What actually happens when you use cloud AI
When you send a prompt to a cloud AI service, that prompt — along with any documents, data, or context you include — travels to a third-party server, gets processed, and a response comes back. What happens to it after that depends on the provider's terms of service, which change, and their data handling practices, which aren't always transparent.
Some providers say they don't train on your data. Some say they do unless you opt out. Some offer enterprise tiers with stronger guarantees. Most business users are on standard tiers and haven't checked.
Most businesses don't have a policy about what data employees are sending to AI services. By the time they think about it, it's already happened.
The data you're sending is probably more sensitive than you think
It starts innocuously — summarise this email, help me respond to this client, review this contract. Each of those tasks involves real business information: client names, deal terms, internal strategy, financial details. Individually each prompt might seem low-risk. Collectively, over weeks and months of daily use across your whole team, it's a detailed picture of your business operations leaving your network every day.
"Private" as a feature, not an afterthought
Self-hosted AI flips this entirely. The model runs locally. Prompts never leave your network. There's no third-party terms of service to worry about, no data retention policy to read, no enterprise tier to pay for. Private is the default, not an upgrade.
For businesses in regulated industries this isn't optional — it's a compliance requirement. For everyone else it's a risk decision. The question is whether you're making that decision consciously or just defaulting to whatever's most convenient.
Powerful enough is good enough
The models available for self-hosting today are genuinely capable. They're not GPT-4 level on every benchmark, but for the tasks most business teams actually need — document summarisation, drafting, analysis, Q&A over internal data — they perform well. The gap between cloud and local has closed considerably in the last 18 months and continues to close.
Choosing a slightly less powerful model that keeps your data private is almost always the right call for business use.
The question isn't whether self-hosted AI is as powerful as cloud AI. The question is whether it's powerful enough for what your business actually needs — and for most businesses, it is.
Not sure what data your team is sending out?
We set up self-hosted AI environments where privacy is built in from day one. If your team is already using cloud AI and you're not sure what's leaving your network, that's worth a conversation.
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