Case Study — From Fragmented Experiments to Enterprise AI Strategy | StatusGo
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Case Study

From Fragmented Experiments to Enterprise AI Strategy

How a leading health plan aligned $20M–$50M in AI investment around one cohesive vision, in under 12 weeks.

$20–50M
AI investment aligned
12 wks
Strategy to roadmap
25+
AI Capabilities prioritized
8
Functions aligned
The Challenge

AI Without a Strategy Is Just Spending

Context: The organization was investing in AI, but lacked a single answer to "why AI" and "what first."

AI initiatives were growing across Marketing, Operations, Care Management, and IT. Each group had different priorities, vendors, and success definitions. The result was predictable: duplication, internal friction, and leadership hesitation to commit capital at scale.

  • Leadership lacked a shared enterprise vision for where AI should create value first.
  • Ownership was fragmented, which created redundancy and slowed decision-making.
  • Investment flowed to visible pilots instead of high-impact enterprise capabilities.

The mandate was clear: stop experimenting and start scaling.

Our Approach

Strategy First. Technology Second.

We partnered with cross-functional leaders to build an enterprise AI strategy grounded in measurable outcomes, not tooling preferences. The goal was to create a shared fact base, align decision rights, and produce a roadmap leadership could fund and defend.

In 12 weeks: We aligned leadership around a single enterprise strategy and a three-horizon execution roadmap.

  • Current-state diagnostic: We mapped where AI was already in use, where manual inefficiencies were highest, and where experience fragmentation was costing the most.
  • Enterprise pillars: We defined five strategy pillars tied to outcomes, including growth, medical cost reduction, and administrative efficiency.
  • Prioritization and sequencing: We ranked 26 capabilities by time-to-value, technology maturity, and enterprise readiness, producing a three-horizon roadmap.
The Impact

From "Why AI?" to "What, When, and Who Owns It"

The engagement produced a board-defensible strategy and the organizational alignment required for execution at scale. Investment shifted from fragmented pilots to deliberate, outcome-linked capital allocation.

  • $20M–$50M in AI investment aligned to a single enterprise vision and roadmap.
  • Eight senior leaders aligned around clear priorities, sequencing, and ownership.
  • 26 capabilities prioritized across growth, operations, and care management with a clear delivery path.

Outcome: Coordinated execution replaced fragmented experimentation.

Why It Worked

Alignment Was the Product

Most AI strategies fail because the organization is not aligned, not because the technology is unavailable. We treated alignment as the primary deliverable and the roadmap as the mechanism.

Leadership could fund decisions, assign ownership, and execute with confidence because the strategy was built with them, not presented to them.

  • Cross-functional workshops replaced siloed steering committees.
  • A shared fact base eliminated competing narratives about AI readiness.
  • Prioritization used objective criteria, not departmental politics.
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