Agentic AI reaches production when process owners decide
Agentic AI projects reach production when the right people decide what "scales."(Hint: It's not steering committees, vendors or IT)
It's the people who run the process.
Your AI vendor has never sat through your month-end close.Your IT team does not spend Tuesday mornings fixing delivery dates in Excel.Your data team does not have to call a customer when a wrong shipment goes out.
The people who live in the process know exactly where the friction sits.
Planners track Excel rituals that burn three days every month.Claims handlers repeat the same checks 100 times a week.Finance reconciles the same invoice mismatches every week.
Real value shows up when these people co-design the systemโnot as "users" at the end, but as owners at the start.
Here is how to lead this in your function. (๐พ Save for later)
๐ญ. ๐ฆ๐๐ฎ๐ฟ๐ ๐๐ถ๐๐ต ๐ผ๐ป๐ฒ ๐ฐ๐ผ๐ฟ๐ฒ ๐๐ผ๐ฟ๐ธ๐ณ๐น๐ผ๐Not "an AI platform." One process you actually run, with the people who run it.
2. Multi-role process mappingOps, IT, and process owners walk the real flow together. Map workarounds, side spreadsheets, manual decisions. Quantify pain in days, errors, and riskโnot "it feels slow."
๐ฏ. ๐๐ฒ๐ ๐ฑ๐ผ๐บ๐ฎ๐ถ๐ป ๐ฒ๐ ๐ฝ๐ฒ๐ฟ๐๐ ๐ฑ๐ฒ๐ณ๐ถ๐ป๐ฒ ๐๐ต๐ฒ ๐ฟ๐๐น๐ฒ๐
- Which steps stay human
- Which steps move to code
- Where AI suggests, and where it must never decide
Example: A finance lead identifies the 11 reasons invoices get stuck, defines when to auto-approve vs. flag for review, and owns the requirements through build. IT collaborates on deployment with a specialized AI consulting firm, like us. First automated invoice in Week 4.
๐ฐ. ๐๐๐ถ๐น๐ฑ ๐ผ๐ป ๐๐ผ๐๐ฒ๐ฟ๐ฒ๐ถ๐ด๐ป ๐ถ๐ป๐ณ๐ฟ๐ฎ๐๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒOpen-source models trained on your invoices, tickets, and delivery notes. Outputs that drop directly into SAP or your legacy stack. Logs you can defend to auditors.
๐ฑ. ๐ฆ๐ต๐ผ๐ ๐ฐ๐ผ๐ป๐๐ถ๐ป๐๐ผ๐๐ ๐บ๐ฒ๐๐ฟ๐ถ๐ฐ๐
- Hours saved per month
- Error rates before/after
- Escalations where humans stepped in
Teams adjust thresholds themselves - not waiting for a vendor.
I know most boards expect IT to "do something with AI," and IT is already buried in backlogs.
That is exactly why process owners should lead the first production system.
If you lead a core function and see repetitive manual work that burns days every month, that is your first AI project - if its requires only a simple system.
Your answer to this question will determine how well your AI systems will perform:
Will you design the AI systems with the people who run the process , or will you adopt someone else's guess?