Key question New
How can organizations continuously evaluate and maintain artificial intelligence systems after deployment?
Artificial Intelligence & Automation
What it means for you
- CIO / IT Executive Allocate Q3 budget to build or procure an MLOps platform featuring model traceability, automated deployment, annotation, and real-time performance monitoring tools.
- IT Manager Schedule an inventory of all deployed operational AI models to audit their current performance drift and verify if automated deployment pipelines are active.
- Business Strategist Draft a mandatory evaluation plan and risk assessment framework for all upcoming AI projects, ensuring alignment with EU AI Act post-market monitoring requirements.
- Researcher Design a blind sampling protocol and reflective human oversight process to test live AI models against shifting real-world user behaviors and data drift.
- Policymaker Mandate structured, ongoing post-market monitoring and traceability requirements for high-risk AI deployments based on the X-RAI continuous evaluation framework.