Agentic AI, explained
What is agentic AI for accounts payable?
Agentic AI goes beyond capture-and-suggest automation — it reasons, decides, and acts. Here’s what that means for D365 Finance teams in 2026.
What makes AI “agentic” (vs. just “AI-powered”)
A lot of AP software claims “AI” today — usually meaning OCR plus machine-learning suggestions that a human still has to approve. Agentic AI is a different tier: an agent doesn’t just suggest a GL code, it decides, executes, and can chain that decision into the next step — matching, routing, flagging — while logging why, and only stopping to ask a human when its own confidence says it should.
Why 2026 is the inflection point for AP
Ardent Partners’ 2026 research frames this year as the end of AI “testing” in AP and the start of the AI-native finance office. That’s consistent with what’s happening on the ground: by Ardent’s count, 75% of AP departments already use some form of AI — but the gap between that and genuinely agentic automation is where 2026’s real change is happening.
What this looks like in practice on a Dynamics 365 Finance invoice
An invoice arrives. An agent extracts the data, checks it against PO and vendor history in Microsoft Dynamics 365 Finance, decides whether it’s a clean match or an exception, and either codes and routes it automatically or escalates with a specific reason attached — not just “needs review.”
Common questions
- Is agentic AI just RPA with a new name?
- No — RPA follows fixed rules and fails outside them. Agentic AI reasons across context and can handle situations a rule wasn’t written for.
- Do we need to replace our existing AP automation to go agentic?
- Not necessarily — agentic AI typically sits alongside existing invoice processing, handling the judgment calls that rules-based systems escalate or mishandle.
- Is agentic AI proven yet, or still experimental?
- Ardent Partners’ 2026 research treats this as past the testing phase for AP specifically — it’s being adopted as a practical operating model, not a pilot.