Case Study
US Healthcare System: What happens when Microsoft Power Platform grows faster than governance
At a Glance
A large US healthcare organization had become a Microsoft Power Platform power user without anyone really planning for it. Hundreds of automations. Dozens of apps. Thirty-plus AI agents. The platform had grown fast, organically, and mostly without oversight.
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The Problem with Organic Growth
Microsoft Power Platform had become the go-to tool for getting things done. Teams across the organization had embraced it, building flows and apps to solve real problems without waiting for IT. That kind of energy is exactly what citizen development is supposed to unlock.
The challenge is that ungoverned growth has a compounding quality. By the time TQA was engaged, hundreds of solutions had accumulated across the tenant with no shared framework for how they were built, owned, or maintained. Nobody had a complete picture of what was running, who owned it, or what would happen if something broke.
The Default environment alone held hundreds of Power Automate flows, Canvas apps, Copilot agents, and solutions — a sprawl that had built up organically over time, with no lifecycle controls and limited visibility.
Governance infrastructure existed in theory. The organization had invested in Microsoft’s CoE Starter Kit and deployed it across the tenant. But it had never been fully configured, and the monitoring features had never been activated. The gap between having the tools and actually using them is one of the most common — and most consequential — patterns TQA sees in enterprise Power Platform environments.
Understanding the Full Picture Before Acting
Before any governance work could begin, TQA conducted a complete tenant audit — every environment, every solution, every flow, every app, and every agent — mapped against ownership and risk. What mattered as much as the scale of what was found was understanding the right sequence for addressing it. Governance changes in complex, active environments carry their own risks. Getting the order wrong can create more disruption than the problems being solved. The audit gave TQA the foundation to prioritize and sequence the work in a way that reduced risk at every step.
Inconsistent
15+ environments across the tenant with inconsistent governance coverage
Stopped flows
Hundreds of stopped flows and unused apps accumulated in the Default environment
Copilot agents
30+ Copilot agents operating without any AI governance framework
Single point of failure
Hundreds of flows attributed to a single user, representing a critical single point of failure
Inactive
Microsoft CoE Starter Kit deployed but monitoring inactive across all environments
A Governance Model Built to Last
TQA structured the engagement to address risk first, then build the technical infrastructure to sustain governance long-term, then invest in the people and culture layer that determines whether any of it actually sticks.
The governance framework covered environment tiering, Data Loss Prevention (DLP) policies calibrated by risk profile, an end-to-end Application Lifecycle Management (ALM) pipeline from development through testing to production, and a security model aligned to the organization’s regulatory requirements. Every recommendation was designed to be proportionate, practical, and maintainable by the internal team.
The enablement layer was built on the same principle. A complete training curriculum was developed from scratch — fourteen self-paced modules covering the full maker and administrator lifecycle — alongside a champions program and community infrastructure designed to sustain adoption without ongoing external support.
Every deliverable was built as an internal asset. The goal was an organization that could govern, train, and scale its Power Platform program on its own terms.
The training strategy was also scoped around a real constraint: no near-term plan for premium Power Platform licenses. Rather than build a curriculum around capabilities the team could not yet access, TQA designed it for the standard-connector ecosystem available from day one — building adoption momentum on what was immediately usable.
Sprawled to Governed
From Sprawl to Governed, Compliant, and Self-Sufficient
The organization moved from significant, largely invisible platform risk to a fully documented governance model aligned to its regulatory environment. Every environment in the tenant was classified, assessed, and brought into a defined governance tier. DLP policies were established across Production and Default for the first time, and a structured ALM process replaced ad-hoc deployment practices.
The client team ended the engagement owning the program. With a complete training curriculum, a defined ALM process, and comprehensive governance documentation in place, the internal team had everything needed to onboard new makers, promote solutions safely, and maintain compliance as the platform continues to grow. The citizen developer program shifted from an organic, ungoverned phenomenon to a structured capability with clear standards and pathways for participation.
The discovery of ungoverned Copilot agents also prompted the organization to establish a formal AI governance position — an outcome with significance well beyond Power Platform. As AI adoption accelerates across enterprise tools, having that framework in place ahead of scale is the right posture for any regulated organization.
The Results at a Glance
14
Self-paced training
modules built from scratch
5+
governance documents
covering strategy, ALM, DLP, naming and security
15+
environments audited
and brought into a defined governance framework
30+
Copilot agents
surfaced and brought under a formal AI governance position
The Broader Pattern
Power Platform adoption consistently outpaces governance. The tools are accessible, time-to-value is fast, and governance feels like a problem to address later. In regulated industries, that gap creates compounding risk — and closing it gets significantly harder the longer it goes unaddressed.
AI is accelerating the same pattern. Organizations adopting Microsoft Copilot Studio are generating agents faster than governance frameworks can keep up. The organizations that scale Power Platform successfully are those that treat AI agent governance as a first-order concern from the start — embedded in the same framework as environment management and data policy, not bolted on afterward.
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