False Sense of Security: Why Most Companies Overestimate Their AI Protection

Most Companies Overestimate Their AI Security Readiness

A recent study by security provider Delinea exposes a striking gap between how companies perceive their AI security and the actual state of their defenses. While 93% of IT decision-makers believe their AI systems are well-protected against manipulation and attacks, only 44% confirm their security architecture is truly ready for safe AI operation. This survey included over 1,700 IT and security experts from various industries worldwide.

The mismatch highlights a critical issue: many organizations rely on traditional IT security strategies that don’t adequately address the unique challenges posed by AI systems. AI environments introduce dynamic "machine identities" that require active management, yet just 61% of respondents have full visibility into all identities active in their systems.

Identity Governance: A Key Gap

Identity governance is essential for secure AI operations, providing authorization and traceability. However, only 48% of companies currently use identity governance mechanisms effectively. Without these controls, organizations risk unauthorized access and difficulty tracking actions across human and machine users alike.

The Rise of Agentic AI Demands New Security Approaches

Two-thirds of companies have implemented agentic AI—systems that can make decisions and act independently. This autonomy introduces risks such as uncontrolled automation, incorrect decisions, and potential exploitation by attackers. Traditional, rigid role-based security models fall short in managing these risks.

Experts recommend shifting to flexible, risk-based access models that verify and secure every action, whether performed by a human or AI agent. This adaptive approach helps prevent attackers from exploiting identity vulnerabilities to access sensitive data and operations.

Building a Comprehensive AI Governance Model

Delinea urges companies to implement a full AI governance framework that establishes clear guidelines, control mechanisms, and traceability. Such a model integrates AI securely into daily operations and ensures responsible use.

What This Means for Operations Professionals

• Reassess security assumptions: High confidence in current measures doesn’t guarantee protection. Regularly validate your security architecture against AI-specific threats.
• Increase identity transparency: Aim for full visibility over all identities, including machine accounts created by AI applications.
• Adopt identity governance: Implement tools and processes that enforce authorization and enable action tracking.
• Prepare for agentic AI: Move beyond static roles to risk-based, adaptive security models that dynamically verify actions.
• Establish AI governance policies: Develop clear control frameworks to guide AI deployment and management within your organization.

Addressing these points is essential to safely operate AI technologies and reduce exposure to emerging threats. For those looking to deepen their AI security knowledge and skills, exploring targeted courses can be a valuable step. Consider checking out Complete AI Training’s courses tailored to various job roles to build practical expertise.

Final Thought

Companies can’t afford to be complacent about AI security. Confidence alone won’t stop attackers or operational errors. The future of AI in business depends on evolving security architectures, transparent identity management, and governance frameworks that keep pace with AI’s growing autonomy.