AI Agent Risks in Enterprise
The essential risk dimensions enterprises need to address to deploy AI agents safely at scale, spanning operational, security, and regulatory risks
Harbor provides a three-dimensional view of agent risk:
Risks arising from how AI agents perform tasks, make decisions, and interact with enterprise systems and processes.
Risks involving data access, handling, confidentiality, integrity, and exposure to security threats.
Risks arising from non-compliance with applicable laws, regulations, standards, and legal obligations.
Our risk framework provides a complete view of agent risk, built on:
Built on frontier research into agentic AI risk, with input from the Stanford Center for AI Safety and research at the leading edge of the field.
Shaped through use cases and failure modes observed through work with our enterprise partners deploying AI in real environments.
Mapped to EU AI Act, GDPR, Product Liability Directive, ISO/IEC 42001, NIST AI RMF, OWASP Top 10, and MITRE ATLAS.
Custom risk scoping to your agent and enterprise:
The agent’s capabilities, autonomy, tools, permissions and data access. An agent that reads documents carries a different risk from one that moves money.
The risks, standards and rules of the agent’s industry, such as HIPAA in healthcare or SR 26-2 in banking.
The laws that apply where the agent, its data and its users are: the EU AI Act and GDPR in Europe, CCPA/CPRA and FTC rules in the U.S.
To guide risk mitigation, we group risks into two categories:
Risks arising from how the AI agent is built, operates, connects to systems, and can be manipulated or compromised.
Risks arising from how the company deploys, oversees, controls, and is accountable for the AI agent and its outcomes.
Harbor provides a three-dimensional view of agent risk:
01 Operational
Risks arising from how AI agents perform tasks, make decisions, and interact with enterprise systems and processes.
02 Security
Risks involving data access, handling, confidentiality, integrity, and exposure to security threats.
03 Regulatory
Risks arising from non-compliance with applicable laws, regulations, standards, and legal obligations.
Our risk framework provides a complete view of agent risk, built on:
Frontier Research
Built on frontier research into agentic AI risk, with input from the Stanford Center for AI Safety and research at the leading edge of the field.
Enterprise Partners
Shaped through use cases and failure modes observed through work with our enterprise partners deploying AI in real environments.
Leading AI Frameworks
Mapped to EU AI Act, GDPR, Product Liability Directive, ISO/IEC 42001, NIST AI RMF, OWASP Top 10, and MITRE ATLAS.
Custom risk scoping to your agent and enterprise:
Agent Architecture
The agent’s capabilities, autonomy, tools, permissions and data access. An agent that reads documents carries a different risk from one that moves money.
Industry
The risks, standards and rules of the agent’s industry, such as HIPAA in healthcare or SR 26-2 in banking.
Regulatory Jurisdiction
The laws that apply where the agent, its data and its users are: the EU AI Act and GDPR in Europe, CCPA/CPRA and FTC rules in the U.S.
To guide risk mitigation, we group risks into two categories:
Technical
Risks arising from how the AI agent is built, operates, connects to systems, and can be manipulated or compromised.
Governance
Risks arising from how the company deploys, oversees, controls, and is accountable for the AI agent and its outcomes.
Let’s insure the agents you deploy
See the full risk framework
Explore the complete set of enterprise AI agent risks, including the dimensions, individual risks, and underlying methodologies
View Framework
See how we apply it to your enterprise
We scope the framework to the agents, usecases, and regulatory environments that matter to your organization
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