Field service combines scheduling, on-site work and customer updates — AI can support all three, including where connectivity is poor. Here’s how UK field service teams can use AI in 2026. (dgm implements osFoundry as an independent partner.)
Where AI helps field service
- job scheduling and dispatch support;
- on-site knowledge access for engineers (manuals, history, troubleshooting);
- service report drafting; and
- customer communication (updates, ETAs).
AI speeds jobs and supports engineers with information — the engineer applies judgement and makes the call.
On-site knowledge is the standout use case
Giving engineers on-site access to manuals, past job history and troubleshooting knowledge via AI lets them find answers quickly without calling back to base. The engineer applies judgement; AI provides grounded information from your real documentation. (See RAG explained.)
The connectivity twist
A real field constraint is poor connectivity. osFoundry supports local inference (running models on a device) and self-hosted deployment, so AI can work on-site without a constant cloud connection — useful for engineers in poorly-connected areas. dgm can scope offline-capable knowledge access.
Data control
Keep customer and job data controlled (self-hosting, an EU region, or local), minimise what AI processes, and avoid consumer tools — with an AI use policy. Customer data is personal data under UK GDPR.
Where osFoundry and dgm fit
dgm builds data-controlled, offline-capable field service AI on osFoundry: local and self-hosted inference for field use (data control via device, your own cloud or EU region — note no dedicated UK region), connectors to field service systems, retrieval over your manuals, and audit.
dgm is an independent integration partner with zero integrations so far — no client claims. To scope a field service AI project, book a consultation with dgm. General information only.