How AI Can Work on Your Business Data
AI is only as useful as the data it can see. Here is what AI on your own business data looks like in practice — and what needs to be in place first.
Public AI chat tools know a lot about the world but nothing about your business. The real opportunity is AI that works on your own data — your customers, jobs, projects, stock and timesheets — and gives answers your team can act on.
What AI on business data looks like
- Asking "which customers have ordered less this quarter?" in plain English.
- Summarising a long job or incident history into a few lines.
- Flagging projects that are trending over budget.
- Drafting quotes, reports or follow-up emails from existing records.
- Spotting patterns in incidents, delays or returns.
Why the data has to come first
AI cannot make sense of ten disconnected spreadsheets and a WhatsApp group. It needs structured, connected data in one place. That is why AI works best on top of a proper business system rather than as a separate experiment.
Keeping it safe and sensible
- AI should only see the data a user is allowed to see.
- Answers should point back to the underlying records.
- People stay responsible for decisions; AI helps them get there faster.
Where to start
Pick a question management asks every week that takes someone hours to answer. If the data for it is already in one system, AI can usually help. If it is not, start by bringing that process into a custom business web app. See our Business App + AI section for examples.
Questions
Does our data get used to train public AI models?
It should not. AI features should be set up so your business data is used to answer your questions, not to train public models.
Do we need a data scientist?
No. With your data in one well-structured system, AI features can be built into the app your team already uses.
About the author
Juan Kotzee
Founder & Managing Director — Drivatic
Juan Kotzee is the Founder and Managing Director of Drivatic, a South African software company specialising in custom business applications, analytics, automation and AI.
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