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Copilot Studio vs Foundry in financial services: what changes?


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TL;DR: Financial services teams are adopting Microsoft Copilot Studio and Foundry for AI agents, but Zenity’s analysis shows the governance problem is not platform choice alone: business-led low-code agents and technical mission-critical agents create different security and compliance pressures, especially around shadow AI, excessive privilege, and runtime enforcement. The decisive gap is governance that follows the agent lifecycle, not just the build platform.

NHIMG editorial — based on content published by Zenity: Considerations for Microsoft Copilot Studio vs. Foundry in Financial Services

By the numbers:

Questions worth separating out

Q: How should security teams govern business-built AI agents in low-code platforms?

A: Start with discovery, ownership, and access boundaries.

Q: Why do technical AI agents create higher privilege risk than simple workflow bots?

A: Technical agents usually integrate with multiple systems, so a single identity can accumulate broad delegated access across models, data sources, and tools.

Q: What do organisations get wrong about AI agent governance?

A: They often treat agent governance as a build-time review problem.

Practitioner guidance

What's in the full article

Zenity's full article covers the operational detail this post intentionally leaves for the source:

  • How Copilot Studio and Foundry differ in builder profile, agent scope, and deployment patterns
  • Examples of common financial services use cases, including onboarding, fraud-related automation, and regulatory workflows
  • The webinar context with Zenity, Microsoft, and Slalom, including the practical defense-in-depth themes discussed
  • The article's specific framing of visibility, policy enforcement, and lifecycle governance for agent programmes

👉 Read Zenity's analysis of Copilot Studio vs Foundry governance in financial services →

Copilot Studio vs Foundry in financial services: what changes?

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