AI vs Manual Takeoff: Speed, Accuracy, and Cost
AI takeoff tools (Togal.ai, STACK) cut initial quantity time by 60-70% on clean plans but require 1.5-4 hours of review to catch errors. Manual takeoff in PlanSwift is slower but more reliable on complex or frequently revised plans. The break-even is roughly 12-15 bids per year. Most shops should run AI for first-pass quantities and fall back to manual for revisions and specialty scopes.
After spending several months testing AI takeoff tools on real commercial bids, I kept coming back to the same question: is this actually saving my team time, or is it creating a different kind of work? The answer is more nuanced than vendor demos suggest. This comparison lays out what I found across speed, accuracy, and total cost — for both approaches.
How I Ran This Comparison
I compared AI takeoff against manual methods across three project types: a 12,000 SF tenant improvement, a 45,000 SF tilt-up warehouse, and a 180,000 SF multifamily building. Manual takeoff was done by experienced estimators using PlanSwift with digitized PDF plans. AI takeoff was done using Togal.ai and STACK’s AI-assisted module on the same plan sets.
The comparison criteria:
- Time to complete initial quantity takeoff
- Accuracy against field-verified quantities (checked against actual material orders on two completed projects)
- Error types (what kinds of mistakes each approach makes)
- Total cost including software licensing and labor
- Revision handling when plans change mid-bid
Feature-by-Feature Breakdown
Speed
Manual takeoff on the 12,000 SF TI took one estimator about 6 hours to complete quantities for all trades — including noting ambiguities and flagging plan conflicts. For the warehouse at 45,000 SF, the same estimator needed roughly 18 hours across two days.
AI takeoff on the same TI ran in about 40 minutes to generate initial quantities, with another 90 minutes of review and correction. For the warehouse, AI generated quantities in under 2 hours, with 3-4 hours of review. The review step is not optional — I’ll explain why below.
Net result: AI is meaningfully faster on straightforward projects. The gap closes on complex jobs because review time scales with plan complexity, not just square footage.
Accuracy
This is where the comparison gets complicated. For the two projects where I could check against actual material orders:
- Concrete quantities (slabs, walls): AI was within 3-5% on both projects. Manual was within 2-4%. Comparable.
- Framing lumber/steel studs: AI was within 8% on the TI. Manual was within 4%. Manual won here — the AI missed several recessed areas in the plans.
- MEP rough-in: Both approaches rely on plan markups from subs. Neither AI nor manual takeoff replaces sub pricing for mechanical, electrical, and plumbing on any project I’ve worked on.
- Finishes (flooring, paint, ceiling tile): AI accuracy varied significantly based on plan quality. Blurry PDFs or hand-drawn plan revisions caused obvious errors. Manual was more consistent because estimators interpret ambiguous drawings; AI tools currently don’t.
The failure mode for AI is different from manual. Manual errors tend to be math mistakes or missed areas — things a second estimator catches in review. AI errors tend to cluster around plan ambiguity: partial walls that aren’t clearly dimensioned, details on separate sheets not cross-referenced, or phased work where plan overlaps create confusion. You need to know what to look for.
Revision Handling
When plans change — and on most jobs, they do — this is where AI tools show their biggest limitation today.
Manual takeoff in PlanSwift lets you select specific areas of the plan, delete old quantities, and re-digitize just the changed area. Experienced estimators can handle a plan revision for a 5,000 SF portion of a larger project in 30-45 minutes.
AI tools currently require you to re-upload revised sheets and re-run the analysis. Most tools don’t have delta comparison that automatically flags only what changed between revisions. Togal.ai’s roadmap has mentioned revision tracking, but it wasn’t production-ready during my testing. Re-running the full AI takeoff and re-reviewing takes nearly as long as the initial run for a partial revision — which eliminates most of the time advantage on fast-moving bids.
Pricing Comparison
| Manual (PlanSwift) | AI (Togal.ai) | AI (STACK) | |
|---|---|---|---|
| Software cost | ~$1,595/year per seat | ~$4,800/year (entry tier) | ~$3,600/year (entry tier) |
| Labor: initial takeoff | 6-18 hrs @ $45-85/hr | 2-6 hrs @ $45-85/hr | 2-6 hrs @ $45-85/hr |
| Labor: review | 1-2 hrs | 1.5-4 hrs | 1.5-4 hrs |
| Break-even (bids/year) | — | ~12-15 bids | ~10-12 bids |
The labor math favors AI if you’re doing 15+ bids per year on projects over 10,000 SF. Below that volume, the software cost eats the time savings. For estimating shops bidding a high volume of repeat project types — same tenant improvement chain, same warehouse tenant — AI pays back faster because the review time drops as estimators learn what errors to look for on that plan type.
One cost that’s easy to undercount: training time. Getting an estimator comfortable enough with AI takeoff to trust and verify the output without over-reviewing it takes about 4-6 weeks of regular use. That’s real onboarding cost, even though no one puts it in the ROI spreadsheet.
Best For: Each Approach
Manual takeoff is the better choice when:
- Plans are complex, heavily marked up, or involve multiple plan revision cycles mid-bid
- The project type is unusual or requires significant estimator interpretation
- Your bid volume is under 10 projects per year
- You’re working from incomplete plans where estimator judgment fills in gaps
- The project involves significant specialty work with custom components
AI takeoff is the better choice when:
- Plans are clean and well-organized (fully digitized, clear dimensions, consistent notation)
- You bid similar project types repeatedly (ground-up retail, standard TI, light industrial)
- Your team is doing high-volume estimating and initial takeoff is the time bottleneck
- You want a fast sanity check on quantities before sending to subs
- You have someone on your team who can own the review process and learn the tool’s failure patterns
Honest Verdict
If I were setting up an estimating workflow from scratch for a GC bidding 20+ commercial projects per year with consistent plan quality, I’d use AI takeoff as the first pass and keep manual digitizing as the fallback for complex revisions and specialty scopes. The hybrid approach captures most of the speed benefit while keeping the accuracy floor high enough to bid on.
What I wouldn’t do: give AI-generated quantities to a project manager without review, or use an AI takeoff to price a project with complicated phasing, demolition, or hand-sketched plan revisions. The tool is only as reliable as the plan quality and the estimator reviewing the output.
The fundamental tradeoff is this: manual takeoff is slower but more error-resistant on complex inputs. AI takeoff is faster but requires a more disciplined review process to catch the errors it makes. Neither approach is obviously superior — it depends on your project mix, bid volume, and whether your estimating team has the bandwidth to build review fluency with a new tool.
For most estimating shops, the right answer in 2026 is a hybrid: AI for initial quantities on clean plans, manual for revisions and anything complicated. The tools are improving, and revision tracking is the feature that will shift the balance if vendors ship it reliably.