As artificial intelligence adoption accelerates across healthcare, organizations are moving beyond conceptual governance frameworks toward operational governance models that can scale. While many institutions have established AI principles, committees, and review processes, fewer have implemented infrastructure capable of supporting governance activities across a growing and decentralized AI portfolio.
This case study highlights how platform-based approaches may help organizations reduce administrative burden, improve documentation quality, and increase portfolio-level visibility, without altering existing AI governance structures.
ABOUT MEMORIAL SLOAN KETTERING CANCER CENTER
Memorial Sloan Kettering Cancer Center (MSK) is one of the world's premier cancer research and treatment institutions. As AI adoption accelerated across the organization, MSK has established a dedicated AI Governance Committee to ensure responsible deployment, safety and oversight.
The MSK Innovation Hub (iHub) serves as Memorial Sloan Kettering's dedicated program for fostering partnerships between the institution and innovative technology companies to advance cancer care. Through the iHub, selected companies gain access to MSK's world-class expertise, clinical insights, and collaborative environment to develop and refine solutions that address real-world challenges in oncology. This program enabled a collaboration between MSK and ALIGNMT AI bringing together MSK's deep clinical and operational expertise in AI governance with ALIGNMT AI's specialized platform for managing responsible AI adoption at scale.
ALIGNTM AI - MSK iHub Collaboration
37%
Overall improvements for AI Governance Workflow
100%
Context centralization achieved for enterprise AI Governance
15
Reduction of out-of-context internal AI review communications
Built around your existing structures
ALIGNMT AI works within governance frameworks you've already established — no major process changes required. The platform reduces manual overhead and surfaces the insights leadership needs.
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Centralized review records
Every document, discussion, and decision lives in a single model record — eliminating context-switching and knowledge silos.
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Real-time portfolio dashboards
Surface model inventory, risk distributions, and approval status at a glance. Decisions made on current data, not last week's spreadsheet.
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Automated compliance workflows
Reduce administrative burden with automated documentation generation, review letter creation, and stakeholder notifications.
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Continuous risk monitoring
Stay ahead of compliance requirements with ongoing risk monitoring and governance documentation built for scale.
