Shared research study link

Civil Engineering Workflows & AI Adoption Study

Understand how civil engineers currently work - the tools they use, challenges they face, time spent on manual tasks like takeoffs and code lookups, and their perspectives on AI as a solution for automating engineering workflows

Study Overview Updated Jan 23, 2026
Research question: How civil engineers work today (tools, challenges, time spent on manual takeoffs/code lookups) and what they want from AI to automate workflows. Research group: 10 US/UK professionals spanning CAD and project engineers, a principal structural, a GIS technician, and EHS/training leads across design, permitting, CA, and closeout.

What they said: Teams run construction‑first workflows on Civil 3D/AutoCAD, Revit, Bluebeam, QGIS, and HEC tools, but lose time at the seams-PDF/Excel retyping, CAD↔GIS/projection mismatches, brittle xrefs/CDE sync, and late survey/geotech. Manual “glue” work consumes 10–15 hrs/week (rising to 18–25 at submittals) for takeoffs, spec/drawing searches, cross‑doc reconciliation, and relinking after cloud hiccups. AI is used cautiously for text/scripting; they reject black‑box design and require offline/local options, deterministic outputs with full provenance, and native integrations that keep labels, schedules, and reports in sync.

  • Prioritize offline‑first, deterministic integrations inside existing tools; ship quick wins: Bluebeam→task/log sync, PDF set diff with change‑clouding, a units/CRS/datum sentinel, issue packager, and title‑block↔CDE register sync.
  • Mid‑term bets: a robust CAD↔GIS cleaner and a single‑source hydrology dataset that drives native Civil 3D labels plus reviewer‑ready reports with explicit math, units, and citations-always behind approve‑before‑change and full logs.
  • Define success by time saved (≥5 hrs/user/week by month 6), fewer seam errors (≥60% drop in unit/CRS/xref failures), and adoption gates met (on‑prem/tenant, reproducibility, auditability).
Participant Snapshots
10 profiles
Edina Marzan
Edina Marzan

Bakersfield-based, 26, Hispanic civil-engineering grad, not currently working. Faith-driven, bilingual, budget-wise homeowner supporting family and studying for FE. Values fairness, clarity, durability, and community; prefers practical, transparent products…

Demitrius Lain
Demitrius Lain

Rural Virginia civil engineer, 36, married with one child. Faith-centered, pragmatic, and ROI-focused. Balances hybrid field work with family life, DIY projects, and outdoor pursuits. Prefers durable, compliant, evidence-backed solutions and transparent ser…

Chancelor Mullen
Chancelor Mullen

Chancelor Mullen is a 29-year-old project engineer in rural Missouri, married, no kids. Practical, community-minded, and data-driven. Balances home renovations with outdoor hobbies. Prefers durable, repairable products and transparent service; skeptical of…

Peter Schlenker
Peter Schlenker

59-year-old veteran structural engineer in rural Nebraska; married, no kids. High-income, pragmatic, privacy-aware. Values durability, TCO, and community resilience. Hybrid work, field-heavy. Mentors youth, grills on weekends, travels by road.

Ashley Vieu
Ashley Vieu

Practical, community-minded single mom in rural Virginia. Ashley is a Learning & Development Coordinator in engineering. Budgets carefully, owns home outright, uses public healthcare, values durability, clear pricing, and kid-friendly, offline-capable solut…

Aoife Brennan
Aoife Brennan

Aoife, 19, Irish in Leeds, is a junior CAD tech earning around £31k. Practical, warm, and eco-minded, she budgets carefully, loves gigs and thrifting, and prioritizes durability, clarity, and fairness in choices.

Marek Kowalski
Marek Kowalski

Marek, 44, is a Polish-born CAD technician in Leeds, married with one child. Budget-conscious and practical, he values reliability, clear information, and family time, balancing remote work, DIY projects, and community-minded routines.

Calum Fraser
Calum Fraser

Practical, family-first civil engineering technician in Fife. Budget-conscious, values durability and transparency. Walks to work, enjoys DIY, football, and coastal walks. Prefers straightforward solutions, local services, and kid-friendly, energy-efficient…

Kirsty MacLeod
Kirsty MacLeod

33-year-old Glasgow-based GIS technician, Scottish-Filipino heritage, single and renting with a rescue cat. Pragmatic Conservative, outdoorsy, budget-conscious, and community-minded. Values durability, clear pricing, and local relevance; enjoys hillwalks, g…

Conor Kavanagh
Conor Kavanagh

Irish single dad in Barry, 37, associate technical CAD role, walks to work, rents privately, tight but steady budget, values durability and clarity. Co-parents an 8-year-old, loves rugby, coastal life, DIY, and straightforward tech.

Overview 0 participants
Sex / Gender
Race / Ethnicity
Locale (Top)
Occupations (Top)
Demographic Overview No agents selected
Age bucket Male count Female count
Participant locations No agents selected
Participant Incomes US benchmark scaled to group size
Income bucket Participants US households
Source: U.S. Census Bureau, 2022 ACS 1-year (Table B19001; >$200k evenly distributed for comparison)
Media Ingestion
Connections appear when personas follow many of the same sources, highlighting overlapping media diets.
Questions and Responses
7 questions
Response Summaries
7 questions
Word Cloud
Analyzing correlations…
Generating correlations…
Taking longer than usual
Persona Correlations
Analyzing correlations…

Overview

Respondents describe a civil engineering workflow fractured across specialist tools (Civil 3D/AutoCAD, Revit, QGIS, Bluebeam, HEC‑RAS/MicroDrainage) where most time loss comes from ‘glue’ work: PDF/Excel reconciliation, xref/CDE sync, coordinate/units mismatches and manual takeoffs/spec hunting. AI is already used for text, scripting and small automations but adoption is conditional: near‑term value is in deterministic, auditable, offline‑capable features that eliminate plumbing work (xref fixes, CAD↔GIS cleaning, markup→task→model round trips). There is strong, consistent distrust of black‑box generative AI for sealed calculations or design decisions; senior/licensed engineers demand reproducible calc trails and code citations as prerequisites for trust.
Total responses: 70

Key Segments

Segment Attributes Insight Supporting Agents
UK engineering technicians (shop / CAD‑focused)
locale
United Kingdom (Wales, Scotland, Leeds area)
occupation
Engineering Technician / CAD technician
age range
19–44
education
Apprenticeship / Level 3 / no formal degree
focus
CAD hygiene, templates, offline reliability, quick automations
This group prioritises pragmatic, file‑level reliability and simple automation (AutoLISP, macros). They value offline/local workflows, consistent layer/style templates, and tools that automatically repair xrefs, unit/coordinate mismatches and other file‑plumbing issues rather than speculative design AI. Conor Kavanagh, Marek Kowalski, Calum Fraser, Aoife Brennan
US licensed / practising civil engineers (analysis & liability‑aware)
locale
United States (rural NE/VA/MO)
occupation
Civil Engineer / Principal / Project Engineer
age range
29–59
education
Bachelor / Graduate
licensing
EIT / PE present
focus
Auditability, deterministic calculations, liability
Senior/licensed engineers accept AI for non‑critical tasks (text, scripting) but will only trust AI that produces full, auditable input→output trails, deterministic reruns, editioned code citations and reproducible calculations. They view AI‑driven design or sealed calculations as unacceptable without formal verification and traceability. Demitrius Lain, Peter Schlenker, Chancelor Mullen
EHS / training / field‑facing roles
locale
United States (rural VA, Bakersfield CA)
occupation
Corporate Trainer / Finishes QA / Field Admin
age range
26–40
focus
Roster management, offline UX, bilingual communication, punchlists
Field and compliance staff care less about CAD plumbing and more about reliable, portable deliverables: offline sign‑in, roster/portal syncing, bilingual punch outputs, simple one‑page handovers and phone‑friendly evidence. Their priority is robust, low‑friction handover and compliance rather than advanced CAD integrations. Ashley Vieu, Edina Marzan
GIS / data analysts
locale
UK (Scotland & urban centres)
occupation
GIS / Data Analyst
education
Degree / Level 4+
focus
CRS/projection integrity, metadata, style translation
GIS practitioners see CAD→GIS friction as a major bottleneck: coordinate reference and unit mismatches, exploded blocks, lost styling and large raster handling. They want deterministic CAD→GIS cleaning, automated metadata capture and style translation rather than generative design AI. Kirsty MacLeod, Marek Kowalski
Younger / junior techs & early career staff
age range
19–33
occupation
Junior CAD tech / Technician / Data Analyst
education
Apprenticeship / Level 3 / Degree
focus
Small automation, scripting help, clear guidance
Junior technicians are the most open to small AI assists (drafting emails, generating simple scripts, code snippets) and see value in tools that reduce repetitive data entry. However, they remain sceptical of AI for safety‑critical or spatial design tasks and request transparent guidance and guardrails. Aoife Brennan, Kirsty MacLeod, Chancelor Mullen

Shared Mindsets

Trait Signal Agents
Toolchain fragmentation and time lost to 'glue' work Most respondents rely on PDFs and Excel as improvised integration layers and spend significant weekly hours reconciling outputs between Civil 3D, hydro tools, QGIS and Bluebeam. There is high demand for tooling that removes repetitive document reconciliation and copy/paste workflows. Chancelor Mullen, Marek Kowalski, Conor Kavanagh, Calum Fraser, Demitrius Lain, Aoife Brennan
Coordinate / units / CRS friction is ubiquitous Frequent errors from mm vs m, local grids vs national grids, or wrong EPSG settings cause rework and conservative local‑mirroring; respondents want automated detection and correction of CRS/unit mismatches. Conor Kavanagh, Kirsty MacLeod, Calum Fraser, Marek Kowalski
CDE / cloud sync fragility drives offline workarounds SharePoint/Desktop Connector/portal sync problems (ghost locks, broken xrefs, path issues) push teams to local mirroring and conservative workflows. Offline‑first or robust sync recovery is a clear product requirement. Marek Kowalski, Calum Fraser, Demitrius Lain, Aoife Brennan
Bluebeam (PDF) remains the trusted review hub Bluebeam is central to review, markup and QA workflows; teams expect any automation to integrate with markup→RFI→task flows and preserve Redline provenance. Chancelor Mullen, Marek Kowalski, Conor Kavanagh, Aoife Brennan
Cautious, conditional AI adoption Across demographics there is pragmatic willingness to use AI for admin, documentation and small automations but strong resistance to black‑box outputs for sealed calculations or design without auditable trails, deterministic reruns and code citations. Edina Marzan, Conor Kavanagh, Peter Schlenker, Demitrius Lain, Aoife Brennan, Kirsty MacLeod
Preference for offline‑first, auditable integrations Respondents repeatedly ask for deterministic, versioned outputs, local processing options, and full logs that tie calculations and model changes back to source inputs-prerequisites for trust in engineering contexts. Peter Schlenker, Demitrius Lain, Kirsty MacLeod, Conor Kavanagh, Marek Kowalski

Divergences

Segment Contrast Agents
US licensed / practising civil engineers Much higher insistence on formal audit trails, deterministic reruns and citation‑level links to codes/editions compared with technicians and junior staff who focus on immediate productivity gains. Peter Schlenker, Demitrius Lain, Chancelor Mullen
UK CAD technicians vs GIS / data analysts CAD technicians emphasise layer/style hygiene, xref plumbing and AutoCAD macros; GIS analysts prioritise CRS integrity, metadata and style translation-both want automation but target different failure modes in handoffs. Conor Kavanagh, Marek Kowalski, Kirsty MacLeod
EHS / field roles vs design teams Field and compliance staff prioritise roster/portal syncing, offline sign‑in and bilingual handovers over upstream CAD/analysis fixes. Their product needs are deliverable‑centric rather than model/analysis‑centric. Ashley Vieu, Edina Marzan
Younger / junior techs vs senior engineers Younger staff are more open to experimental AI assistance (scripts, prompts, drafting) while senior/licensed engineers require hardened, auditable features and are less tolerant of probabilistic outputs. Aoife Brennan, Kirsty MacLeod, Peter Schlenker
Creating recommendations…
Generating recommendations…
Taking longer than usual
Recommendations & Next Steps
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Overview

Civil engineers lose 10–15 hrs/week to manual “glue” work across Civil 3D/Revit/QGIS/Bluebeam/SharePoint and portals. The action plan builds an offline-first, deterministic, auditable assistant that lives inside existing tools to remove the high-friction joins:
  • Markup → task/log sync with provenance
  • Units/CRS/datum sentry and CAD↔GIS cleaning
  • DWG/PDF revision diff + auto change-clouding
  • Title block ↔ CDE register sync and issue packaging
  • Single-source hydro dataset driving plan labels + reports with a full calc trail
Guardrails: approve-before-change, version-locked runs, explicit citations, and local/tenant deployment to address liability, trust and data privacy.

Quick Wins (next 2–4 weeks)

# Action Why Owner Effort Impact
1 Bluebeam → Task CSV bridge (offline-capable) Eliminates hours of retyping PDF markups into Excel/SharePoint logs; reduces missed items in QA. Eng - PDF Integrations Low High
2 PDF set diff + auto change-clouding Fast, accurate deltas between revisions; kills manual sheet compares that spike before submittals. Eng - Doc Processing Med High
3 Title block ↔ CDE register sync (SharePoint/ACC) Removes double entry; aligns sheet attributes with issue registers to prevent version drift. Eng - CDE Connectors Med High
4 Units/CRS/Datum Sentinel (CLI + GUI) Catches mm↔m, USFT↔FT, CRS/rotation errors-the top reported source of field mistakes. Eng - CAD/GIS Platform Low High
5 Quantity delta kit (Civil 3D → Excel PowerQuery) Standardizes takeoff deltas and audit trails; avoids copy/paste errors across revisions. Solutions - Workflow Low Med
6 Issue packager (naming, zips, receipts, watermarks) Cuts 30–45 min per issue cycle; reduces portal rejections for naming/size. Eng - Workflow Low Med

Initiatives (30–90 days)

# Initiative Description Owner Timeline Dependencies
1 CAD Glue SDK v1 (Civil 3D + Bluebeam) A local plugin suite that fixes the plumbing around drawings:
  • Xref repair, style/parts governance, sheet-set QA
  • DWG compare (label/object-aware) + pre-issue checks
  • Bluebeam round-trip: markups → tasks → CAD jump-to
  • Runs offline, logs every action, approve-before-change
Eng - CAD Platform 0–6 months: alpha (internal) → pilot (3–5 firms) → beta (wider) Autodesk APIs (AutoCAD/Civil 3D), Bluebeam Revu API/Studio access, Pilot client templates/styles
2 Single-source Hydrology Dataset + Label/Report Sync Import SSA/HydroCAD to a versioned dataset that drives native Civil 3D labels and generates reviewer-ready reports with equations, units and citations. No black-box sizing; deterministic reruns with diffs. Eng - Analysis Integrations 4–8 months: parse/import → label binding → report generator Vendor import agreements (SSA/HydroCAD), PE advisory board for calc trail/rounding rules, Real-project QA harness
3 Deterministic CAD↔GIS Cleaner Robust CAD→GIS→CAD pipeline: detect/fix CRS & units, explode/flatten safely, map attributes, and translate styles QGIS↔ArcGIS. Emits GeoPackage/clean DWG with full metadata. Eng - Geo 3–7 months: detection → mapping rules → style translator QGIS/ArcGIS plugin SDKs, Sample OS/BNG + US datasets, Licensing review for basemaps
4 Offline-first CDE/Portal Packager One-upload to push submittals to SharePoint/ProjectWise/Procore with naming/size rules, queued offline sync, conflict resolution, and receipt logging back to the register. Eng - Connectors 5–9 months: SharePoint/Procore first → ProjectWise Partner/API agreements (Procore, ProjectWise, ACC), Legal/privacy review, Customer metadata schemas
5 Field As-built & Photo Linker (bilingual, offline) Mobile capture that tags photos/notes to chainage and sheets, produces bilingual punch/closeout PDFs, proposes DWG edits for as-builts, and assists drone alignment with control residuals. Product - Mobile/Field 6–10 months: PWA offline MVP → native wrappers Mobile offline storage/sync, Bilingual templates (EN/ES, EN/PL), Pilot jobs with CA/closeout
6 Governance, Security & Audit Layer Cross-cutting: tenant/on-prem deployment, version-locked runs, full input→output logs (CSV/PDF), PII guards, and approve-before-change policy enforcement across all modules. Security & Compliance 0–12 months in parallel with modules SOC2/ISO controls, IT security review with pilots, Legal (NDA, data-processing addendum)

KPIs to Track

# KPI Definition Target Frequency
1 Hours saved per user/week Self-reported + telemetry-estimated hours eliminated by markup→task, diffing, packaging and CAD QA automation >=5 hrs/user/week by month 6 (pilot median) Monthly
2 Prevented error incidents Count of flagged unit/CRS/xref/path/style mismatches before issue (per 10k files scanned) >=50 detections/10k files; ≥60% decline in downstream field errors by month 9 Monthly
3 % outputs with full audit trail Share of assisted actions with exportable logs (inputs, versions, diffs, citations) 95%+ of actions logged/exportable Monthly
4 Offline sync success rate Successful queued jobs that sync without conflict or data loss >=99% success Monthly
5 Time-to-issue reduction Avg hours from review complete to issued package vs baseline per project -30% by month 6; -40% by month 9 Quarterly
6 Adoption/Activation Weekly active users of CAD Glue SDK and count of active projects using at least 2 modules 50 WAU/10 projects by month 4; 200 WAU/40 projects by month 9 Weekly

Risks & Mitigations

# Risk Mitigation Owner
1 API/license constraints with Autodesk/Bluebeam/Procore/ProjectWise limit deep integrations Prioritize sanctioned plugin surfaces; secure partner agreements; design file-first fallbacks; stage features per vendor policy BD + Eng Partnerships
2 Perceived liability if tools are seen as making design decisions Hard guardrails: approve-before-change, no auto-sizing, calc trails + citations, disclaimers; PE advisory board reviews Product + Legal
3 Data privacy/tenant requirements block cloud use Offer on-prem/tenant deployments; local processing; zero-retention modes; DPA/SOC2; redaction options Security & Compliance
4 Offline sync conflict complexity degrades trust Deterministic conflict resolution, dry-run previews, robust rollback; pilot in low-risk workflows first Eng - Sync
5 Change management and senior-user skepticism Deploy as boring helpers inside existing tools; measure ROI; training with checklists; opt-in pilots that showcase audit wins Customer Success
6 Regional standards/CRS nuances cause wrong defaults Region packs (US/UK first), explicit unit/CRS banners, editable rulesets, and test suites with messy real data Eng - Geo + PM

Timeline

0–2 months: Ship quick wins (markup→CSV, Units/CRS Sentinel, issue packager); recruit 3–5 pilot firms; finalize partner/API access.

2–4 months: CAD Glue SDK alpha (xref/style QA, DWG compare, pre-issue checks); PDF set diff GA; begin CDE sync POC.

4–6 months: CAD Glue SDK pilot; Title block↔CDE sync GA; start Hydrology dataset → labels/report beta; CAD↔GIS cleaner beta.

6–9 months: Hydrology + label/report GA; CAD↔GIS cleaner GA; Offline CDE packager GA (SharePoint/Procore); field photo/as-built MVP.

9–12 months: Field module GA (bilingual/offline); expand connectors (ProjectWise); scale pilots to 40+ projects; harden audit/security across modules.
Research Study Narrative

Civil Engineering Workflows & AI Adoption Study - Executive Synthesis

Objective: Understand current civil engineering workflows-the tools used, pain at the seams between tools, time spent on manual tasks (takeoffs, code/spec lookups, reconciliation), and pragmatic expectations for AI that could safely automate the “glue” without risking safety or liability.

How work gets done-and where it breaks

Teams follow a pragmatic, construction-first cadence: kickoff and scope; base data setup (survey/geotech, coordinates); concept checks; detailed design and sheet production; QA/QC and revision control; permitting/bidding; construction support; and as-built closeout. Respondents stressed “no data, no design” and disciplined CAD standards-“buildable, printable sheets” over glossy outputs (Conor Kavanagh). Biggest schedule multipliers: missing/late survey and geotech, ambiguous briefs/late changes, and permitting delays.

Across tools (Civil 3D/AutoCAD, Revit, QGIS, Bluebeam, HEC-RAS/MicroDrainage, drone photogrammetry), the time tax accumulates at the joins. PDF and Excel are the de facto glue, with brittle import/export, coordinate/projection mismatches, xref/path breakage, and fragile cloud/CDE sync (SharePoint/Desktop Connector). “I spend too much time shimming gaps with exports, PDFs, and Excel” (Chancelor Mullen); “One bad day and every xref goes missing” (Marek Kowalski).

Time and error profile (cross-question evidence)

  • Manual hours: 10–15 hours/week typical; 18–25+ hours during tenders/submittals/CA. “12–18 hours per week… 20–25 during submittal season” (Peter Schlenker).
  • Top sinks: reconciliation across documents (storm report vs plan labels; geotech vs typicals), quantity takeoffs, and portal/CDE duplication. Poor OCR/scanned PDFs amplify time (Demitrius Lain).
  • Error hotspots: handoffs/version drift, manual re-entry of Bluebeam markups, unit/CRS/datums mismatches (“mm vs metres… one ghost shift and your sections look drunk”), BIM round-trips that strip semantics, and late/incomplete site data.

AI today: narrow utility, strict conditions

Adoption is pragmatic: AI is used as a grunt-work assistant for text, bilingual punch notes, and small scripting (AutoLISP/Python/Excel). Automated takeoff on civil PDFs underperforms (hatches, clipped xrefs, scales), often costing rework (“I binned it and did the counts by hand,” Conor). Trust hinges on local/offline options, auditable input→output traces, deterministic reruns, and data isolation. “If I cannot audit inputs and units line by line, it is a non-starter” (Chancelor); “When it floods or clashes, who owns it?” (Aoife Brennan).

Persona nuances

  • UK CAD techs prioritize xref/layer hygiene, unit/CRS sanity checks, and offline reliability (Conor, Marek, Calum, Aoife).
  • US licensed engineers require reproducible calcs, editioned code citations, and clear liability boundaries (Peter, Demitrius, Chancelor).
  • EHS/field roles value offline/bilingual punch, roster/portal sync, and evidence capture over upstream CAD fixes (Ashley, Edina).
  • GIS analysts want deterministic CAD→GIS cleaning, metadata, and style translation (Kirsty, Marek).

Recommendations (actionable, low‑risk)

  • Bluebeam→Task bridge (offline-capable): auto-sync markups to CSV/logs to end manual retyping and missed items.
  • Units/CRS/Datum sentinel: detect mm↔m, grid/rotation errors and fix before issue.
  • PDF set diff + auto change-clouding: fast, trustable deltas that update sheet indexes.
  • Title block ↔ CDE register sync (SharePoint/ACC): remove duplicate entry and version drift.
  • Deterministic CAD↔GIS cleaner: safe explode/flatten, attribute mapping, style translation to GeoPackage/clean DWG.
  • Single-source hydrology dataset → labels/reports: bind native Civil 3D labels and reviewer-ready reports with equations, units, and citations.

Guardrails and risks

  • Approve-before-change only; no auto-sizing or black-box geometry.
  • Version-locked, deterministic runs with full input/output logs and editioned citations.
  • Local/tenant deployment and zero-retention modes to satisfy privacy/IP constraints.
  • Mitigate vendor/API limits via sanctioned plugins and file-first fallbacks.

Next steps and measurement

  • 0–2 months: Ship Bluebeam→CSV and Units/CRS Sentinel; recruit 3–5 pilot firms; secure API/partner access.
  • 2–6 months: Launch PDF diff; pilot Title block↔CDE sync; beta CAD Glue SDK (xref/style QA, DWG compare) and CAD↔GIS cleaner.
  • 6–9 months: GA hydrology dataset→labels/reports; offline CDE packager (SharePoint/Procore); field photo/as-built MVP (bilingual, offline).
  • KPIs: hours saved/user/week (target ≥5 by month 6); prevented unit/CRS/xref errors (≥50 detections/10k files; ≥60% downstream error reduction by month 9); % actions with exportable audit trails (≥95%); offline sync success (≥99%); time-to-issue reduction (−30% by month 6, −40% by month 9).
Recommended Follow-up Questions Updated Jan 23, 2026
  1. Which roles must approve adoption of new engineering software at your organization (e.g., IT/security, BIM/CAD manager, discipline lead, procurement, legal, client representative)?
    multi select Informs enterprise sales motion, stakeholder mapping, and required security/procurement collateral.
  2. What is the maximum per-seat monthly price you would realistically pay for an AI assistant that reliably saves 5–10 hours per week?
    numeric Guides pricing strategy and ROI messaging for initial packaging.
  3. For each task below, indicate the minimum acceptable accuracy (%) required for you to adopt automation: quantity takeoffs; spec/code lookup; PDF revision diffing; coordinate/unit (CRS) checks; OCR of scanned drawings.
    matrix Sets quantitative performance thresholds for MVP acceptance by task.
  4. Which validation and provenance features would you require to trust automated outputs (e.g., source citations, side‑by‑side diffs, unit/CRS transformation logs, calculation steps, version locking, approval checkpoints)?
    multi select Prioritizes trust-building UX and audit features needed for adoption.
  5. How often do you work without reliable internet connectivity on project workstations?
    frequency Calibrates offline-first architecture, caching, and sync design requirements.
  6. Among potential integrations (e.g., Civil 3D, Revit, Bluebeam, QGIS, SharePoint/OneDrive, ProjectWise, Procore, HEC tools), which are most versus least essential for a first release?
    maxdiff Ranks integration targets to sequence partnership and engineering effort.
Questions target gaps in procurement, pricing, performance thresholds, trust requirements, offline constraints, and integration prioritization to derisk go-to-market and roadmap.
Study Overview Updated Jan 23, 2026
Research question: How civil engineers work today (tools, challenges, time spent on manual takeoffs/code lookups) and what they want from AI to automate workflows. Research group: 10 US/UK professionals spanning CAD and project engineers, a principal structural, a GIS technician, and EHS/training leads across design, permitting, CA, and closeout.

What they said: Teams run construction‑first workflows on Civil 3D/AutoCAD, Revit, Bluebeam, QGIS, and HEC tools, but lose time at the seams-PDF/Excel retyping, CAD↔GIS/projection mismatches, brittle xrefs/CDE sync, and late survey/geotech. Manual “glue” work consumes 10–15 hrs/week (rising to 18–25 at submittals) for takeoffs, spec/drawing searches, cross‑doc reconciliation, and relinking after cloud hiccups. AI is used cautiously for text/scripting; they reject black‑box design and require offline/local options, deterministic outputs with full provenance, and native integrations that keep labels, schedules, and reports in sync.

  • Prioritize offline‑first, deterministic integrations inside existing tools; ship quick wins: Bluebeam→task/log sync, PDF set diff with change‑clouding, a units/CRS/datum sentinel, issue packager, and title‑block↔CDE register sync.
  • Mid‑term bets: a robust CAD↔GIS cleaner and a single‑source hydrology dataset that drives native Civil 3D labels plus reviewer‑ready reports with explicit math, units, and citations-always behind approve‑before‑change and full logs.
  • Define success by time saved (≥5 hrs/user/week by month 6), fewer seam errors (≥60% drop in unit/CRS/xref failures), and adoption gates met (on‑prem/tenant, reproducibility, auditability).