You do not need a complicated business case for internal AI. Two numbers will tell you almost everything.
Internal knowledge AI is easy to get excited about and easy to over-justify. Skip the vague productivity-uplift claims. There are two concrete ROI stories, and for most 200 to 800 person companies, either one on its own is enough.Here is how to model both with numbers you already have.
ROI 1: Onboarding ramp reduction
New hires are expensive precisely when they are least productive: the ramp period, when they cannot yet find answers on their own. Cut that period and you capture real money.Take your new hires per year. For a 500-person company with 20 percent turnover, that is roughly 100.Estimate a daily productivity cost. At a 60,000 fully-loaded salary over about 250 working days, that is roughly 240 per day.Compare baseline ramp to ramp with self-serve answers. Instant, source-cited answers can move a 90-day ramp toward roughly 28 days.Run those numbers and the annual saving for a single 500-person company lands in the seven figures.
Two independent ROI stories. Any one of them is usually enough to justify the decision.
ROI 2: Recovered search time
The second story applies to every employee, not just new ones. People spend a large share of the work week looking for information that already exists, consistently around one in five hours. Take your headcount and average salary, estimate the share of the week lost to searching, and the portion an instant answer engine can recover. Even recovering a fraction returns a large number across a few hundred employees.
- Baseline first. Measure current ramp time or time-to-answer before you switch anything on.
- Pick one number. Track a single clear metric through the pilot, not a dashboard of vanity stats.
- Tie it to money once. Convert the operational metric into a cost figure a single time, using your real salary and headcount data.
The point
You do not have to take ROI on faith. Pick the story that fits your company, model it with your own numbers, then prove it with a five-day pilot on one team. If the math works on paper and holds up in the pilot, the decision makes itself.
I look forward to seeing how these developments will improve service levels and customer satisfaction in the freight industry!