Quick Answer
AI in ERP now does more than summarize data. Microsoft Dynamics 365 AI can help process invoices and sales orders, reconcile accounts, communicate with suppliers, and surface exceptions so employees spend less time on repetitive administrative work. Across Microsoft Dynamics 365, AI is increasingly participating in workflows by reading documents and emails, preparing transactions, investigating discrepancies, and handing unusual cases to employees for review.
Key Takeaways
- Microsoft Dynamics 365 AI is moving from chat and prediction toward agents that can carry out multi-step business processes.
- Business Central agents can assist with vendor invoices and sales orders received by email.
- Dynamics 365 Finance can use AI to investigate reconciliation exceptions and recommend actions.
- Supply Chain Management can use AI to support supplier communication and purchase-order follow-up.
- Human review remains important for exceptions, approvals, and financially significant decisions.
- The strongest AI projects usually start with a narrow, measurable workflow problem.
AI Is Moving Into the Workflow
The first wave of generative AI made business software easier to interact with. Users could summarize information, draft an email, or ask questions in natural language. It was certainly useful, but the employee was still doing most of the underlying process.
Microsoft's newer AI agents, like those available in the Copilot suite, go further than their predecessors; Business Central's Sales Order Agent, for example, can monitor a mailbox for customer requests, identify the customer, check item availability, create a sales quote, and prepare a response. Instead of waiting for a user to ask a question, the system can handle part of a process and bring a person in when judgment or approval is needed.
Use Case 1: Processing Accounts Payable
Invoice entry is a natural target for automation because so much of the work is repetitive. A vendor sends a PDF invoice, someone identifies the vendor, enters the document, checks the lines, compares it with purchasing information, and routes anything unusual for review. Business Central's Payables Agent is designed to automate much of that intake. It can process PDF invoices received by email and prepare the corresponding payable work inside Business Central.
How Business Central AI Delivers Value
The goal of AI in an ERP is to reduce the time AP employees spend retyping information that already exists on a document. That gives the team more time to investigate mismatches, resolve vendor issues, and handle the exceptions where experience really matters. Business Central also provides ways for users to supervise agents and step in when they need input.
Use Case 2: Turning Customer Emails Into Sales Orders
Customer orders are often surprisingly unstructured.
For instance, an email might say, “Can you send 20 more of the blue units we bought last month?” A salesperson can interpret that quickly, but traditional ERP software expects structured fields.
The Sales Order Agent bridges some of that gap. According to Microsoft, it can monitor customer emails, identify the customer, check product availability, prepare a sales quote, and move the request toward an order. For organizations processing a high volume of routine email orders, that can remove a meaningful amount of copying, lookup work, and back-and-forth communication.
Use Case 3: Making Reconciliation More Continuous
Financial reconciliation has traditionally been a scheduled exercise. Teams compare balances, investigate differences, make corrections, then repeat the process all over again during the next close.
Dynamics 365 Finance, however, is moving toward more continuous exception management.
Microsoft's Account Reconciliation Agent can evaluate exceptions raised in the reconciliation workspace and recommend actions. At time of writing (September 2026), Microsoft identifies the agent as a production-ready preview.
The broader idea, however, is useful beyond simply helping with reconciliation: AI can help finance teams find the transactions that deserve attention instead of asking employees to manually inspect everything.
Use Case 4: Reducing Procurement Follow-Up
Procurement teams spend a lot of time asking simple questions, like:
- Has the supplier confirmed the purchase order?
- Is the delivery still on schedule?
- Did the vendor request a quantity or date change?
- Which PO does this email refer to?
Dynamics 365 Supply Chain Management's Procurement Agent can identify purchase orders that need follow-up and generate messages for vendors. It can also read vendor emails, classify what they are about, and match proposed changes to the relevant purchase order. Some supplier-communication features currently remain in production-ready preview at time of writing, but they show the direction clearly – we are moving towards a world where employees can let AI handle repetitive coordination around transactions, instead of merely being a tool to analyze them afterward.
Where Should You Start With AI in ERP?
Start with the boring work.
Look for a process where employees repeatedly read information, enter it somewhere else, compare records, chase routine responses, or separate normal transactions from exceptions.
Then establish a baseline. How many transactions happen each month? How long does the process take? Where do errors occur? Which steps truly need human judgment?
A narrow project with a measurable before-and-after is much easier to evaluate than an organization-wide directive to “use more AI.”
AI Still Needs Process Design
Before deploying an agent, make sure ownership, permissions, approval rules, escalation paths, and exception handling are clear. AI should operate inside those controls, particularly when financial or operational transactions are involved.
Building AI Into Your Dynamics 365 Environment
Microsoft Dynamics 365 AI is developing quickly, and businesses do not need to adopt every new feature at once.
IES helps organizations evaluate Dynamics 365, Business Central, Power Platform, integrations, and managed services around the way their teams realistically work on a day-to-day basis. That includes identifying where AI can remove repetitive effort, where conventional automation is a better fit, and where people should stay firmly in control.
Microsoft AI for ERP: FAQs
