ChatGPT, Claude or Copilot for an FMCG or DTC company

How do ChatGPT, Claude and Copilot compare right now?

Laura Rosenberger, founder of Superposition, puts it this way:

ChatGPT and Claude are very evenly matched these days. You'll often see one edge ahead of the other, and then it reverses a couple of months later. At the moment more of the organisations I work with are on Claude, but I'm also seeing others do really well with ChatGPT. Copilot isn't as far behind as it used to be, though I mostly see it in larger, more corporate businesses.

Microsoft Copilot sits inside Microsoft 365, and Microsoft says it follows your existing permissions and can draw on your emails and files. Gemini plays a similar role in Google Workspace. ChatGPT, from OpenAI, and Claude, from Anthropic, are separate assistants with their own business plans, and Anthropic lists Claude for Microsoft 365. Names, plans and features change often; we checked the vendor pages under Sources on 4 November 2026.

Why do business accounts matter more than the brand of tool?

The bigger difference is between personal and business accounts. OpenAI says it may use content from its services for individuals to train its models unless you opt out, but does not train on business plans by default.

Anthropic gives users of its consumer plans a choice, and does not train on its commercial products by default.

Microsoft says prompts and responses in Copilot for organisations are not used to train its foundation models. Google says Workspace does not use customer data to train its models without permission. Business plans also give you admin controls, such as managing who has access.

How should you choose? Five questions

1. 01
   What is your team already using and comfortable with?

   If many people already use one tool, starting there saves a lot of retraining.

2. 02
   Which systems does it need to work with?

   Outlook and Teams point towards Copilot, Gmail and Drive towards Gemini. Check how each option connects to your e-commerce platform, shared drives and spreadsheets.

3. 03
   What will it cost across the team?

   Most business plans are priced per person per month, and some add usage-based charges. Compare the plan you would actually need, not the cheapest tier.

4. 04
   How does it handle your data?

   Use business accounts rather than personal ones, and check the training defaults and admin controls with whoever looks after IT and data protection.

5. 05
   Which one does better on your real work?

   Try your shortlist on the same three to five tasks, such as a weekly trading report, product descriptions or customer service replies, and compare what you would actually use.

Don't overthink it. The tools keep leapfrogging each other, and the skills your team learns carry across, so you can switch later.

Superposition

What should the training cover, whichever tool you pick?

People leave with a new way of working: a more ambitious view of what’s possible, a real understanding of what the tools can do, and frameworks for applying them to their own role so they get more done, and better. Training should also cover your own rules, such as what information can go in and which account to use.

Choosing a tool rarely fixes uneven use on its own. We recommend giving people time to practise on real work between sessions, with a leader who supports what they try.

How Superposition does this

Superposition runs practical, in-person AI training for UK consumer brands in food and drink, CPG, FMCG, DTC and e-commerce, typically doing £10m to £100m in revenue. The training is built around the tools you already use.

Superposition was founded by Laura Rosenberger, former COO of Naked Wines UK, a DTC wine business with over £100m in revenue, and co-founder of the wine brand Laylo.

1. We get to know your business. We talk to your leaders and the people taking part about their work, tools and blockers.
2. We run the sessions at your office. People use AI on their own work, with time to practise in between.
3. We map the bigger opportunities. Your leaders get a map of where AI could help across the business, what each opportunity needs and the steps to take next.

Sometimes the answer is a better process or a system you already have.