How much AI value is trapped in your ServiceNow environment?

Answer six questions on the left. Your dashboard updates instantly on the right, with support capacity, productivity value, ROI multiple, and payback.

Your ServiceNow workflow

Six inputs drive the whole dashboard.

38%
62%

Dashboard updates live as you type

Your Estimated AI Readiness Impact

Choose a scenario
62%Target deflection

$288,400

Total Annual Savings

1.4×

ROI Multiple

≈ 2.7 FTE

Total FTE Capacity Freed

8.3 mo

Payback Period

Ready to put this in your business case?

Send the full ROI estimate report to your inbox, or explore the roadmap to see what needs to happen next to turn AI readiness into measurable value.

Explore the AI Readiness Roadmap

FAQs

How do I fine-tune my assumptions?

There's no separate assumptions form to fill out. Fine-tuning happens in real time: re-enter any of the six inputs on the left, ticket volume, self-service and target deflection, resolution time, knowledge management team size, or article volume, and every number on the dashboard recalculates instantly.

If you want to see a range rather than a single number, use the Conservative, Target, or Aggressive toggle above the dashboard. It applies a more cautious or more optimistic realization rate to your inputs without you having to touch every field by hand.

How did you calculate this?

Your estimate compares your current self-service resolution rate against your target deflection rate to estimate additional tickets deflected, then converts that into agent time returned to your organization. Financial value combines two sources: productivity value from that freed agent time, and productivity value from knowledge management efficiency gains based on your article volume. Default, industry-typical cost assumptions apply throughout, and the Conservative, Target, or Aggressive toggle applies a savings realization factor to both sources, reflecting how much of that value is likely to be captured in practice.

This estimate is directional and based on the inputs and assumptions provided. Actual outcomes may vary based on platform maturity, knowledge quality, workflow design, adoption, governance, and implementation scope.