Since the debut of ChatGPT in 2022, we’ve speculated that new GenAI tools could supercharge the day-to-day research and planning work of strategy teams. In practice, fluency with these tools varies widely, and some health systems have been reluctant to leverage these powerful but often unreliable tools for sensitive work. The future of strategy planning is here, it’s just not evenly distributed.
To learn more about how strategy teams are using GenAI, we asked a half dozen health system strategy leaders about their most valuable use cases and how they’re preparing for the future. The clearest payoff so far is research and competitive intelligence: sizing up markets, profiling competitors, and reaching a point of view on acquisition targets faster than before. But respondents also flagged common barriers: limited time to practice, messy AI outputs that need extensive cleanup, and limits on which tools are sanctioned for official use.
Here’s what they had to say, anonymized for confidentiality:
Large multi-hospital system, South Central US
Most valuable use case: “The biggest benefit so far is in research. As we think about what differentiates us in this market, how we consider new capabilities or services, and what competitors might be primed to be acquired, AI really helps us to more quickly assess the market, answer our questions, and provide us with a point of view that we haven't had previously.”
How they’re preparing for the future: “Frankly, like everyone we are trying to build time in our week to practice with the tools we have. So far, we haven't identified any new tools that we feel we need. It's more about practicing, refining, and sharing what we learn with our colleagues. This is an area that we continue to struggle with just based on how much work there is.”
Large academic medical center, Midwest US
Most valuable use case: “The most impactful use case has been a purpose-built strategy assistant with a knowledge base specific to the team and organization. It has significantly accelerated complex deliverables from concept to draft, for example partnership and business planning materials, from a structured outline, to a full written business plan in the standard template, to a preliminary five-year ROI model. Work that took days can now advance much faster, leaving more time to refine ideas, validate assumptions, and engage stakeholders.”
How they’re preparing for the future: “The team is hosting an upcoming session on its future vision for AI and how to build thoughtful engagement across the team. Members are experimenting with workflows and documenting lessons learned, and intend to keep learning from one another across the end-to-end process (prompt development, evaluating outputs, refining deliverables, and identifying where AI best supports complex work) while preserving the human judgment and expertise essential to the role.”
Large multi-state integrated system, Southeast US
Most valuable use case: “Our most valuable use is competitive intelligence research to create hospital profiles of regional competitors. It is collaborative rather than delegation-oriented. The value comes less from raw draft speed and more from building source and citation verification discipline directly into the output requirements. We built a reusable profile method that assigns a footnote and confidence tier to each source, with footnotes linking to the sources for quick verification, so the output shows its work. The result is executive-facing deliverables that are faster to review and enhance toward publishing. That is the only version of "faster" that matters for C-suite recommendations.”
How they’re preparing for the future: “We think a lot more about how we organize, store, and model data as the foundation for both traditional automation and emerging AI pilots. Dashboards, workflows, and agents are only as reliable as the structures beneath them, and ad-hoc spreadsheets and "final_final_v3" files cannot support that. We are piloting how to connect data sources of truth with SharePoint and Power Query connectors so spreadsheets refresh from an identified "official" source. Biggest challenge: enterprise LLM deployment inside a large corporate environment is far more cumbersome than consumer-facing tools, which will be a structural challenge for adoption, alongside stitching together trusted data across silos and permissions.”
Academic health system, Northeast US
Most valuable use case: “We initially thought AI would be most valuable for logistics and project management tasks such as meeting notes and agenda preparation, but we've slowly moved away from those since it often took more editing and cleanup than initially thought. The real value is in using AI to develop scoping documents, strategic frameworks, and risk-benefit analyses to enable senior leadership decision-making. We didn't need AI to do this work per se, but the speed and effectiveness with which it turns out these work products has enabled productive, timely, and thoughtful discussion.”
How they’re preparing for the future: “We are all working to hone our prompting skills and assessment of output. We tested the Copilot tools within the Microsoft suite and piloted a collaborative Copilot capability that was a game changer for slide deck preparation, though adoption is expensive, so we are working with our Digital/AI team to maximize the tools we already have. These tools have become a significant part of our day to day and allow our small team to produce a very high volume of work. We are eager to find new and better ways to use them.”
Large multi-state integrated system, West US
Most valuable use case: “The most valuable use case has been rapidly synthesizing research, stakeholder feedback, and strategic inputs into executive-ready narratives and frameworks. It has reduced the time to move from information gathering to strategic insight, freeing me to focus on decision-making and stakeholder engagement. Quick example: checking an outline against an entire folder of inputs to ensure I have covered the waterfront from every group I consulted.”
How they’re preparing for the future: “I am intentionally integrating AI into my daily workflows and experimenting with increasingly sophisticated use cases beyond drafting and summarization. I am investing time in understanding agentic AI and how strategy teams can redesign work to pair human judgment, creativity, and relationship-building with AI-powered analysis. Quick example: a monthly all-hands "learning moment" where team members share how they used our tools that month to spread best practices quickly.”
Community-based system, Mid-Atlantic US
Most valuable use case: “AI is becoming an increasingly integrated part of our strategic planning process. We use GenAI to quickly research industry trends, synthesize market intelligence, develop first drafts of planning content, and accelerate executive-ready deliverables. As a result, the team spends less time gathering and organizing information and more time assessing strategic implications, prioritizing opportunities, and supporting leadership decision-making.”
How they’re preparing for the future: “We are encouraging the team to use organization-sanctioned tools and looking at what products may become more available to support the strategic planning process.”
Health system, Northeast US
Most valuable use case: “Our most valuable use case for generative AI has been in helping to build out frameworks and models to assess certain opportunities or components of strategic planning. While the tool hasn't been particularly helpful in producing the actual models, it has been helpful in framing methodologies and helping to find research to support assumptions we are making. Though we have had to do a lot of verification of sources and numbers as it tends to hallucinate and share inaccurate or made-up research/numbers at times!”
How they’re preparing for the future: “Our strategy team has been consistently preparing for the impact of AI in the future. We're using the tools in our day-to-day work, experimenting with different use cases, and working on our fundamental AI skills (e.g., prompting). We are limited right now with the tool we have (Copilot) but are constantly thinking about how a strong generative AI tool could contribute to our team's work. It's part of our department priorities to integrate AI into our work to help make processes more efficient and improve the outputs. We certainly have a journey ahead of us for optimizing our use of AI and the tools we have access to, but it's something we're excited about and consistently planning for given the inevitability.”
Interested in connecting with one of the strategy leaders quoted above? Reach out to us at StrategyCatalyst@hmacademy.com