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

5W1H Analysis

Who

Key individuals, organisations, and stakeholders involved include developers and technologists working on agentic artificial intelligence (AI), AI researchers focusing on multi-agent systems, and organisations looking to integrate generative AI solutions.

What

The news highlights the necessity for organisations to reconsider their approach to risk management due to the implementation of multi-agent generative AI systems. The focus is on understanding the "confused deputy problem," a security issue where a computer program mistakenly uses its authority to access resources, potentially leading to security vulnerabilities.

When

The information was published on 19th May 2025, as organisations become more invested in developing agentic AI structures.

Where

The developments are relevant globally, impacting industries and markets that are adopting or plan to adopt multi-agent generative AI technologies, most notably in tech hubs such as Silicon Valley, London, and other technology-intensive regions.

Why

The underlying reason for this focus is the rapid advancement and deployment of AI technologies, which increase potential security risks. Organisations need to understand and mitigate these risks to protect data integrity and maintain trust in AI systems.

How

Organisations are urged to adopt new risk assessment strategies, integrating security measures such as robust authentication protocols, auditing AI decision-making frameworks, and employing AI ethics guidelines to preemptively address potential security lapses.

News Summary

The article discusses how organisations developing agentic AI must rethink their approach to risk management to address the "confused deputy problem." This issue arises when AI, as an autonomous agent, inadvertently accesses resources beyond its intended authority, causing potential security breaches. The highlighted solution involves re-evaluating risk management protocols and implementing enhanced security frameworks to safeguard against these vulnerabilities as AI technology continues to evolve globally.

6-Month Context Analysis

In the past six months, there has been escalating interest in AI safety and ethics, particularly regarding transparency and accountability in AI decision-making processes. Major tech companies have increasingly focused on developing ethical AI guidelines and instituting collaborative efforts to standardise AI risk management practices across the industry, prompted by the rapid deployment of AI technologies and their rising complexity.

Future Trend Analysis

As organisations transition towards multi-agent AI systems, there is a growing trend in prioritising AI safety and ethical considerations. This includes developing sophisticated risk frameworks to preemptively identify and mitigate security breaches related to agentic AI models.

12-Month Outlook

Over the next 12 months, we anticipate a greater emphasis on cross-industry collaboration to establish standardised security protocols for AI technologies. Organisations will likely invest in AI ethics research and advanced security mechanisms to build resilient and robust AI systems.

Key Indicators to Monitor

- Implementation of new security frameworks in AI systems - Industry-wide adoption of AI ethical guidelines - Investment levels in AI risk management research and development

Scenario Analysis

Best Case Scenario

Organisations successfully integrate comprehensive security measures, significantly reducing the risk of security breaches from agentic AI, thereby enhancing trust and reliability in AI solutions across industries.

Most Likely Scenario

Enterprises incrementally develop and adopt these risk management frameworks, leading to gradual improvements in security practices, though challenges might persist in aligning these advancements with rapidly evolving AI technologies.

Worst Case Scenario

Failure to address the confused deputy problem effectively results in significant security breaches, causing substantial organisational data losses and damaging stakeholders' confidence in AI technologies.

Strategic Implications

Organisations must prioritise the integration of robust security protocols and encourage investment in AI ethics research. Establishing clear regulatory guidelines can mitigate potential risks and foster a secure environment for AI advancements. Collaboration with industry peers will be crucial to ensure the widespread adoption of these practices.

Key Takeaways

  • Organisations must understand the confused deputy problem to effectively manage AI risks.
  • Global collaboration is needed to establish standardised AI security frameworks.
  • Investment in AI ethics research will become increasingly vital.
  • Advanced security measures are necessary to preemptively address vulnerabilities.
  • The integration of robust risk management strategies will enhance AI reliability.

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