Many Companies Haven’t Assessed Agentic AI Risks, Survey Reveals

TL;DR:

  • Significant proportion of companies deploy AI agents without risk assessment
  • Gap between implementation speed and governance development
  • Security, data protection, and operational risks remain unaddressed
  • Autonomous AI decision-making creates new threat surfaces
  • Urgent need for comprehensive AI agent risk frameworks

A substantial number of organisations are implementing agentic AI systems—autonomous agents capable of independent decision-making and action—without conducting comprehensive risk assessments, according to recent survey findings. This deployment-first, governance-later approach creates significant security and operational vulnerabilities.

The Assessment Gap

Agentic AI represents a fundamental shift from passive AI systems that respond to queries toward autonomous agents that initiate actions, make decisions, and interact with systems independently. These capabilities introduce risks qualitatively different from traditional AI applications, yet many organisations proceed with deployment before establishing appropriate governance frameworks.

The survey reveals that companies recognise AI agents’ strategic value but underestimate the complexity of managing systems that can operate without continuous human oversight. This creates a dangerous gap between technological capability and organisational preparedness.

Unaddressed Risk Categories

Security Vulnerabilities: AI agents with system access and decision-making authority create new attack surfaces. Without proper assessment, organisations may not understand how compromised agents could affect infrastructure, data, or operations.

Data Protection: Autonomous agents that access, process, and share sensitive information require rigorous data governance. Insufficient risk assessment leaves organisations exposed to privacy violations and regulatory non-compliance.

Operational Risks: Agents that can initiate transactions, modify systems, or communicate externally without human approval require fail-safes and oversight mechanisms. Deploying without these controls invites operational disruption.

Accountability Gaps: When autonomous systems make decisions affecting customers, employees, or stakeholders, clear accountability frameworks become essential. Many organisations have not established who bears responsibility when agents err.

Why Assessment Lags Behind Deployment

Several factors contribute to the assessment gap:

Technology Velocity: Agentic AI capabilities advance rapidly, creating pressure to deploy quickly to maintain competitive advantage. Risk assessment processes—often slower and more methodical—struggle to keep pace.

Novelty: Traditional risk assessment frameworks designed for passive AI systems don’t fully capture the risks of autonomous agents. Organisations lack established methodologies for evaluating these newer systems.

Skills Shortage: Comprehensive AI risk assessment requires understanding both technical capabilities and organisational context. Many companies lack personnel with this combined expertise.

Path Forward

Addressing this gap requires organisations to develop specific risk assessment frameworks for agentic AI before or alongside deployment. This includes:

  • Mapping agent capabilities and system access
  • Identifying failure modes and their consequences
  • Establishing human oversight mechanisms
  • Creating audit trails for agent actions
  • Defining clear accountability structures

Regulatory pressure will likely accelerate assessment adoption. As governments develop AI governance requirements, organisations that have already established robust risk frameworks will find compliance easier than those playing catch-up.

Implications

The rush to deploy AI agents without comprehensive risk assessment mirrors earlier technology adoption patterns where innovation outpaced governance. However, the autonomous nature of AI agents makes this gap particularly concerning—these systems can affect operations, customers, and stakeholders at scale without continuous human supervision.

Organisations deploying agentic AI responsibly will differentiate themselves not through capability alone, but through demonstrated ability to manage the risks these powerful systems introduce. As the technology matures, effective risk governance will transition from optional best practice to competitive necessity.

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