Case Study

AI Strategy & Transformation Roadmap

Healthcare • Mid‑Market Organization

The Challenge

The organization had invested heavily in analytics tools, but teams were working in silos, producing conflicting metrics and inconsistent insights. Leadership lacked a unified AI strategy, and no clear roadmap existed for scaling predictive capabilities across the enterprise.

Without alignment on data governance, KPI definitions, or AI readiness, the organization struggled to prioritize use cases, evaluate value, or build trust in analytics‑driven decision‑making.

What We Found

Through interviews, system reviews, and a deep dive into existing analytics workflows, we uncovered several root causes behind the organization’s fragmented decision‑making and stalled AI initiatives.

  • Teams were defining KPIs differently, leading to conflicting reports and eroded trust.
  • Data pipelines lacked standardization, making predictive modeling difficult to scale.
  • No formal governance existed to evaluate, prioritize, or fund AI use cases.
  • Analytics talent was distributed across the business with no unified operating model.

Our Approach

We designed a structured, enterprise‑grade approach that aligned leadership, standardized decision‑making, and established a scalable foundation for AI adoption across the organization.

AI Readiness Assessment

We evaluated analytics maturity, data quality, governance gaps, and organizational alignment. This revealed inconsistencies in KPI definitions, data ownership, and predictive modeling readiness.

Enterprise AI Operating Model

We designed a unified operating model that clarified roles, responsibilities, and decision rights across analytics, engineering, and business teams—creating a scalable framework for AI adoption.

12‑Month AI Roadmap

We built a prioritized roadmap sequencing foundational data work, governance improvements, and high‑value AI initiatives—each evaluated for feasibility, impact, and strategic alignment.

The Outcomes

The organization gained clarity, alignment, and a scalable foundation for AI adoption. Leadership now had a unified strategy, a clear roadmap, and the confidence to invest in high‑value initiatives.

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    40% reduction in redundant analytics work across business units

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    A 12‑month AI roadmap adopted by executive leadership

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    AI use cases prioritized and funded across three business units

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    A unified operating model that improved trust in analytics and decision‑making

Why It Mattered

With a unified strategy, a clear operating model, and a prioritized roadmap, the organization finally had the structure and alignment needed to scale AI responsibly. Leadership gained confidence in where to invest, teams had clarity on how to execute, and the business established a foundation for long‑term, intelligence‑driven transformation.

Ready to Build Your AI Strategy?

If you’re exploring how to modernize your data foundation, align leadership, or build an AI roadmap, let’s talk. Every engagement is founder‑led and tailored to your organization’s goals.

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All client details have been anonymized to protect confidentiality while preserving the integrity of the outcomes and approach.