AI assistants from Anthropic (Claude), Google (Gemini), and OpenAI (ChatGPT) are becoming core tools for companies. They’re all powerful, but they’re also changing fast. The “best” choice today may not be the best tomorrow.
Below we explain what each one is strongest at, how Microsoft 365 Copilot is different, and a few other big contenders to watch.
Quick snapshot
ChatGPT (OpenAI): Broad, polished assistant with a large developer ecosystem and frequent model upgrades.
Gemini (Google): Deeply multimodal (text + images + other inputs), tightly integrated into Google services and developer platforms.
Claude (Anthropic): Focus on safe, controllable responses and enterprise tools; Anthropic publishes focused “Sonnet/Claude” model releases.
Microsoft 365 Copilot: An enterprise product that connects to your Microsoft 365 data so the assistant can use your real company documents, email and calendars to give personalised help. It’s “I knows your company” capability is its main business advantage.
What “latest” means (and why it matters)
These providers release new model versions and product updates regularly, so performance, safety, and pricing can shift quickly. Judge vendors on how they update and support customers, not only on a single benchmark or headline.
How they differ
Integration with your company data
Microsoft 365 Copilot: Designed to read and act on your organisation’s Microsoft 365 content (emails, Teams chats, SharePoint, OneDrive, calendar) through what Microsoft calls Work IQ. That allows Copilot to give answers that reference your people, projects and files — a major boost for internal productivity. If your business already lives in M365, Copilot is especially impactful.
ChatGPT / Gemini / Claude: Can be integrated into business systems via APIs or vendor enterprise offerings and can work with uploaded documents or “connectors,” but out-of-the-box they don’t automatically have access to your email/files unless you set up secure integrations or use an enterprise product that bundles that capability.
Strengths at common business tasks
Knowledge & summarisation (meeting notes, long docs): All three are good; models with larger context windows and enterprise tooling (e.g., ChatGPT’s newer models, Gemini’s advanced modes, Claude Sonnet family) often handle very long documents better.
Coding / technical tasks: OpenAI’s recent models and some of Anthropic’s Sonnet-family releases emphasise coding improvements. Google’s Gemini also competes strongly for reasoning and multimodal tasks. Benchmarks shift as vendors release updates.
Multimodal work (images, video, audio): Google’s Gemini and some vendors are explicitly building broad multimodal features; choose these if you need image or mixed-input processing.
Safety, controllability and compliance
Claude (Anthropic): Anthropic has emphasised safety and control as central design goals, which is especially useful for regulated industries.
Enterprise offerings (Copilot, ChatGPT Enterprise, Gemini in Vertex AI): Offer controls, logging, admin tools and SIEM integrations to help meet governance and data residency requirements. Always confirm specifics, such as data retention, with the vendor.
Pricing & licensing
Models and product pricing tiers vary, including free versions, enterprise-wide paid versions, and cloud-hosted vs self-hosted. Open-source or licensable models (e.g., Meta’s Llama family or some Mistral releases) let you self-host for more control, sometimes at lower ongoing cost but with higher engineering overhead.
Ease of use for non-technical staff
Copilot (M365): Wins when it comes to familiarity, as it appears inside apps people already use (Word, Excel, Outlook, Teams) and can pull from the same documents, meaning lower friction and quicker uptake.
ChatGPT / Gemini / Claude: Great for tasks like customer support prompts, marketing copy, analysis, but may need a UX layer or training to fit everyday office workflows.
Other big contenders worth watching
Meta / Llama (Llama 3 / Llama 4 variants): Large open models that organisations can fine-tune or self-host; strong option if you want more control.
Mistral: Gaining attention for strong performance-per-cost and open offerings; they also provide enterprise chat services.
Cohere: Focuses on enterprise embeddings and “Command” models suited for retrieval-augmented workflows. Good if you’re building search/semantic-retrieval into processes.
How to choose
"What problem are you solving?" (e.g., automate meeting notes, speed up helpdesk answers, generate customer proposals) — pick a model/product that’s proven in that task.
"Where does your data live?" If you already use Microsoft 365 heavily, Copilot’s integration is a strong plus. If you keep everything in Google Workspace, Gemini’s integrations may be attractive.
Security & compliance: Ask vendors where model inference runs, how data is logged, and whether you can turn off data retention for training. Enterprise plans usually provide more controls.
Pilot first: Run a small, measurable pilot (1–3 workflows), measure time saved and accuracy, then scale. (Tip: test with real company docs, not artificial examples.)
Vendor roadmap & updates: Because models update quickly, prefer vendors with clear enterprise SLAs, regular release notes, and an upgrade path.
A few realistic expectations
They’re not perfect
All generative models sometimes make confident but incorrect statements. That’s why human checks are usually still needed for important outputs.
Choices change fast
New model versions and features appear frequently, so what’s strongest today may be overtaken in weeks or months. That’s why vendor stability, security and integration matter as much as headline benchmarks.
Short recommended next steps
- Pick one clear internal use case (e.g., “automate weekly project summaries”).
- If you use Microsoft 365 heavily, try Copilot features in a pilot, as its integration with your company data is its main USP. Ask IT about licensing and admin controls first.
- For cross-cloud or custom needs, evaluate short pilots with ChatGPT, Gemini, and Claude to compare accuracy, user acceptance and governance.
- Insist on measurable KPIs for the pilot, such as time saved, error rate, or user satisfaction.
- Revisit every 3–6 months, as models and vendor capabilities evolve quickly.
Final thoughts
Claude, Gemini and ChatGPT are all excellent tools with slightly different strengths: safety and controllability (Claude), multimodal reasoning and Google ecosystem ties (Gemini), and a large, fast-moving ecosystem and developer tooling (ChatGPT).
Microsoft 365 Copilot’s standout advantage for many businesses is that it connects directly to your company’s M365 data so the assistant can act like an informed colleague, a stand-out feature if your work already lives in Microsoft apps. But because the landscape changes fast, the best approach is a small, measurable pilot and a focus on governance and integration rather than chasing the “number one” model.
