Winner: 2026 Work Innovation Leader, AMER 

This award recognizes Aetna, a CVS Health Company, for its pioneering use of AI-powered workflows to modernize portfolio governance in a highly regulated healthcare environment. By embedding AI directly into the architecture of intake, prioritization, and risk management, Aetna has established a new enterprise benchmark for operational efficiency and execution discipline at scale.

The Medicaid SPMO’s partnership with Asana has been a catalyst for meaningful operational change. By embedding AI‑driven workflows into our intake, prioritization, and governance processes, the team has increased capacity, improved execution discipline, and delivered measurable business value in a highly regulated environment. Our transformation with Asana has allowed us to scale responsibly, support growing demand, and make better decisions faster without increasing organizational complexity. The results reflect both the power of the platform and the strength of the team leading this work.

Gregory Miller

Executive Director, Medicaid Strategic Project Management Office

Stage 1: Strategic intake and discovery 

Previously, the SPMO’s intake process relied on manual tools and context switching, making it difficult to maintain consistent information as project volume increased. They solved this by implementing an AI-enabled intake engine that ensures a standardized baseline before evaluation begins. By using AI to bridge the gap between raw request data and formal project charters, the team reduced the risk of misaligned investments and manual review bottlenecks.

• Standardized baseline: Every requester completes a formal project charter capturing scope, objectives, and risks before work can advance. 

• AI-led call prep: AI Studio reviews intake and charter data to create tailored discovery questions, helping project managers enter conversations with sharper prompts and reduce the need for follow-up meetings to clarify scope. 

• Hybrid data model: Select charter data is captured in Asana to support visibility, while a centralized spreadsheet preserves the evaluation rigor required for a regulated portfolio. This hybrid model preserves evaluation rigor while enabling downstream AI analysis. 

• Intake evaluation and decision support: AI Studio reviews intake data, supports routing decisions, and generates summaries with clear, documented rationale — with human judgment remaining central throughout.

The most transformative element is the AI’s ability to read project charter data from Excel and apply it across decision points like discovery and staffing. This shifted AI into a scalable decision-support engine that ensures we aren't constantly fixing things later.

Jeffrey Webb

Ld. Director, Medicaid SPMO

Stage 2: Prioritization and portfolio alignment

Portfolio routing and prioritization previously required extensive manual coordination and subjective decision-making, slowing time to funding and execution. Aetna implemented AI Studio to standardize how intakes map to enterprise goals and provide a documented rationale for portfolio assignment, ensuring every project is governance-ready.

• Connects work to strategic goals: AI Studio automatically aligns every intake with the defined company goals, ensuring consistent goal tracking across the portfolio and supports more informed prioritization.

• Portfolio validation and documentation: AI checks the charter and intake record to validate portfolio fit and produces a clear rationale to enable efficient board review and handoff.

• Governance‐ready intake package: AI prepares a governance‐ready intake package so the initiative can move cleanly into funding review, resourcing, and execution.

• Human-in-the-loop oversight: All AI-generated insights and recommendations are reviewed and validated by PMO leadership to ensure human judgment remains central.

We just needed intake and evaluation to be cleaner and more consistent. By using AI to apply consistent evaluation logic and justify portfolio alignment, we reduced back-and-forth and made it easier to get work ready for review without extra process.

Jeffrey Webb

Lead Director, Medicaid SPMO

Stage 3: Execution, risk oversight, and reporting

Managing in-flight projects was formerly inconsistent, particularly for risk, issue, change, and decision (RAID) tracking. Aetna replaced this administrative friction with an AI-augmented execution model that standardizes how execution health is communicated. This ensures that leadership has timely visibility into project health across the portfolio, reducing exposure to compliance issues and delivery delays.

• Standardized RAID management: AI helps structure RAID entries by generating clear, executive-ready descriptions and mitigation language, making them easier to review and escalate.

• Phase summary automation: AI Studio researches project updates and RAID data to create consistent phase summaries, saving 468 hours annually.

• Lowered barrier to entry: Making RAID capture fast and consistent encourages teams to log items early rather than avoiding the process altogether.

• Clearer execution visibility: Standardized reporting allows stakeholders to quickly understand project health without relying on project-manager-specific interpretation.

If logging risks feel heavy, people won’t do it. The goal was to make RAID capture fast and consistent, so it becomes part of normal execution. By reusing that data to generate status summaries, we improved risk visibility without adding manual rework.

Jeffrey Webb

Lead Director, Medicaid SPMO

Before this transformation, the Aetna Medicaid SPMO relied on manual reconciliation and subjective routing to move complex initiatives through governance. By building an AI-powered intake and execution engine in Asana, the organization has shifted its culture from manual documentation to data-driven decision-making. As the team continues to scale and manage an increasingly complex Medicaid portfolio, its AI-augmented infrastructure ensures that governance rigor, regulatory compliance, and member impact grow together.