersecurity firms. Regulatory bodies might also introduce stricter guidelines on AI agency and decision-making clarity.

Key Indicators to Monitor

- Development and adoption rates of AI risk management frameworks. - Policy changes or new regulations concerning AI security. - Investment trends in AI security startups and tools.

Scenario Analysis

Best Case Scenario

Organisations successfully implement robust risk management strategies for AI, significantly reducing the impact of the confused deputy problem, and setting new industry standards for AI safety.

Most Likely Scenario

Companies incrementally improve their AI systems' security postures while encountering sporadic issues that drive iterative improvements. Collaboration across the tech industry helps remediate emerging problems efficiently.

Worst Case Scenario

Failure to address the confused deputy problem leads to significant AI failures, resulting in financial losses and potential legal repercussions for companies involved. Public trust in AI technologies diminishes, slowing industry growth.

Strategic Implications

Organisations must prioritise AI security by investing in education and training to better understand AI-specific risks, establish clear protocols to manage AI interactions, and collaborate with industry partners to share insights and solutions.

Key Takeaways

  • AI developers and organisations must deepen their understanding of AI-specific risks like the confused deputy problem.
  • Implementing comprehensive AI risk management frameworks is essential.
  • Monitoring regulatory changes and evolving security best practices is crucial for compliance and safety.
  • Collaborations can offer valuable insights and promote shared security improvements.
  • Proactive investment in AI security and ethics can safeguard against future risks and bolster industry trust.

Source: Before you build agentic AI, understand the confused deputy problem