Applications Due 10/30/2026

AI Learning Collaborative

Use Case 2: AI-Enabled Workflows for Quality Measurement

Artificial Intelligence (AI) is rapidly reshaping health care. From supporting timely, consistent, and accurate utilization management decisions, to improving data quality and accelerating quality measurement, AI is already influencing how care is delivered and managed.

NCQA’s AI Learning Collaborative will help organizations adopt and evaluate AI-enabled workflows with quality, safety, equity, transparency, and accountability. The Collaborative will run in cycles focused on specific high impact use cases. Each use case follows an 8-month peer learning model that helps organizations build foundational knowledge, generate evidence, implement changes, and scale successful approaches. The Collaborative’s first use case, AI in Prior Authorization, is set to kick off in Fall 2026, with participant recruitment now complete. NCQA is now accepting applications for its second use case, AI-Enabled Quality Measurement. A third use case, AI-Empowered Care Management, is planned for January 2027.

Applications are now open for the second use case, AI-Enabled Workflows for Quality Measurement. This Learning Collaborative focuses on how organizations can create high-quality, trustworthy, timely, and accurate AI-enabled quality measurement workflows that improve the quality of both measurement processes and outputs, enabling better insights to support quality improvement, ratings, and payment programs. This will be an eight-month learning program. Additional information about the learning collaborative can be found here.

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Benefits of Program Participation

  • Help shape and gain access to a living leading-practices playbook that outlines practical approaches for implementing AI-enabled quality measurement workflows, including a framework for monitoring outcomes.
  • An NCQA anonymous quantitative and qualitative assessment of your organization’s AI-enabled quality measurement workflows. The assessment will compare your approach against emerging leading practices and provide de-identified, aggregate benchmarking against participating peer organizations, as permitted under the participation agreement.*
  • Regular opportunities to learn from your peers and gain insight into implementation challenges and solutions.

*Please note: information collected as part of the Learning Collaborative will be de-identified, used in aggregate, and treated as confidential, in accordance with participation agreements.

Cost

$25,000 per organization

This learning collaborative is a paid opportunity, costing $25,000 per organization. Community-based plans or health plans with fewer than 500,000 members may be eligible for a discounted fee. If your organization meets these requirements and is interested but unable to pay the full fee, please reach out to ai@ncqa.org.

Eligibility

Organizations implementing or supporting AI-enabled quality measurement workflows are eligible to apply, including health plans, vendors, and joint health plan-vendor teams. Table 1 includes expectations for organizations and partnerships seeking to join the collaborative and Figure 1 outlines the quality measurement workflow stages that are the focus of this cohort. Selection will balance multiple organizational characteristics including stages of maturity, organizational size, populations served and lines of business. Organizations using synthetic data will not be accepted for this Collaborative.

Table 1: Expectations for Organizations & Partnerships Applying to the Collaborative

Table 1: Expectations for organizations and partnerships applying to the Collaborative — entry paths and who brings the data.

NCQA position on data, IP and licensing: arrangements between a plan and its vendor are for those parties to work out; each participant must bring baseline and post-implementation data for comparative evaluation.
Figure 1: AI-Enabled Workflows for Quality Measurement

Figure 1: AI-enabled quality measurement workflow stages — Measure Specification, Event Detection, External Source Engagement, Normalize and Map, Measure Logic Applied, Measure Calculation / Spec Execution, Aggregation / Submission, and Evaluation of Quality Signals, with governance oversight and monitoring ongoing at each step.

Accepted organizations are expected to:

  • Attend Regular Collaborative Meetings: including orientation, kick off, discussion-based meetings, office hours and 1:1 conversations.
  • Share Information: share outcomes metrics, participate in surveys and interviews about workflow and processes
  • Share Knowledge: openness about challenges, opportunities, and lessons learned from your AI journey are critical for participating in this collaborative. All members must be willing to share their experience and actively listen to others, fostering a culture of peer learning.
  • Commit the Appropriate Resources: organizations should commit a small, cross-functional team (ex. Project managers, technical and operational team members, executive sponsors) to support this work, with an estimated total commitment of 8–10 hours per month across the team, not per individual team member.

Applicant and Participant Expectations

Applicants selected for participation will be expected to:

  • Submit a complete application by 10/30/2026.
  • Identify and commit resources to support participation.
  • Garner the necessary internal buy-in to sign a contract within two months of acceptance and remit payment within 60 days of contract signature.
Want to learn more or have questions about the application process?

For questions about the Collaborative or application process, please contact ai@ncqa.org

APPLICATION STARTS HERE:

Before you begin

The questions below are intended to assess program fit, support development of a balanced cohort, understand each organization’s starting point, tailor Collaborative discussions, and establish an initial baseline for participating organizations.

This application asks for information about AI implementation and operational capabilities. Application responses will be treated as confidential and reviewed only by NCQA for participant selection and related planning. Responses will not be shared outside the selection process.

To reduce burden and protect sensitive operational details, this public application focuses on initial fit and readiness information. NCQA may request more detailed metrics-availability information through a confidential follow-up after initial application review, selection, or contracting.

Please answer the questions below to the best of your ability. If a question is not applicable or information is not yet available, note that in your response.