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September 3, 2026

Myth busting: AI agents don’t need multi-factor authentication (MFA) 

Posted by purplefishagency

September 4, 2026

We’re unpacking common AI identity myths, aiming to separate fact from fiction to help organisations understand what it takes to securely integrate AI agents at scale. 

Myth: “AI Agents Don’t Need MFA” 

Technically, that’s true. AI agents don’t enter passwords, approve push notifications or retrieve one-time passcodes. Traditional MFA was designed for humans, not machines. But that’s where this perception creates risk. While AI agents may not need MFA, they still need to be trusted, authenticated and governed. The rise of AI agents is shifting the identity conversation from verifying people to governing an unseen workforce. As a result, the real question isn’t whether AI agents need MFA. It’s whether they have the correct permissions in place to ensure they don’t extend access beyond the role they are created for.  If organisations cannot see how much reach these agents have and the systems they are connected to, or how they are authenticating themselves, they risk creating a growing population of unmanaged machine identities. 

Reality: What AI agents need instead 

Instead of MFA, AI agents require four key identity security controls: 

1. Identity and visibility 

Before organisations can secure AI agents, they need to know where they exist. Security leaders should be able to answer: 

  • How many AI agents are operating in the environment? 
  • Who deployed them? 
  • What systems do they access? 
  • What data sources are they connected to? 
  • Are there unauthorised or shadow AI deployments? 

2. Authentication and trust 

Every AI agent needs a trusted identity. Whether that identity is established through certificates, secrets, tokens or application credentials, organisations must ensure agents can securely prove who they are before receiving access to resources.

3. Least privilege access 

Many AI applications are granted excessive permissions to simplify deployment. This creates unnecessary risk. AI agents should only have access to the systems, applications and data required to perform their specific task.  

4. Continuous oversight 

Identity isn’t a one-time event. Organisations need ongoing visibility into: 

  • Agent activity 
  • Privileged actions 
  • Access changes 
  • Credential usage 
  • Emerging risks 

One of the biggest challenges for security teams is shadow AI. Employees can now create or deploy AI agents with minimal oversight, often connecting them to business systems and sensitive data. Without visibility into these deployments, organisations may be exposing themselves to unnecessary risk. 

What strong AI identity governance looks like 

Securing AI agents requires more than policy. Organisations need visibility into what AI agents are doing, what they can access and whether they’re operating within defined boundaries. 

This is where identity security platforms such as BeyondTrust can play an important role, helping security teams gain insight into AI agents across their environment, including their privileges, owners, connected systems, knowledge sources and potential shadow AI activity. 

By combining visibility, least-privilege controls and secure credential management, organisations can reduce the risks associated with unmanaged machine identities while maintaining oversight of an expanding AI workforce. 

As organisations continue to expand their use of AI, these capabilities become essential for maintaining control, accountability and trust in machine identities. 

The bottom line 

AI agents may not need MFA, but they do need identity security. As the unseen workforce grows, trust can no longer be assumed. It must be continuously verified. 

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