“AI for sales” can mean two quite different things depending on where the model runs. That one detail drives the privacy story, the compliance story, and part of the capability story. Here is the honest comparison.
The two models
- Cloud AI sends your data to a provider’s servers, where a large model processes it and sends back a result. This is how most well-known AI products work.
- On-device AI runs a model locally, on your own computer. Your data is processed on the machine and never leaves it.
Side by side
| Cloud AI | On-device AI | |
|---|---|---|
| Where your data goes | To the provider’s servers | Nowhere, stays on your machine |
| Raw capability | Highest (frontier models) | Good for concrete tasks, not frontier |
| Privacy / compliance | Needs review (processor, transfers, training) | Simple, nothing leaves the device |
| Works offline | No | Yes, after the model downloads |
| Ongoing cost | Often per-use or per-seat API cost | No per-use inference cost |
| Best for | Open-ended, heavy reasoning | Private, practical CRM tasks |
When cloud AI fits
- You need the strongest possible reasoning or very broad general knowledge.
- Your data is not sensitive, or you have the contracts and settings to use it compliantly.
- You are fine with a per-use or per-seat cost and an internet connection.
When on-device AI fits
- You are working with customer data and want to avoid sending it anywhere.
- You want an easy security and compliance yes, no new processor to vet.
- You value working offline and without per-use inference costs.
- The tasks are concrete: answer questions about your data, enrich fields, draft outreach, rather than open-ended reasoning.
For CRM data specifically, that second column is usually the better fit, which is why Upcells runs its AI on-device. You get a practical copilot for your Salesforce data on the Accelerator tier without the data leaving your machine. If risk is your main concern, see is it safe to put CRM data into AI?.
A note on honesty
On-device AI is not a magic equal of a frontier cloud model. It is a capable, local copilot. The right question is not “which is more powerful” but “which fits the task and the data”, and for private CRM work, local usually wins.
Frequently asked questions
What is the difference between on-device and cloud AI? Cloud AI processes your data on a provider’s servers; on-device AI runs the model on your own machine, so your data never leaves it.
Is on-device AI less capable than cloud AI? For raw, open-ended reasoning, yes, cloud frontier models are stronger. For concrete CRM tasks, a local model is a capable copilot, with the advantage that your data stays private.
Which is better for working with Salesforce data? For sensitive CRM data, on-device AI is usually the better fit: it removes the privacy and compliance questions and still handles enrichment and data questions well.