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Introduction: The New Era of AI Autonomy
As AI agents begin to take on more autonomous tasks previously managed by humans, businesses must rethink how they manage identity and access. With the rapid adoption of AI tools and systems, especially those capable of operating independently, organizations face increasing security risks related to unauthorized access and privilege escalation. In a recent interview featured in the “Leader’s Voice” series, Eduarda Camacho, Chief Operating Officer (COO) of Israeli cybersecurity company CyberArk, emphasized the growing importance of identity and access management (IAM) in the era of AI agents.
the Original
In a members-only feature, CyberArk COO Eduarda Camacho shares her insights on the critical role of identity management in the evolving landscape of AI-powered workforces. As AI agents become more sophisticated and autonomous, companies must establish clear boundaries around what each systemâjust like each human employeeâis allowed to do and access.
Camacho explains that identity and privilege management is no longer limited to human users. AI agents must now be treated as active digital identities within the corporate ecosystem. Their roles, access levels, and responsibilities must be tightly controlled to avoid breaches or unintentional misuse of data.
According to Camacho, managing digital identities goes beyond technical systems. It’s about integrating policy, strategy, and operational discipline to ensure that AI agents remain compliant and under control. Organizations that overlook this responsibility may find themselves vulnerable to security threats, including insider threats introduced by AI systems themselves.
She further underscores that identity management should be dynamicâadapting to real-time changes in user behavior, task scope, and system access needs. Businesses must implement role-based access controls (RBAC), continuous authentication, and real-time monitoring to safeguard both human and AI activity.
This approach, she says, isn’t just about risk reductionâit’s about trust. Enterprises must build secure environments where AI agents can be trusted to act in line with company objectives and within permitted boundaries.
What Undercode Say: Identity in the AI Agent Era đ
A New Identity Paradigm
The traditional model of cybersecurity, which focused heavily on securing networks and endpoints, is being outpaced by the rise of autonomous AI agents. These agents are not just tools; they act, learn, and sometimes make decisions without direct human supervision. As such, treating them like passive software is no longer an option.
Machine Identities Are Real Identities
At Undercode, we see an urgent need to extend identity frameworks to cover AI systems just as rigorously as human accounts. This means assigning them unique identifiers, tracking their behaviors, and monitoring their access just like any employee. The challenge? AI can work 24/7, scale rapidly, and potentially act without full contextâcreating entirely new vectors for risk.
Why Privileged Access Must Be Tightly Controlled
Privilege escalation remains one of the most dangerous attack methods. If an AI agent, whether maliciously manipulated or unintentionally misconfigured, gains unauthorized access to sensitive systems, the damage could be catastrophic. Companies must implement zero-trust principles and enforce least-privilege access for all entitiesâhuman or not.
The Compliance Angle
In regulated industries, failing to manage AI identities properly can lead to compliance violations. GDPR, HIPAA, and emerging AI-specific regulations are beginning to hold companies accountable for how machine agents interact with data. A solid IAM system is the foundation for demonstrating compliance.
Human-AI Collaboration Demands Transparency
When humans and AI collaborate, transparency in responsibilities and actions is essential. Identity management plays a key role in ensuring accountability, particularly in audit trails. Who did whatâwas it a person or an AI? IAM makes that question answerable.
Automation with Guardrails
While automation promises efficiency, it must come with security guardrails. AI agents need clear guidelines about what they are authorized to execute. Dynamic identity governance tools that use behavioral analytics can detect anomalies and shut down rogue actions before harm is done.
The Road Ahead
Going forward, we expect identity management to evolve into a hybrid model where identity, context, and behavior come together to form adaptive access control. Machine learning can assist in detecting outliers and reducing false positives, while robust policy frameworks ensure predictability.
In essence, companies must accept that AI agents are not just background toolsâthey are active digital entities with identities that need to be governed accordingly.
â Fact Checker Results
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AI agents are increasing in enterprise use â Verified by multiple industry reports.
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Identity management extends to non-human entities â Supported by cybersecurity best practices.
â AI agents donât need oversight â False. Without oversight, they pose major risks.
đŽ Prediction
As AI agents continue to evolve and integrate deeper into enterprise operations, we predict that identity and access management will become the centerpiece of digital security strategies. Companies that fail to implement AI-specific IAM protocols will be at greater risk of both cyberattacks and regulatory penalties. Expect a surge in AI governance tools, with startups and established cybersecurity firms alike launching new solutions to address this urgent need.
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