RSMUS.comBanks aren’t debating whether generative AI belongs in the enterprise anymore. The real question has shifted to something much more practical and regulated:
How do we deploy AI in a way that fits our existing security, compliance and audit model?
In the current market, there are three enterprise-grade AI assistants that are often mentioned in banking conversations:
All three have made meaningful investments in enterprise security and privacy. But for banks already standardized on Microsoft 365, the decision is rarely about raw model capability. It’s about control boundaries, audit defensibility and operational friction. And in that context, Copilot for Microsoft 365 is usually the most straightforward and defensible option.
Building On Your Current Environment
For banks already running their collaboration, identity and data governance stack on Microsoft 365, Copilot isn’t “just another AI tool.” It’s an extension of the same environment regulators already understand:
- Same tenant
- Same identity plane
- Same data loss prevention
- Same eDiscovery and retention model
- Same administrative controls
Additionally, Microsoft states that prompts, responses and accessed Microsoft Graph data are not used to train foundation large language models (LLMs), and that interactions remain within the Microsoft 365 service boundary.
That single fact dramatically simplifies conversations with risk committees, compliance teams, internal auditors and regulators. Other enterprise assistants may be strong, but they introduce new boundaries that must be explained, governed and defended.
Why Other AI Assistants Still Matter
Both OpenAI and Anthropic offer enterprise-grade assistants via ChatGPT Enterprise and Claude Enterprise. Each option includes explicit “no training by default” commitments, encryption at rest and in transit, SOC 2 / ISO-aligned controls and configurable retention options in enterprise contexts.
These platforms are often referenced as benchmarks for enterprise AI maturity, not because they’re poor choices, but because they represent independent SaaS control planes.
For banks not standardized on Microsoft 365, these platforms may warrant deeper evaluation.
However, for banks already deeply invested in Microsoft 365, they primarily serve as comparison points, not primary recommendations.
What Auditors and Regulators Care About Most
- Model Training on Bank Data
Copilot for Microsoft 365 is positioned so that prompts, responses and accessed data are not used to train Microsoft foundation models.
ChatGPT Enterprise and Claude Enterprise make similar commitments in enterprise contexts, but those assurances live outside your collaboration tenant and rely more heavily on contractual enforcement. Keeping AI interactions inside an already‑approved service boundary reduces audit complexity.
- Data Boundary and Residency
Copilot operates within the Microsoft 365 service boundary already approved for email, documents and collaboration.
Other assistants operate within their own SaaS environments, even when enterprise-grade. If your institution strongly prefers “no new data boundary for employee productivity tools,” Copilot aligns naturally.
- Retention, Legal Hold, and eDiscovery
Banks often prioritize discoverability over minimal retention for employee tools. Copilot aligns with existing Microsoft 365 retention and eDiscovery models, depending on licensing and configuration.
Other platforms offer configurable retention, but introduce:
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- Separate legal hold workflows
- Separate audit exports
- Separate policy enforcement
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- Governance Integration
All major platforms meet baseline encryption and isolation expectations. The difference is integration depth. While Copilot inherits Microsoft Purview, Entra ID and Microsoft 365 audit logs, other assistants require parallel governance tooling.
The Practical Reality for Microsoft 365 Banks
For Microsoft-centric banks, Copilot’s biggest advantage isn’t its novelty, but its governance inheritance. Copilot respects existing permissions, sensitivity labels and DLP policies. However, it’s important to note that if permissions or data classifications are weak in your organization today, Copilot can surface those weaknesses and data hygiene issues faster.
Bottom Line
Banks don’t fail AI programs because the models are weak. They struggle when AI doesn’t fit their control environment.
For institutions already standardized on Microsoft 365, Copilot isn’t just an AI assistant. It’s the most natural, defensible evolution of the platform banks already trust. By minimizing new risk surface area and leveraging controls already in place, Copilot creates a clean, regulatory narrative.
Other tools exist. Some are excellent. And if a bank is not a Microsoft 365 customer, institutions can consider broader evaluations of standalone enterprise assistants, though they’ll likely require the application of strict governance, retention and audit requirements.
But when the goal is safe, scalable, regulator-ready adoption, Copilot for Microsoft 365 is usually the smartest place to begin.
Diego Rosenfeld
Diego leads RSM's technology advisory practice, focused on helping organizations build actionable IT roadmaps and navigate business transformation. Working across a broad range of industries, he brings both strategic perspective and hands-on experience to each engagement, frequently serving clients as a fractional or interim CIO. Much of Diego's current client work centers on generative AI. He has developed a considered point of view on the subject: the organizations best positioned to benefit are those that approach adoption responsibly, thoughtfully sequencing initiatives across productivity improvement and process automation rather than pursuing speed at the expense of sound judgment. He works closely with leadership teams to develop AI strategies that are practical, governed, and built to last. Diego is a strong proponent of OKR driven IT execution, applying structured objective-setting to align technology initiatives with broader business priorities. He pairs this with a focus on IT financial transparency, helping clients identify cost optimization opportunities and determine whether their technology investments are delivering measurable value. Diego enjoys writing about emerging technology and is a regular speaker at webinars and live events, connecting the dots between strategy and real-world application. Outside of work, Diego is an avid tennis and padel player, and competes on the American Backgammon Tour.
