AI Research Tool ROI

Measure one fixed task

Pick a task your team repeats, such as a market scan or a regulatory summary. Time it by hand over several runs. Then time it with each tool, including the time spent checking the output. Compare total time to a verified result, not to the first draft. Track how many tasks each tool completed without a rework cycle. Rework often hides the true cost of a fast tool.

Count verification as work. A fast draft that needs heavy checking can save little time. An error that reaches a client costs far more than the minutes it took to catch.

Why accuracy belongs in the math

A field experiment at Boston Consulting Group with 758 consultants, published as a working paper, found that AI improved productivity and quality on tasks inside the model's capability. On a task outside that capability, AI use lowered accuracy. Read the working paper before you build a business case on speed gains alone, since the results cover one firm, one model and one task set.

A simple model with placeholders

Use this structure in a spreadsheet: hours per task by hand, hours per task with the tool, minutes of checking per output, errors found in review, and the cost of an error. Leave the cost fields blank until you have measured them. Do not copy a vendor's time-saved figure into the model. Put the assumptions on a separate tab with a note on where each came from, so the model can be reviewed without reading the formulas.

Run the model on at least ten real tasks before deciding. Review the results at the end of each month, since tools and prices change.

Claims to discount

Vendor ROI claims often come without a method. Energent's strategy consulting page says consultants save about three hours a day and cites a 94.4% accuracy benchmark. Those are unverified vendor claims. The sources I reviewed did not include an independent measurement of time saved on research tasks. Compare pilot results with the cost of your current method, including staff time for research and any external fees.

Hyperresearch's case rests on output quality, not a time claim. Its DRACO run scored 77.7 in October 2026, and its method page explains the test. The first Deep report is free, so a team can measure its own result before paying for anything.

Checklist

• Choose one repeated task and time it by hand over several runs.
• Include checking time in every tool run.
• Count the errors found in review for each tool.
• Leave cost fields blank until you have measured them.
• Discount any vendor time-saved claim that lacks a method.

Questions & answers

Sources for this entry

• Navigating the Jagged Technological Frontier (working paper)
• Energent: AI for strategy consulting (vendor)
• Hyperresearch: DRACO benchmark method

Vendor descriptions are attributed to the vendor. Prices change; confirm with each vendor.

Continue this reading path

• Selection & fit
• AI-Powered Research Tool
• Resource directory

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