구매 담당자의 필수 과제 : GRC 및 TPRM 환경에서 AI를 평가, 선정 및 도입할 수 있는 기회를 놓치지 않는 방법

This IDC Perspective discusses how to evaluate, select, and deploy AI in GRC and TPRM environments before your window closes. Your organization is approaching a critical inflection point at which AI-generated information volumes, accelerating cyberattack life cycles, and a deepening talent shortage will soon make human-in-the-loop workflows operationally unsustainable. While regulatory frameworks and your own risk culture currently demand human accountability for consequential GRC decisions, clinging to this requirement beyond its useful life will become an operational liability within two to three years.The platforms you select today must demonstrate that AI autonomy is earned incrementally through auditable performance records - tracking decision accuracy, override rates, concurrence trends, and explainability standards across risk scoring, vendor assessment, audit management, and AI governance activities. Require your vendors to present automation not as a binary switch, but as a graduated, reversible, risk-stratified progression with built-in reassessment checkpoints that your practitioners control.Your own data environment is equally consequential; AI operating on your incomplete or stale GRC data will be rejected by your experienced practitioners regardless of platform sophistication. Demand that your vendor deliver transparent, plain language communication of AI performance - including honest acknowledgment of limitations - as a nonnegotiable foundation for building durable confidence across your team.When evaluating technology suppliers, treat native AI performance instrumentation, role-aware automation notifications, and a credible autonomous operations road map as core procurement requirements, not differentiating features."AI autonomy in GRC isn't a leap of faith - it's a performance record. Demand the evidence, validate the outcomes, and authorize trust incrementally. The organizations that hold their vendors to this standard will define the next era of risk management," says Phil Harris, research director, Governance, Risk, and Compliance Solutions, IDC.

Executive Snapshot

• Key takeaways
• Recommended actions

Situation Overview

• New market developments and dynamics
• AI characteristics and activities for measured automation readiness in GRC/TPRM platforms
  • Decision quality and accuracy metrics
  • Third-party risk management-specific activities
  • Audit management-specific activities
  • AI governance-specific activities
  • Workflow and process execution metrics
  • Data quality and integrity activities
  • Explainability and transparency metrics
  • Human-AI interaction and trust metrics
  • Automation-readiness notification trigger criteria
  • Presenting the automation-readiness question: What buyers should expect from their platforms
    • Confidence-based-readiness notifications
  • Scope-bounded automation proposals
  • Graduated autonomy with automatic check-in intervals
  • Risk-stratified automation lanes
  • Peer benchmarking context
  • Plain language explainability summaries
  • Reversibility assurance messaging
  • Role-based framing for different stakeholders
    • "What could go wrong?" Transparency panel

Advice for the Technology Buyer

• What technology buyers should demand from suppliers

Learn More

• Related research
• Synopsis