Perplexity vs ChatGPT for regulated industries: compliance comparison

TL;DR. ChatGPT Enterprise and ChatGPT Edu have a more mature compliance story (BAA, ISO 27001, ISO 27701, ZDR, deeper enterprise tooling). Perplexity Enterprise is closing the gap and has a structural advantage for regulated-industry research workflows: every output ships with source citations the buyer can verify, which simplifies the audit trail. For research and discovery tasks under regulated supervision, Perplexity Enterprise is often the better procurement read; for transactional and integration tasks, ChatGPT Enterprise still leads.

The comparison frame

Regulated industries — financial services (FCA, PRA, SEC, FINRA), healthcare (HIPAA, NHS DSPT, EU national health laws), legal (SRA, BSB), pharmaceutical (FDA, EMA), and others — share three procurement concerns when picking an AI tool:

1. Evidence trail. Output the regulator can audit back to source.
2. Tier eligibility. The contracted product, not a consumer adjacent one.
3. Data controls. Training defaults, retention defaults, BAA where applicable, region commitments where applicable.

Perplexity and ChatGPT solve a different first-order problem (search-with-citation versus general-purpose generation), and that difference flows into the regulated-industry read.

The full vendor reads sit at the Perplexity profile and the OpenAI profile.

1. What the tool actually does for a regulated user

| | Perplexity Enterprise | ChatGPT Enterprise | |---|---|---| | Primary mode | Search-grounded answers with inline citations | General-purpose chat, document generation, code, analysis | | Default output structure | Answer + cited sources (URLs the user can click) | Answer; sources only when the user asks the model to cite | | Retrieval source | Live web + connected knowledge bases | OpenAI training set + retrieval-augmented when the buyer wires it up | | Strongest use cases for regulated buyers | Regulatory research, market intelligence, due diligence summaries, expert-witness preparation | Drafting, summarisation, code, structured-data work, customer support, integration with other systems |

The citation behaviour is the structural advantage for Perplexity in regulated work. A compliance officer reviewing a research summary can click each citation, confirm the source, and document the evidence trail without re-running the workflow. ChatGPT will cite sources when asked but does not surface them by default in the same way.

2. Tier eligibility and the consumer trap

| | Perplexity Enterprise | ChatGPT Enterprise | |---|---|---| | Eligible tier for regulated use | Perplexity Enterprise | ChatGPT Enterprise; ChatGPT Edu; ChatGPT API on Enterprise agreement; Azure OpenAI | | Tier without enterprise contract | Perplexity Pro; Perplexity free | ChatGPT Plus; ChatGPT Team without explicit BAA addendum; ChatGPT free | | BAA eligibility (US healthcare) | Emerging — Perplexity Enterprise has been pursuing BAA-readiness; confirm with sales | Yes — ChatGPT Enterprise, ChatGPT Edu, OpenAI API on Enterprise; Azure OpenAI also | | Training default on the eligible enterprise tier | No training on customer data | No training on customer data |

A staff member using free Perplexity or free ChatGPT for regulated work is operating outside the enterprise default. Both vendors' consumer tiers create the same exposure: the procurement policy has to address consumer use directly, either by blocking the consumer products or by an explicit signed-policy approach.

3. Data controls

| | Perplexity Enterprise | ChatGPT Enterprise | |---|---|---| | Training on customer data (enterprise tier) | No | No | | Default retention of enterprise interactions | Enterprise-tier dependent; confirm with sales | 30 days at the API; ChatGPT Enterprise has bespoke retention controls | | ZDR equivalent | Enterprise-tier dependent | Yes, approval-gated | | SOC 2 Type II | Yes | Yes | | ISO 27001 | In progress at time of review; confirm | Yes | | ISO 27701 | In progress at time of review; confirm | Yes | | EU data residency | Enterprise option | Enterprise option; Azure OpenAI provides region-locked deployment |

ChatGPT Enterprise has a more mature published security posture. Perplexity Enterprise has been closing the gap; buyers in regulated industries should pull the most recent attestations directly through the sales channel rather than relying on the public marketing pages.

4. AI Act deployer-side read

Both vendors are GPAI providers. The deployer-side obligations land on the buyer based on the use case, not the vendor:

• Regulatory research, market intelligence, and due-diligence summarisation generally sit minimal-risk under the Act.
• Clinical decision support, automated underwriting, automated credit scoring, and similar regulated-use cases bring Annex III high-risk obligations onto the buyer.
• Buyers in financial services or healthcare are usually also subject to sectoral AI guidance (FCA / PRA on AI in financial services; FDA on AI/ML-based Software as a Medical Device; EMA on AI in medicines regulation) — these sit on top of the AI Act.

See the EU AI Act hub for the deployer assessment workflow.

5. Subprocessor depth

| | Perplexity Enterprise | ChatGPT Enterprise | |---|---|---| | Foundation models in use | Mix of Anthropic, OpenAI, and Perplexity's own | OpenAI's own models | | Cloud subprocessor | Amazon Web Services; Microsoft Azure | Microsoft Azure | | Search index | Perplexity's own crawled index + connected sources | N/A in the base product | | Implication for buyer's TIA | More providers in the diagram; multi-cloud | OpenAI runs on Azure; the data flow is shorter |

For buyers in regulated industries with strict Transfer Impact Assessment requirements, ChatGPT Enterprise on Azure OpenAI has the simpler data-flow diagram. Perplexity Enterprise's multi-cloud, multi-model stack is more complex to document but offers more redundancy.

Picking between them

Pick Perplexity Enterprise when:

• The regulated-industry use case is research or due diligence and the citation-by-default behaviour materially shortens the evidence trail
• The compliance officer needs to verify every output against named sources
• The buyer's team is small and the workflow is "research → summary → human review → file" rather than "AI in production"

Pick ChatGPT Enterprise when:

• The use case includes generation, drafting, summarisation, and code in addition to research
• The buyer needs HIPAA BAA, ISO 27001 + ISO 27701, and ZDR all under one contract today
• The buyer is building AI into a product surface (integrations, agents, customer-facing workflows) and needs the breadth of the OpenAI API

Run both side by side when:

• The buyer's compliance owner is auditing a research workflow and the regulated-industry use case demands citations the regulator can click through
• The team's drafting and generation workflow can run on ChatGPT Enterprise while the research workflow runs on Perplexity Enterprise

The shared regulated-industry checklist

Both vendors require the same buyer-side controls before any regulated-industry deployment:

1. Enterprise tier confirmed; consumer tier blocked or policy-controlled
2. DPA or BAA executed before any in-scope data enters the system
3. Sectoral AI guidance reviewed (FCA, FDA, EMA, SEC, FINRA, NHS DSPT, etc.)
4. Use-case classification under the EU AI Act if any EU exposure
5. Logging cadence set; human-review checkpoint documented
6. Workforce training delivered on the actual approved tool, not a generic AI policy
7. Quarterly review of vendor subprocessor changes (more important on Perplexity given the broader stack)

Related reading

• The DPA hub: DPA for AI vendors
• The AI Act deployer-side read: EU AI Act for AI buyers
• The HIPAA-specific checklist: HIPAA for AI tools
• Cross-comparison: OpenAI vs Anthropic DPA
• Cross-comparison: OpenAI vs Copilot enterprise compliance

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