- InsightAI Risk Management
AI in internal audit: the modern audit plan, powered by models
AI is reshaping every phase of the internal audit lifecycle — from risk scoping and sampling to fieldwork automation, anomaly detection, and continuous monitoring. This deep dive examines the use cases gaining traction, the vendor categories enabling them, and the questions audit leaders should be asking before they buy.
- InsightAI Risk Management
AI in Risk Management: From Detection to Decision
A buyer's guide to enterprise AI across credit, operational, market, and emerging risk — where the technology is mature, where it is not, and how risk leaders should evaluate vendors.
- ToolAI Risk Management
Agent Safety Readiness Assessment
An interactive tool to assess the maturity and readiness of enterprise AI agents regarding safety governance, risk mitigation, and operational controls. Provides a scored evaluation with improvement guidance.
- InsightAI Risk Management
Hallucination Insurance and Indemnification: Vendor Negotiation
This insight examines the emerging concept of hallucination insurance and indemnification clauses related to large language model (LLM) outputs. It provides legal and procurement teams with frameworks and negotiation strategies to address hallucination risks in vendor contracts.
- ToolAI Risk Management
Building a Model Inventory for Risk Management
A gated worksheet template to help enterprises develop a structured model inventory, supporting effective risk management and compliance in AI deployments.
- ComparisonAI Risk Management
Hallucination Risk by Industry: Healthcare vs. Marketing vs. Code
Hallucination in large language models (LLMs) presents varying risk profiles depending on industry context. This comparison evaluates tolerance levels for hallucinated outputs within healthcare, marketing, and software development, identifying operational impacts and mitigation priorities.
- InsightAI Risk Management
Legal Liability for Hallucination: Who Pays When the Model Lies?
This essay examines the legal and contractual frameworks around accountability for hallucinations in large language models (LLMs). It analyzes how enterprises can allocate risk and pursue indemnification when AI-generated inaccuracies cause harm or financial loss.
- PlaybookAI Risk Management
Model Remediation Playbook: When Models Fail Compliance
This guide outlines a systematic approach for enterprise teams to address AI model compliance failures, covering initial detection, impact assessment, remediation strategies, and prevention measures. It is designed for AI risk officers, platform engineering leads, and compliance managers managing regulated AI deployments.
- ToolAI Risk Management
Model Risk Management Maturity Assessment
Evaluate your financial services organization's maturity level in model risk management with this detailed assessment. Understand areas for improvement and benchmark your practices against industry standards.
- GuideAI Risk Management
Third-Party Model Risk: Assessing Vendor Models
This guide provides procurement and risk teams with a structured framework to assess risks associated with third-party AI models. It covers key evaluation criteria, due diligence practices, and ongoing monitoring to manage vendor-related model risks.
- Lexicon entryAI Risk Management
AI Risk Management
Understand AI Risk Management for the enterprise — a structured approach to identifying, assessing, and mitigating the unique risks associated with developing and deploying AI systems.