Project Overview
A regional healthcare system with 14 facilities wanted to adopt AI but did not know where to start. They had seen demos from a dozen vendors, received conflicting advice from consultants, and had no internal AI expertise to evaluate any of it. Leadership knew AI could improve outcomes and efficiency but needed a clear, honest plan before committing budget.
We ran a six-week strategy engagement that included stakeholder interviews across clinical, operations, IT, and executive teams. We assessed their data infrastructure, identified high-impact use cases, and evaluated build-versus-buy tradeoffs for each. The result was a prioritized 12-month roadmap with clear milestones, resource requirements, and risk mitigations.
The roadmap identified three quick-win projects: predictive no-show modeling, automated clinical documentation, and supply chain demand forecasting, alongside two longer-term initiatives requiring data infrastructure investment. Each initiative included a business case with projected ROI and implementation timeline.
The healthcare system used the roadmap to secure board approval for a $2.4M AI investment and hired their first internal AI lead using the job description and team structure we recommended. Six months later, two of the three quick-win projects were in production.
Key Takeaways
- Strategy-led AI drives adoption and board-level buy-in
- Quick wins build momentum for larger infrastructure investments
- Stakeholder alignment across clinical, ops, and IT is essential
- Build-versus-buy analysis prevents costly vendor lock-in
Challenge
The healthcare system had no internal AI expertise and was overwhelmed by conflicting vendor pitches. Leadership needed a clear, prioritized plan before committing budget to any AI initiative.
Strategy
We conducted a six-week engagement with stakeholder interviews across clinical, operations, IT, and executive teams. We assessed data readiness, identified high-impact use cases, and evaluated build-versus-buy tradeoffs.
Solution
We delivered a prioritized 12-month roadmap with three quick-win projects and two longer-term initiatives, each with a detailed business case, ROI projections, and implementation timeline. We also provided hiring recommendations for their first internal AI lead.
Healthcare Engagement
(Confidential)