There are two AI conversations in finance. One is about dashboards that summarise what already happened. The other is about agents that do the work — that read the receipt, apply the policy, route the approval, and post to the ERP without a human touching each step. Only the second one gives you hours back.
The useful test for any “AI feature” is simple: does it remove a handoff, or just speed up a click? Speeding up a click is nice. Removing a handoff — a person who otherwise had to open, read, decide, and pass along — is where the time actually lives.
An expense claim passes through five stations. Here is which ones an agent can own today, and which stay human.
The expense pipeline — who owns each step now. Four of five stations are touchless. The human moment is deliberately preserved where judgement and accountability belong: approving the exceptions. Illustrative of an agentic configuration.
Where the hours come from
Not from the approval itself — a manager clicking “approve” was never the bottleneck. The hours come from everything before the click: the chasing, the re-keying, the “can you attach the bill,” the manual policy check, the copy-paste into the ERP.
- 80% — Claims that clear with zero manual touches (straight-through)
- 4 min → 20s — To capture, code and file one claim (per claim)
- 3–5 d → same-day — From submission to ERP posting (cycle time)
Human touches per claim — manual vs agentic. Multiply the removed touches by your monthly claim volume — that product is your recovered finance capacity. Illustrative.
Automation is not autonomy — draw the line on purpose
Let the agent decide the deterministic things. Keep a human on the judgement calls. The trick is deciding which is which, in advance.
Let the agent decide — Rules with a right answer
Reading a receipt, matching it to a card feed, catching a duplicate, checking an amount against a policy limit, computing GST, coding to the right cost centre, posting a balanced entry.
In MyVyay OCR, policy engine, ERP posting run unattended
Keep a human — Calls with a judgement
Approving spend that’s over threshold, out of policy, or novel. The agent surfaces the exception with everything already checked; the manager decides in seconds, on the record.
In MyVyay Role-based auto-approval + exception routing
The goal isn’t an AI that approves everything. It’s an AI that makes every approval a two-second, fully-informed decision — and handles the 80% that never needed a decision at all.
Agentic AI earns its place when it removes work, not when it adds a chatbot. In expense operations the removable work is concrete: capture, extraction, policy checks, and posting. Automate those, keep humans on the exceptions, and the hours are real — not a slide.
See it on your own numbers: book a 20-minute demo or start free and run this playbook against your real spend data.