The Real ROI of an Answer Engine: How to Calculate the Value of Automating Your Knowledge Work

Most companies buy software based on features. Smart companies buy software based on Unit Economics.

When evaluating Generative AI or RAG (Retrieval-Augmented Generation), the question shouldn't be "Can it chat?" The question should be "How many hours of expensive human labor can it reclaim?"

At docusrch, we calculate ROI in two distinct layers:

1. The Baseline: Eliminating the "Search Tax" (Time spent looking).
2. The Bonus: Automating the "Work Tax" (Time spent doing).

Here is the breakdown of how much manual document work is actually costing you — and what you save when you automate it.

Layer 1: The "Search Tax" (Baseline ROI)

Every knowledge worker pays a tax just to do their job. Before they can write a report or close a deal, they have to find the information.

• The Stat: McKinsey estimates employees spend 1.8 hours every day (nearly 20% of the workweek) just searching for internal information.
• The Cost: For a 50-person team with an average salary of $80k, that wasted time costs roughly $72,000 per month.

The ROI

By deploying a Universal Answer Engine — where employees can ask questions and get instant, cited answers — you reclaim that 20%. Even if you only solve half the problem, the platform pays for itself in days, not months.

Layer 2: The Cost of "Doing" (The Opportunity)

Beyond simple search, there is a second, harder tax: the "Manual Work Tax."

Consider the manual workflows that slow your team down after they find the document:

1. The Compliance Review: A senior leader spending 90 minutes reading a contract to check for one specific clause.
2. The Data Extraction: An ops manager opening 50 invoices just to copy-paste the totals into Excel.
3. The First Draft: A sales rep spending 4 hours writing a proposal based on past case studies.

The Future: From Search to Agents

We believe the solution isn't just finding the document — it's automating the work.

We have moved beyond simple chat to build "Knowledge Agents" designed to handle these specific tasks — reading, extracting, and drafting — automatically.

To learn how we are automating these complex workflows, read our deep dive: What are AI Knowledge Agents?

Conclusion: Do the Math

You don't need to guess if AI is worth it. Just look at your team's calendar.

• Are they digging for files? (The Search Tax)
• Are they manually reviewing contracts or copy-pasting data? (The Work Tax)

If the answer is yes, you are paying a premium for manual labor that an Answer Engine could do for pennies.

Ready to reclaim that time?