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

5W1H Analysis

Who

The key stakeholders involved are technology organisations, AI developers, and risk management professionals. Corporations developing AI technologies, particularly those focused on multi-agent systems, are central to this discussion.

What

The issue at hand is the "confused deputy problem," a known security vulnerability in computing. The focus is on preparing for risks associated with multi-agent generative AI by understanding and managing compound risks inherent in these systems.

When

The discussion and analysis of these risks are pertinent as of May 2025, indicating a forward-looking approach towards risk management practices in AI deployment.

Where

The implications are global, affecting organisations and markets worldwide where AI technologies are developed and deployed.

Why

There is a pressing need to address the confused deputy problem to ensure that the increasing complexity of AI systems does not lead to security vulnerabilities. As AI systems become more agentic, they pose unique challenges that require a reevaluation of traditional risk management approaches.

How

Organisations must approach AI development with a robust understanding of the confused deputy problem, employing specialised security frameworks and risk assessment tools designed to mitigate the unique risks posed by multi-agent AI systems.

News Summary

The blog highlights the importance for organisations to rethink their risk management strategies as they engage with multi-agent generative AI. Understanding the confused deputy problem—a potential security vulnerability—is critical to avoiding compound risks that could emerge in these advanced systems.

6-Month Context Analysis

Over the past six months, there has been growing discourse around AI safety and ethics, with significant conferences and publications discussing emergent risks in AI. Key players in tech have called for updated security measures as AI systems become increasingly autonomous. This specific focus on the confused deputy problem aligns with broader efforts to preemptively tackle compound vulnerabilities in AI systems before they escalate.

Future Trend Analysis

As AI evolves, there is a clear trend towards developing more autonomous and connected systems. This brings an increased focus on securing these systems against vulnerabilities like the confused deputy problem.

12-Month Outlook

Expect to see enhanced regulatory frameworks and industry standards that specifically address security in multi-agent systems. Companies will likely increase investments in security technologies and methodologies designed to identify and counteract complex AI vulnerabilities.

Key Indicators to Monitor

- Development of new security protocols for AI systems - Increased publications and patents focused on AI risk management - Regulatory changes targeting AI safety standards

Scenario Analysis

Best Case Scenario

If organisations successfully integrate advanced risk management strategies, the deployment of multi-agent AI systems will be secure, driving innovation without compromising safety.

Most Likely Scenario

Organisational awareness will grow, leading to gradual changes in how AI systems are developed and monitored. While challenges may persist, the industry is likely to see improvements in managing AI-related risks.

Worst Case Scenario

Failure to adequately address the confused deputy problem could result in significant security breaches, undermining public trust in AI systems and causing regulatory crackdowns and financial losses.

Strategic Implications

Organisations should prioritise security education for AI developers and invest in state-of-the-art risk assessment tools. Collaborations between tech companies and regulatory bodies may also be beneficial to standardise AI safety protocols.

Key Takeaways

  • Organisations must tackle AI security with a focus on the confused deputy problem to mitigate compound risks (Who, What).
  • Global markets must brace for changes as new AI security standards emerge (Where, What).
  • Investment in educational initiatives about AI vulnerabilities will be crucial (How).
  • Regulations are likely to tighten as AI systems become more prevalent (Why, Where).
  • Continuous monitoring and quick adaptation to new security protocols will be essential (When, How).

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