GUIDE AI Fact or Fiction: 10 Questions to Ask MDR Providers About AI Capabilities
Organizations comparing MDR providers often struggle to determine which vendors have AI that is fully operational versus still under development. This eBook, "AI Fact or Fiction: 10 Questions to Ask MDR Providers About AI Capabilities," clarifies these differences by outlining the factors that define a truly production-ready AI system — including real-world operational maturity, how AI supports detection and investigation quality, its role in reducing time-to-resolution, and the importance of transparent roadmaps and human oversight. Download the eBook to help guide smarter decision-making, and contact TSpec for help assessing your MDR options.
Is Your AI System Fully Operational?
It's important to know if the MDR provider's AI is production-ready or still under development. Many vendors may present their AI as mature while it is actually in beta. Look for evidence of real-world application and measurable outcomes, as well as insights into how the AI is currently being utilized in threat detection, investigation, and response.
What Autonomy Does Your AI Have?
Understanding the autonomy of the AI is crucial for effective incident response. Providers should clearly document the specific actions the AI can perform independently, such as endpoint isolation or file quarantine, and outline the role-based approval workflows for high-impact decisions. This ensures that human oversight is maintained, especially for actions that could affect business continuity.
How Do You Ensure AI Decision Transparency?
A mature MDR provider should provide detailed reasoning behind each AI-driven action, avoiding 'black-box' operations. This includes maintaining an evidence trail that explains what actions were taken, why they were taken, and the context behind those decisions. Daily operational summaries and exportable evidence packages can further support compliance and internal reporting needs.
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