Most drinks brands we talk to don't have an "AI problem" — they have a data problem wearing an AI costume. Before any model can help you forecast demand or answer customer emails, it needs clean, structured, trustworthy data to work from. Start there and the rest gets dramatically easier.
Here's the order we'd recommend for a wine, spirits or F&B SME getting started.
1. Get to a single source of truth
If your stock lives in one system, your sales in another, and your customer list in a spreadsheet someone updates by hand, no AI tool will save you. The highest-leverage first move is almost always cleaning and consolidating your data into one place you can trust.
This isn't glamorous, but it's the foundation everything else stands on.
2. Pick one painful, repetitive workflow
Don't try to "do AI" across the whole business. Choose a single workflow that is:
- repetitive and time-consuming,
- well-defined (clear inputs, clear outputs), and
- low-risk if it occasionally gets things wrong.
Customer-service triage, order-confirmation drafting, and supplier-data tidying are common starting points.
3. Enable your team, don't replace it
The fastest wins come from getting your existing team comfortable using AI tools day to day — not from a six-month platform build. A short enablement programme often returns more value in a month than a large project does in a quarter.
What to skip (for now)
| Tempting | Why wait |
|---|---|
| A custom in-house model | Expensive, slow, rarely needed early |
| "AI everywhere" rollouts | Spreads effort too thin to show ROI |
| Tools on top of messy data | Garbage in, confident garbage out |
The honest summary
Clean your data, pick one workflow, enable your people. Prove value, then expand.
That's the playbook we used to take a fine-wine merchant's back-office costs down 65% — and it's the same sequence we'd recommend to almost any SME.
Want to talk through where to start? Book a free 20-minute call or email hello@neovara.io.