Artificial intelligence is rapidly becoming a strategic priority for health plans. From automation to predictive analytics, AI promises efficiency, cost reduction, and competitive advantage.
But there’s a problem.
And it’s one that CFOs are starting to feel in their budgets.
In her recent article published in Healthcare IT Today, our CEO, Megan Schmidt, explores a critical issue that many organizations are overlooking: AI initiatives in health plans are being built on fragmented, incomplete, and poorly structured data foundations.
The result?
- ➔ Escalating implementation costs
- ➔ Missed ROI targets
- ➔ Operational inefficiencies
- ➔ Increased financial risk
AI is only as powerful as the data that fuels it. When data is siloed across systems, inconsistent in format, or lacking governance, AI investments struggle to deliver measurable value. For finance leaders, that translates directly into higher spend without proportional return.
In the article, Megan outlines:
- ✅ Why AI underperformance is often a data architecture issue
- ✅ How CFOs can better evaluate AI investment risk
- ✅ The financial impact of fragmented health plan data
- ✅ What organizations must fix before scaling AI initiatives
This is not just a technology conversation; it’s a financial strategy discussion.
If your organization is investing in AI, this is a must-read.
Read the full Healthcare IT Today ARTICLE.
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