Firms Can't Quantify Their AI Exposure

Partners, risk committees, and insurers ask how exposed the firm is to unmanaged AI, but the answer is spread across IT tickets, policy surveys, and anecdote. Without a combined measure, firms cannot prioritize investment or demonstrate progress. PointGuard AI combines discovery, posture findings, and adversarial testing into one exposure score that leadership can track over time.

AI risk is discussed often but rarely measured.

• No single inventory of firm AI use exists.
• Posture and testing results sit in separate tools.
• Leadership needs a number, not a list of findings.
• Clients and insurers ask for evidence of control.

AI Security Posture Mgt., AI Discovery & Inventory, and AI Red Teaming feed a combined exposure score.

1. Inventory AI use. Discover tools, agents, and platforms across the firm, with owners and data access.

2. Assess posture. Evaluate configurations, credentials, and access for each AI platform.

3. Test resilience. Run adversarial tests against firm AI applications and agents.

4. Score and report. Combine results into one exposure score by practice group and track it for leadership, clients, and insurers.

• OWASP Top 10 for LLMs: LLM02 Sensitive Information Disclosure and LLM06 Excessive Agency, supporting measurement of data exposure and excessive authority.
• OWASP Top 10 for Agentic Applications: ASI03 Identity and Privilege Abuse and ASI10 Rogue Agents, addressing unmanaged identities and agents outside governance.
• NIST AI RMF: GOVERN sets risk tolerance; MAP inventories uses; MEASURE scores exposure; MANAGE prioritizes remediation.