Compare / Manual Entry vs AI Extraction
Manual Invoice Data Entry vs. AI Extraction
Manual entry is accurate when done carefully — but it's the biggest time sink for bookkeepers processing more than 20 invoices a month. Here's an honest look at where each approach holds up.
Time and cost by volume
*Manual cost based on $30/hr bookkeeper rate
| Volume | Manual Time | Manual Cost* | SkipEntry Time | SkipEntry Cost |
|---|---|---|---|---|
| 50 invoices/mo | ~2 hours | ~$60 | ~5 minutes | Free (50 pages) |
| 200 invoices/mo | ~8 hours | ~$240 | ~20 minutes | $49/mo |
| 1,000 invoices/mo | ~40 hours | ~$1,200 | ~90 minutes | $149/mo |
| 5,000 invoices/mo | ~200 hours | ~$6,000 | ~8 hours | $349/mo |
What manual entry gets right
A careful human reviewer catches things that AI extraction can miss — context-dependent errors, unusual line item descriptions, or fields that require judgment rather than recognition. If your practice processes 10–20 invoices a month from a small set of familiar vendors, manual entry may be fast enough that automation isn't worth the change.
Manual entry also requires no software setup, no learning curve, and no subscription. For a solo bookkeeper with low volume, the status quo can be a reasonable choice.
Where manual entry breaks down
The problems compound with volume. At 200+ invoices a month, manual entry consumes a significant portion of billable hours — time that can't be spent on higher-value work or new clients.
- Volume fatigue. Accuracy drops during high-volume runs. Transcription errors on amounts are hard to catch without a second review pass.
- Vendor variety. Every vendor formats their invoice differently. Context-switching between formats slows entry and increases mistakes.
- Scanned invoices. Faded ink, rotated pages, handwritten notes — scanned invoices are significantly slower to enter manually and more error-prone.
- No audit trail. Manual entry leaves no record of what was extracted from where. AI extraction creates a linkage between source PDF and extracted data.
- Scale ceiling. Growing a bookkeeping practice means hiring more staff just for data entry, rather than more capacity for advisory work.
A hybrid approach: the best of both
The most effective workflow isn't fully automated or fully manual — it's AI extraction with human review. The AI handles the mechanical work of reading and structuring data. The bookkeeper reviews, corrects, and confirms.
This is exactly how SkipEntry is built. The side-by-side review interface shows the original PDF on the left and the extracted data on the right. Any field can be corrected with a click. Math validation flags discrepancies before you export. Corrections teach the system, so accuracy on that vendor improves over time.
The result: the speed of automation with the accuracy of human oversight. Bookkeepers who switch typically spend 10–15 minutes reviewing what previously took hours to type.
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