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If you're an IT or security professional, you've probably been asked about generative AI more times in the last six months than in the previous six years. The hype is real, but so are AI risks and the pressure to justify your decisions, especially in regulated industries. Whether you're fielding questions from your board, compliance team, or most tech-savvy end users, the conversation always circles back to two things: security and privacy.
Let's cut through the noise and get practical. We have spent a lot of time digging into the security and privacy documentation for six of the biggest GenAI platforms on the market: Microsoft Copilot, OpenAI ChatGPT, Google Gemini, Anthropic Claude, Perplexity, and DeepSeek. Here's what you need to know before you roll out any of these tools — or let your users loose with them.
Compare the Top GenAI Platforms
Microsoft Copilot: The Enterprise-First Approach
If you're already a Microsoft 365 shop, Copilot is the safest first step. It's built with regulated industries in mind, layering on encryption (FIPS 140-2, the federal standard for cryptographic security, at rest and in transit), zero trust architecture, and data isolation between tenants. Authentication runs through EntraID, so your existing permissions and policies carry over.
Privacy: Microsoft acts as a data processor under its data processing agreement (DPA), and — crucially — your prompts and responses aren't used to train its models. Web queries are anonymized, and you get full audit logs and eDiscovery through Purview. Bottom line: Copilot keeps your data in your environment and is built for compliance.
Pro tip: Don't use the consumer version for anything regulated. Stick to enterprise deployments.
OpenAI ChatGPT: Powerful, but Mind the Version
ChatGPT is the most popular GenAI platform in the world, but not all versions are created equal. The enterprise, business, and API versions offer robust security (AES-256, TLS 1.2+ encryption, industry standards for securing data in transit and at rest), SOC 2 Type II and ISO certifications (international standards for information security management), and external penetration testing. You own your data, and by default, it's not used for training unless you opt in.
Privacy: You can set custom retention policies and even enforce zero data retention. But here's the catch: The consumer versions (free and plus) are not recommended for regulated environments. Data may be retained and used for training unless you explicitly opt out, and admin controls are minimal.
Pro tip: If you're in finance, healthcare, or any regulated space, go enterprise or go home.
Google Gemini: Enterprise-Grade, If You Deploy It Right
Google's Gemini is all-in on AI, and its enterprise deployments (via Google Cloud or Workspace) come with strong security features: AES-256 and TLS encryption, identity and access management (IAM) controls, VPC Service Controls (Google's isolation feature for cloud resources), and client-side encryption. You get granular admin controls, audit logs, and Vault integration for compliance.
Privacy: By default, Gemini doesn't train on customer data unless you opt in. You can configure auto-delete settings and retention policies. But — and this is a big but — consumer-facing Gemini apps don't offer the same controls and may retain data longer.
Pro tip: If you're a Google Workspace institution, Gemini is a solid choice. Otherwise, steer clear of the consumer apps for anything sensitive.
Anthropic Claude: Built for Finance, Built for Trust
Claude has made waves with its Claude for Financial Services model, tailored for analysts, underwriters, and portfolio managers. Security is enterprise-grade (SOC 2 Type II and ISO 27001), and you get zero-data-retention mode and custom retention policies. Input sanitization and command blocklists help prevent prompt injection attacks.
Privacy: Claude does not train on user data by default and offers granular retention controls and opt-in memory features. Anthropic's Unified Harm Framework and policy vulnerability testing show a real commitment to responsible AI.
Pro tip: If you're processing large documents or need the strongest privacy protections, Claude is worth a look.
Perplexity: Research Power, but Watch the Details
Perplexity is best known for its research and citation capabilities, and the Enterprise Pro for Finance version offers SOC 2 Type II compliance and zero data retention for API interactions. Admin controls let you manage file retention and access, and incognito mode can be enforced.
Privacy: Consumer versions may retain data and lack strong authentication. Multifactor authentication (MFA) isn't built in, and some ambiguity remains in its data usage policies. If you're considering Perplexity, stick to the enterprise version and review the documentation carefully.
Pro tip: It's great for deep research, but it shouldn’t replace your core compliance workflows.
DeepSeek: Don't Use It
DeepSeek is known for being cost-effective and open source, but it's not recommended for regulated environments. It lacks a clear encryption standard, appears to offer limited security controls, and its servers are located in China — meaning your data is subject to PRC law. Data may be retained indefinitely and used for model improvement unless you opt out.
Privacy: Data handling and residency practices may not meet regulatory expectations, and retention policies can be unclear.
Pro tip: If you must use DeepSeek, self-host it and build your own security and compliance layers. Otherwise, steer clear, especially if you're handling sensitive financial or personal data.
Key Takeaways for IT and Security Leaders
Before deploying GenAI, it helps to step back and think strategically about governance, security, and privacy.
- Enterprise deployments are your friend: Consumer versions of GenAI platforms rarely offer the controls, compliance, or privacy you need.
- Governance matters: Build out your AI policies, inventory, risk assessments, and training programs before you deploy anything.
- Know your use case: Not every platform is right for every job. Match the tool to your needs, and don't be afraid to say "no" if the risks outweigh the benefits.
- The chief AI officer seat is real: If your board hasn't asked about it yet, they will. Start preparing now — AI governance is quickly becoming a board-level concern.
Ready to take the next step? Reach out to us to talk about how we can help you make empowered, secure decisions about GenAI — before the hype turns into a headline.
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