Industry · Construction & Field Services
AI for Construction & Field Services: BOQ Extraction, RFI Response & Dispatch Automation
Short answer: AI agents read engineering drawings to generate procurement-ready quantity lists, route RFIs to the right discipline before they delay a schedule, and dispatch field technicians with the job history already attached.
A drawing's dimension callouts converting directly into a structured, procurement-ready Bill of Quantities.
- BOQ extraction turns engineering drawings into structured, procurement-ready quantity lists - hours instead of days.
- RFI routing matches each request to the right drawing and discipline lead automatically, before it becomes a schedule risk.
- Field service dispatch matches jobs to technicians by skill, proximity and equipment history, not just who's free.
Why construction and field services are underserved by generic automation
Most business automation tools assume clean, structured data - a form, a database record, an API call. Construction and field services run on the opposite: drawings, hand-annotated specs, photos taken on-site, RFIs written in half-sentences under deadline pressure. That's exactly the unstructured-input problem an AI agent is built to solve, and it's a large part of why this sector has lagged behind finance and retail in automation adoption - the tools that worked for spreadsheets never worked for blueprints.
BOQ extraction: from drawing to procurement in hours, not days
A Bill of Quantities extraction agent reads a CAD export or scanned engineering drawing using a vision-language model tuned for architectural and structural notation, identifies dimension callouts, material labels and quantity annotations, and generates a structured BOQ ready to feed into procurement or an ERP. A quantity surveyor still reviews the output, but the first pass - the part that used to take a day or more per drawing set - happens in minutes.
RFI response: catching schedule risk before it becomes delay
An RFI (Request for Information) that sits unanswered for a week can cascade into a real schedule delay. An RFI-routing agent reads the incoming request, matches it against the relevant drawing sheet or spec section, flags whether it touches the critical path, and routes it to the correct discipline lead - structural, MEP, architectural - automatically, rather than waiting for someone to triage the inbox.
An RFI matched to its drawing and routed to the right lead, the same day it lands.
Field service dispatch: context, not just availability
Traditional dispatch matches a job to whoever's next in the queue or closest on a map. An AI-powered dispatch agent adds a layer most systems miss: equipment history. If a technician is being sent to service a specific HVAC unit, the agent pulls that unit's maintenance history and likely parts needed before the technician leaves the depot, cutting the number of return trips for a missing part.
The technician arrives with the equipment history already loaded, not discovering it on site.
A curve construction and field services are catching up to
Construction has historically trailed other industries in software adoption, but the underlying agentic AI curve applies just as much here - the gap is opportunity, not a reason to wait.
33% of enterprise software applications will include agentic AI by 2028
Up from under 1% in 2024 - a 30x-plus jump in four years, which is the pace Gartner is using to justify calling this a genuine platform shift, not a feature update.
View the source →The sectors moving fastest on this list share one trait: high-volume, document-heavy work with a clear before/after time metric - which describes BOQ extraction and RFI routing almost exactly.
What to check before you buy
| Question to ask | Why it matters |
|---|---|
| Does it read CAD exports and scanned drawings, or only one format? | Real projects mix both, often within the same set |
| Does RFI routing check schedule impact, or just categorize? | Schedule risk is the reason RFI speed matters at all |
| Does dispatch pull equipment history automatically? | Cuts return trips for missing parts or context |
| Does it connect to your existing PM/ERP/field service platform? | Avoids a parallel system nobody fully adopts |
Bring a real drawing or RFI to see it live
We'll walk through exactly how the agent extracts, routes, or dispatches against your own project documents.
Book a demoFrequently asked questions
What is BOQ extraction and why does it need AI?
A Bill of Quantities (BOQ) lists every material and quantity needed for a project, usually derived by hand from engineering drawings. AI-based BOQ extraction reads the drawing directly - dimensions, annotations, material callouts - and generates a structured, procurement-ready quantity list, cutting a process that can take days down to hours.
Can AI actually read architectural and engineering drawings accurately?
Modern vision-language models handle standard CAD exports and scanned drawings well for extracting dimensions, labels and material call-outs, though accuracy depends on drawing quality and annotation consistency. Low-confidence extractions should be flagged for a quantity surveyor to verify rather than used blind.
How does AI speed up RFI (Request for Information) response?
An agent reads the incoming RFI, identifies which drawing, spec section or contract clause it relates to, checks for schedule impact, and routes it to the right discipline lead automatically - cutting the time between an RFI landing and someone starting to answer it.
What does AI-powered field service dispatch actually do?
It reads the incoming service request, checks technician availability, skills and proximity, and matches the job to the right person automatically, often pulling in equipment history so the technician arrives with context instead of discovering the issue on site.
Does this require replacing our existing project management or ERP software?
No - the agent layer connects through your existing project management, ERP or field service platform's API, adding document understanding and routing intelligence without displacing the system your team already works in.