ChatGPT vs Claude vs Gemini for business

Side-by-side comparison

Capabilities move fast - treat this as a directional guide, not a benchmark. We help you validate the current best fit for your exact use case.

Business plans and data controls

The free and personal tiers of these assistants are not where business data belongs. Each vendor sells team and enterprise plans with admin consoles, single sign-on, user management and audit features, and each describes its business offerings as not using your business content to train its models by default. The same applies, in each vendor's description, to their commercial API terms. Plan names, retention periods, data-residency options and the exact wording change regularly, so check the current terms and data processing agreement for the specific plan before you roll anything out.

Questions worth putting to every vendor: where is data processed and stored, how long are prompts and outputs retained, who can access them, can you set zero or shortened retention for API use, and which connectors can reach your internal systems. Your own controls matter as much as theirs - decide which data classes staff may paste into an assistant, and enforce it through policy and admin settings.

Chat apps vs APIs: two different purchases

Buying seats in ChatGPT, Claude or Gemini gives employees a ready-made assistant for drafting, research, analysis and coding. Building on the API is a different decision: you call the model from your own software - a support bot, a document-processing pipeline, an AI agent inside your product - and pay for usage rather than seats. The chat app with the best user experience for your staff is not automatically the best model for an automated workflow, so evaluate the two separately. API builds also need engineering around the model: retrieval from your documents, guardrails, logging, evaluation and cost monitoring.

Fitting your existing suite

Where your company already works often decides the workforce assistant. Gemini is built into Google Workspace - Gmail, Docs, Sheets and Meet - so Workspace organisations get it inside familiar tools. Microsoft 365 organisations usually look first at Microsoft's own Copilot, which has been built largely on OpenAI models, with Microsoft adding other model options over time. ChatGPT and Claude both offer connectors to common business systems such as file storage, email, calendars and developer tools, and support the Model Context Protocol for connecting to other systems. On the cloud side, check which models are available on the platform you already use - Azure, Google Cloud or AWS - since buying through an existing cloud agreement can simplify procurement, security review and billing.

Evaluate on your own tasks

Public benchmarks and leaderboards change month to month and rarely match your work. A better test: collect a few dozen real examples of the task - support tickets, contracts to summarise, code changes, data to extract - and write down what a good answer looks like. Run the same examples through each model with the same instructions, have the people who do the work today grade the outputs without knowing which model produced them, and record cost and response time alongside quality. Repeat the test when a vendor ships a new model; the winner for one task is often not the winner for another.

A multi-model strategy

Many organisations standardise on one assistant for staff while keeping their own software model-agnostic. In practice that means a thin abstraction layer between your application and the model APIs, prompts and evaluations stored with your code, and the ability to route each task to the model that handles it best - a capable model for complex reasoning, a smaller, cheaper one for high-volume classification, and a fallback provider if one has an outage. It also reduces vendor lock-in as prices and capabilities shift. For the most sensitive data, open-weight models hosted in your own environment are a further option.

Which should you choose?

In practice, the strongest products are often model-agnostic - routing each task to the best model. That's how we build: on Claude, GPT, Gemini and open models via our AI development services and LLM development.

Frequently asked questions