Claude vs ChatGPT vs Gemini: Picking an AI Assistant for Your Team

The question isn't which model is cleverest

Model leaderboards flip every few months, and by the time you have rolled an assistant out to your team, the rankings will have changed again. All three flagship assistants (Anthropic's Claude, OpenAI's ChatGPT and Google's Gemini) are more than capable for everyday business writing, analysis, summarising and admin. Choosing on raw intelligence is choosing on the one factor that won't stay still.

What stays stable is how each vendor handles your data, what admin controls come with a seat, what it costs per person, and how well it plugs into the tools you already pay for. Those are the criteria this comparison scores, and it ends with a recommendation by company type rather than a single winner, because there isn't one.

Data privacy: who trains on what

The headline is reassuring: the paid business tiers of all three exclude your prompts and files from model training by default. The real trap is consumer accounts. Free and personal tiers may use conversations to improve models unless settings are changed, and their terms differ from business terms in ways that matter for confidentiality. So the first governance rule costs nothing: staff use company workspace accounts, never personal ones, for anything involving client or company data.

Under UK GDPR the vendor acts as your processor when you're on business terms, and all three offer a data processing agreement. If your client contracts demand specific data residency, check the current options at enterprise tier before committing, and ask for each vendor's security documentation (SOC 2-type reports and similar are standard at this level). Run a short data protection impact assessment before rollout if staff will handle personal data in the tool; the ICO's template makes this a half-day job, not a project.

Admin controls: what a seat actually buys

At team level (ChatGPT Team, Claude Team), you get a managed workspace: centralised billing, member management and the no-training commitment. The heavier controls that IT departments ask for (SAML single sign-on, SCIM user provisioning, audit logs, granular retention settings) generally arrive only at enterprise tier, with custom pricing and often a minimum seat count.

Gemini's structural advantage is that it is managed from the Google Workspace admin console many firms already use, so your existing access rules and device policies extend to AI use without a new dashboard. Microsoft shops have the equivalent argument for Microsoft 365 Copilot, which is worth trialling alongside the big three if your world is Outlook, Teams and SharePoint.

Pricing per seat

Pricing has converged: team-level tiers for all of these assistants cluster around £20–£25 plus VAT per user per month, usually with a discount for annual billing. Gemini is the outlier in packaging rather than price, since Google has folded its AI features into Workspace Business plans, so many Workspace customers already have a capable assistant included in what they pay.

• Five seats on a team tier: roughly £100–£125 a month, whichever vendor you pick.
• Enterprise tiers: custom pricing, minimum seats, and the SSO and audit features above.
• Hidden costs are the real variance: staff training time, building a shared prompt library, and any integration work.

Because list prices are so similar, price should almost never be the deciding factor. Fit with your existing suite saves more money than a pound or two per seat.

Integrations and ecosystem

Gemini's pitch is proximity: it drafts in Gmail, summarises in Docs, builds formulas in Sheets and takes notes in Meet, so nobody has to remember to open a separate tool. For teams whose whole day happens inside Workspace, that removes the biggest adoption barrier, which is habit.

ChatGPT has the broadest third-party ecosystem: custom GPTs, connectors to common storage and productivity tools, strong voice and image features, and the widest existing staff familiarity, which means the least training friction of the three.

Claude's strengths are long documents and careful writing: contracts, reports, policies and anything where tone matters. Projects give teams shared context that persists across conversations, the Model Context Protocol (MCP) has become a common standard for connecting assistants to internal tools, and Claude Code is a serious draw if you have developers in-house.

The decision matrix

• Google Workspace-first firm: start with Gemini; you may already be paying for it, and adoption is near-frictionless.
• Microsoft 365-first firm: trial Microsoft 365 Copilot against ChatGPT Team and pick on output quality for your actual documents.
• Professional services (legal, accountancy, consultancy, agencies) living in long documents: Claude, for document handling and writing quality.
• Sales and marketing-led teams wanting the widest toolbox of images, voice and plugins: ChatGPT.
• Firms building software or automations: Claude or ChatGPT, weighted by whether your developers prefer Claude Code or OpenAI's tooling.
• Regulated or high-confidentiality work: whichever vendor's enterprise tier meets your residency, SSO and audit requirements; run the DPIA before the pilot, not after.

Run a proper pilot before you commit

Shortlist two, then run a four-week pilot with three to five staff on real work: this month's proposals, this week's inbox, last quarter's report. Ask pilots to log time saved and rate output quality, then decide on evidence rather than demo-day impressions. Whatever you pick, write a one-page usage policy (approved accounts, banned inputs, review requirements) and spend an hour training the team; the tool matters less than how deliberately it's used.

If you want help choosing, piloting or building the guardrails around any of these tools, our team does this for UK small businesses week in, week out.