By the end of 2026, an estimated 78% of professional services firms will have at least one paid generative-AI subscription. For most, the choice comes down to two products: Microsoft 365 Copilot and ChatGPT Enterprise (with Google Gemini Enterprise and Anthropic Claude for Work as serious alternates).
For healthcare and financial-services firms — where HIPAA, SOC 2, FINRA, GLBA, and state privacy laws all apply — the decision isn’t about which product writes better marketing copy. It’s about which one can be deployed without creating a compliance liability, and which one your team will actually use enough to justify the cost.
This guide covers what each product is, what they cost, how they handle regulated data, the use cases where each wins, and a recommendation framework for a typical small or mid-size practice.
Quick verdict
Most regulated practices should start with Microsoft 365 Copilot. It’s already inside the apps your team uses, your existing M365 BAA covers it for HIPAA, and the data stays in your existing tenant. ChatGPT Enterprise is a stronger product for raw reasoning and document analysis, but the deployment overhead — separate procurement, separate BAA negotiation, separate data governance — only pays off when you have specific use cases that Copilot can’t handle.
What each product actually is
Microsoft 365 Copilot
- An AI assistant embedded directly inside Word, Excel, Outlook, Teams, and PowerPoint
- Uses GPT-4 class models (specific model varies and updates) plus Microsoft Graph data from your tenant
- Available as an add-on to Microsoft 365 E3, E5, or Business Standard / Premium
- Tenant-scoped — Copilot only sees data your user already has access to inside M365
ChatGPT Enterprise
- A standalone web product from OpenAI
- Uses GPT-4-class models (with periodic upgrades to newer models)
- Supports custom GPTs, file uploads, web browsing, advanced data analysis, image generation
- Independent of M365 — you upload or paste data into it; it doesn’t read your tenant directly
How they overlap
Both can summarize documents, emails, and meetings; draft text in your voice; answer questions about uploaded content; help with formulas, code, presentations. Both don’t train on your prompts when used in their enterprise tiers.
How they differ
| Capability | Copilot | ChatGPT Enterprise |
|---|---|---|
| Lives inside Outlook, Word, Excel, Teams | ✅ | ❌ |
| Reads your M365 mailbox/files automatically | ✅ (within user’s permissions) | ❌ (you upload manually) |
| Custom GPTs | Limited (Copilot Studio, extra cost) | ✅ (built-in) |
| Image generation | ✅ (basic via Designer) | ✅ (DALL-E built in) |
| File upload analysis | Limited | ✅ Strong |
| Web browsing | ✅ (Bing-based) | ✅ |
| Code interpreter / data analysis | Limited | ✅ Strong |
| Pricing (per user/month) | $30 | $60 (typical Enterprise) |
| Minimum seats | 1 | Typically 150+ |
Cost reality — actual 2026 pricing
The list price tells only part of the story. Real cost includes the underlying license you need, plus deployment effort.
Microsoft 365 Copilot
| Line item | Cost |
|---|---|
| Underlying M365 license (E3 / E5 / Business Standard / Premium) | $13–$57 per user/month |
| Copilot add-on | $30 per user/month |
| All-in for a 50-person practice on Business Premium | $2,600/month ($31,200/yr) |
ChatGPT Enterprise
| Line item | Cost |
|---|---|
| Per-user license (typical) | $60 per user/month |
| Minimum commitment | Typically 150 seats (negotiable) |
| Custom GPT development (optional) | $10K–$40K project basis |
| All-in for a 50-person practice (with negotiated 50-seat minimum) | $3,000/month ($36,000/yr) |
A combined approach
Many regulated practices we work with end up running both:
- Copilot for everyday in-app productivity (200+ daily uses)
- ChatGPT Enterprise for power users (5–10 people doing research, document analysis, and custom workflows)
For a 50-person practice, this stacks to roughly $2,600 + $300–$600 (5–10 ChatGPT seats) = ~$3,000–$3,200/month all-in.
How each handles HIPAA
Microsoft 365 Copilot for HIPAA
✅ Covered by Microsoft’s existing BAA when you sign one with your M365 tenant
✅ Data stays inside your tenant — no external processing
✅ Inherits your existing Purview DLP, sensitivity labels, and retention policies
✅ Audit logging integrated with M365 unified audit log
⚠️ What you still need to do:
- Configure Copilot to respect sensitivity labels (default is permissive)
- Tighten SharePoint sharing — Copilot will surface anything users have access to, including over-shared files
- Review your Microsoft Graph permissions — Copilot reads what users already see; if they see too much, Copilot will surface too much
- Update HIPAA training to cover AI use
ChatGPT Enterprise for HIPAA
⚠️ As of early 2026, OpenAI’s ChatGPT Enterprise has begun signing BAAs on a case-by-case basis for healthcare customers. Verify yours is in place before any user uploads PHI.
⚠️ What you still need to do:
- Negotiate and sign a BAA with OpenAI before processing any PHI
- Establish data governance — what data is allowed in ChatGPT, what isn’t
- Train users on what counts as PHI (a surprising amount of data they might not think of)
- Disable any account integrations that send data outside the BAA scope
- Document data flows for HIPAA risk assessments
Bottom line: For any practice that hasn’t done the upfront BAA work with OpenAI, ChatGPT Enterprise should be considered off-limits for PHI. Use it for non-PHI productivity work; use Copilot for anything inside the EHR or M365 tenant.
How each handles SOC 2 / FINRA / GLBA (financial services)
Microsoft 365 Copilot for financial services
✅ Inherits your M365 tenant’s SOC 2 Type 2 attestation, ISO 27001, FedRAMP High (in GCC tenants)
✅ Customer Lockbox, Customer Key, and tenant-residency controls extend to Copilot
✅ Microsoft publishes a detailed Copilot data security and compliance whitepaper that lines up cleanly with most FINRA examiner expectations
⚠️ FINRA has specific recordkeeping rules for written communications. If Copilot is being used to draft client communications, those drafts and final outputs need to land in your archived books-and-records system (typically Smarsh, Global Relay, or Microsoft Purview Communication Compliance).
ChatGPT Enterprise for financial services
⚠️ ChatGPT Enterprise has SOC 2 Type 2 attestation but does not yet have a formal FINRA-compliant archiving integration like Microsoft does. Some firms have built custom integrations through the OpenAI API; this is a non-trivial engineering project.
⚠️ For RIAs and broker-dealers, the recordkeeping problem is the bigger blocker — not the data security itself. If your compliance team can’t produce a chat transcript on demand, you have a problem.
Use case cheat sheet
| Task | Better tool | Why |
|---|---|---|
| Draft a follow-up email after a Teams call | Copilot | It’s already in Outlook with the meeting context |
| Summarize a 60-page deposition or contract | ChatGPT Enterprise | Stronger document analysis and longer context handling |
| Build an Excel forecast model from a brief | Copilot | Direct integration with Excel formulas |
| Research a niche topic with web search and citations | ChatGPT Enterprise | Better browsing and source-tracking |
| Generate a SharePoint-shared deck for a client meeting | Copilot | Lives in PowerPoint; pulls from your tenant |
| Build a custom workflow for the team (custom GPT) | ChatGPT Enterprise | Custom GPTs are stronger and easier to share |
| Triage your inbox and pull out action items | Copilot | Reads Outlook directly |
| Analyze a structured CSV of patient billing data (de-identified) | ChatGPT Enterprise | Code interpreter is faster for ad-hoc analysis |
| Draft a policy document referencing your firm’s existing policies in SharePoint | Copilot | Tenant-scoped retrieval |
| Brainstorm a marketing campaign with image generation | Tie | Both work; Copilot keeps the work inside your tenant |
What about Google Gemini Enterprise and Claude for Work?
We get asked about both regularly. Brief view:
Google Gemini Enterprise — Strong if your practice is on Google Workspace (not M365). HIPAA-eligible with a signed BAA. Less compelling if you’re already in M365; the integration depth that makes Copilot useful doesn’t exist for Gemini in M365.
Claude for Work (Anthropic) — Strong reasoning, lower hallucination rate in many evaluations, and Anthropic has been more conservative on enterprise data handling. Increasingly used by financial services firms for analysis tasks. Lacks the in-app integration of Copilot. Worth piloting alongside ChatGPT Enterprise rather than instead of it.
For most regulated SMBs, the deployment-friction calculus still favors Copilot as the primary AI tool, with one of the standalone tools (ChatGPT Enterprise or Claude for Work) added for power users.
Decision framework
Use this flow if you’re trying to make the call:
Are you already on Microsoft 365?
→ Yes — Start with Copilot pilot for 5–10 users. Decide on enterprise ChatGPT after 60 days based on actual unmet needs.
→ No, on Google Workspace — Start with Gemini Enterprise pilot. Different decision tree.
Do you handle PHI or other regulated data?
→ Yes — Verify BAAs are in place for any AI tool you deploy. Default to in-tenant tools (Copilot, Gemini Enterprise) over external ones until your data governance is mature.
Do you have specific use cases that need long-context document analysis or custom GPTs?
→ Yes — Add ChatGPT Enterprise or Claude for Work for those users specifically.
Do you have a books-and-records / FINRA / SEC archiving requirement?
→ Yes — Verify your AI tools’ outputs land in your archive. This is often the hardest piece to solve outside Microsoft Purview.
What we recommend for a typical 50-person regulated practice
For a 50-person healthcare or financial-services practice with no current AI deployment, our standard recommendation:
- Months 1–2 — Foundation
- Sign Microsoft 365 Copilot BAA (already in place if you have one for M365)
- License 5–10 pilot users
- Establish AI use policy (what data is allowed, what isn’t)
- Train pilot users (2 hours each)
- Months 3–4 — Measure
- Track time saved on top 5 use cases
- Identify unmet needs the pilot revealed
- Months 5–6 — Expand
- Roll Copilot out to all knowledge workers
- Add ChatGPT Enterprise for 5–10 power users with specific document-heavy or analysis-heavy use cases
- Sign separate OpenAI BAA if any of those users will touch PHI
- Ongoing — Govern
- Quarterly review of which users are actually using their licenses
- Re-train as use cases evolve
- Annual data-governance review
Where to start
ACS helps healthcare and financial-services practices deploy AI tooling without breaking compliance. Our typical engagement: a 30-minute scoping call, a 4-week pilot rollout (BAA, licensing, governance, training), and ongoing tuning as use cases mature.
Schedule a free AI deployment scoping call →
Or call 1-650-300-7557.
Frequently asked questions
Will Microsoft Copilot train on our data?
No, not in the M365 Copilot tier. Microsoft has been explicit that prompts and responses in M365 Copilot are not used to train the underlying foundation models.
Will ChatGPT Enterprise train on our data?
No, not in the Enterprise tier. OpenAI has the same posture — Enterprise prompts are not used for training. The free and Plus tiers are different; do not let employees use those for work tasks.
Can we run our own AI on-premises instead?
Yes, increasingly. Local LLMs (Llama, Mistral, etc.) running on dedicated hardware are now viable for some regulated workloads. The compliance story is cleaner (data never leaves your environment) but the operational burden is higher and the model quality typically trails the frontier hosted models by 6–12 months. For most SMBs this is overkill.
What about all the smaller AI tools — Otter, Fireflies, Jasper, Grammarly, etc.?
Each is a separate vendor, separate BAA conversation, and separate data governance. We recommend treating these as exceptions — only deploy them when there’s a clear use case the primary AI tools don’t cover, and only after the BAA is signed.
How quickly can we deploy Copilot?
For a clean M365 tenant, 1–2 weeks from license purchase to pilot users actively using it. The slow part isn’t the technology — it’s the user adoption and policy work.
Related reading
- How AI-Powered Managed IT Services Are Revolutionizing SMB Operations
- Microsoft 365 vs Google Workspace: A Business Comparison
- Healthcare IT Services
- Financial Services IT Solutions
This article reflects pricing and capabilities as of the publication date. The AI vendor landscape changes quickly; verify product capabilities and BAA status with vendors directly before relying on them for compliance-sensitive deployments.
