How AI Is Transforming Dynamics 365 Business Central in 2026
Nearly every software pitch your team sat through this year probably mentioned AI. For a 60-person distributor or services firm running Business Central, the useful question is narrower: what's already in the product, what does it actually save, and what does our data need to look like before any of it works?
That's the question Brightmoor clients ask us most, so this article answers it specifically for AI in Dynamics 365 Business Central. We cover the Copilot features you can use now (marketing text, bank reconciliation help, sales line suggestions, analysis assist and chat), Microsoft's predictive extensions for late payments and forecasting, the data prerequisites that decide whether any of it helps, and where the product is heading. We'll stick to what's shipping and say clearly when we're describing direction rather than detail, because Microsoft's AI roadmap moves faster than any blog post.
What Does AI in Business Central Actually Look Like?
AI in Business Central comes in two forms. Copilot features use generative AI, through Microsoft's Azure OpenAI service, to draft text, interpret plain-language requests and propose matches inside the pages your team already uses. Predictive extensions are older machine-learning add-ons from Microsoft that score or forecast based on your own history. Neither replaces a person: Copilot produces suggestions that someone reviews before anything is saved or posted.
Administrators control which Copilot features are switched on from the Copilot capabilities page (search for "Copilot" with Tell Me). Copilot works within each user's existing permissions, and Microsoft states that your business data isn't used to train the underlying models. Availability varies by country and language, so check current Microsoft documentation for your environment. For a broader view of what AI means for smaller ERP users, see what AI-powered ERP is and how it helps small businesses.
Which Copilot Features Are Most Useful Today?
Marketing text for items
On the item card, Copilot drafts product descriptions from the item's name, category and attributes, with options for tone, length and emphasis. If you sell through the Shopify Connector, that text can flow to your storefront. It's the lowest-risk feature to start with, and output quality depends almost entirely on how good your item attributes are.
Bank reconciliation assist
In bank account reconciliation, Copilot proposes matches between imported statement lines and open ledger entries, including awkward ones that rule-based matching misses. It then suggests G/L accounts for leftover lines, such as bank fees, based on how you've posted similar transactions before. For a controller reconciling several accounts each month, this is often the most tangible time saver.
Sales line suggestions
On sales quotes and orders, users can describe what they need in plain language, such as "the same items as this customer's last order," and Copilot proposes lines to review. It can also work from an attached file, which helps when customers email order lists. Inside sales teams handling repeat B2B orders benefit most.
Analysis assist
Analysis mode turns list pages into pivot-style analysis. With analysis assist, a user types something like "sales by customer by month, top ten customers only" and Copilot builds the grouping and filters. It's a quick win for managers who would otherwise export to Excel.
Chat with Copilot
The chat pane answers how-do-I questions, finds records and helps people navigate, which matters most for occasional users and new hires. Treat its answers like a capable colleague's: usually helpful, still worth checking.
What About Late-Payment Prediction and Forecasting?
Two Microsoft extensions predate Copilot and remain useful.
The Late Payment Prediction extension scores open sales invoices on how likely they are to be paid late, with a confidence level, so collections can focus on the right customers before the due date. It learns from your history of posted invoices and payments, so a company with a year or two of clean data gets more from it than one that migrated only opening balances.
The Sales and Inventory Forecast extension applies time-series forecasting to your sales history to project demand per item, highlight likely stockouts and help create replenishment requests. It works best for items with steady history; new products and promotion-driven spikes still need human judgment. Setup requirements have changed over the years, so check Microsoft's current guidance before you rely on it.
| Capability | What it helps with | Data it relies on | Effort to adopt |
|---|---|---|---|
| Marketing text | Product descriptions for web and catalogs | Item categories and attributes | Low |
| Bank reconciliation assist | Matching statement lines, coding leftovers | Statement imports, posting history | Low to medium |
| Sales line suggestions | Faster quote and order entry | Sales history, clean item master | Low |
| Analysis assist | Ad-hoc analysis without exporting | Well-structured list data | Low |
| Late Payment Prediction | Prioritizing collections | Invoice and payment history | Medium |
| Sales and Inventory Forecast | Demand and stockout visibility | Steady item-level sales history | Medium |
What Data Do You Need Before AI Helps?
Every feature above is only as good as the data underneath. Before switching anything on, we review four areas with clients:
- Item master. Consistent descriptions, categories, attributes and units of measure. Copilot can't write useful marketing text for an item called "WIDGET-BLK-2" with no attributes.
- Customer and payment history. Payments applied to the right invoices, sensible payment terms, and few manual write-offs disguising the real pattern. Prediction learns from whatever you feed it.
- Bank data. A reliable statement import, whether through a bank feed or file import, and consistent G/L coding for recurring items like fees.
- Permissions. Copilot respects user permissions, so sloppy permission sets show up in AI answers too. Tidy them before rolling chat out widely.
If you migrated only open balances, expect predictive features to become useful gradually as history builds.
Where Is Business Central AI Heading?
The direction of travel is clear: from suggestions toward agents, meaning AI that carries out multi-step tasks while a person approves the result. Microsoft has previewed a Sales Order Agent for Business Central that reads customer email requests, checks availability, prepares quotes and drafts replies for a salesperson to review, and has signaled similar agents for other areas such as payables. Availability depends on region, language and release, and agent capabilities may be licensed differently from built-in Copilot features, often on a consumption basis. Check current terms before planning around them.
Two other developments matter for smaller companies. Copilot Studio lets you build your own agents that work with Business Central data, such as an internal assistant that answers order-status questions in Teams. And partners and ISVs can build Copilot capabilities directly into AL extensions, so expect more AppSource apps with AI built in. For the wider Dynamics 365 picture, this overview of Copilot use cases across Dynamics 365 is a good companion read.
How Should a Small or Mid-Size Business Get Started?
Our recommended sequence is deliberately modest:
- Review the Copilot capabilities page with your admin and decide which features to enable, and for whom.
- Pick one finance feature and one sales or operations feature, for example bank reconciliation assist and sales line suggestions.
- Measure a baseline before you start, such as minutes per reconciliation or per order entered, so you can tell whether it helped.
- Train people to review, not rubber-stamp. Every suggestion still needs a human check.
- Revisit at each release wave, because new capabilities arrive twice a year.
AI also pays off most when the process underneath already runs smoothly. If approvals and recurring postings are still manual, ERP workflow automation is often the better first investment.
Key takeaway: The Business Central AI that pays off today is practical and narrow: faster reconciliations, quicker order entry, better product data and earlier warnings on late payers. Clean data decides how much value you get.
Conclusion
AI in Business Central isn't a separate project or a moonshot. It's a set of Copilot features and predictive extensions that sit inside everyday work, plus a steady move toward agents that handle routine tasks under human review. For most growing companies, the winning approach is to fix the data foundations, switch on a couple of well-chosen features, measure the time saved and expand from there, tracking each release wave rather than chasing every announcement.
If you'd like a practical read on which Business Central AI features fit your team, Brightmoor Dynamics is happy to talk it through.
Frequently Asked Questions
Is Copilot included with Business Central?
Microsoft has included Business Central's built-in Copilot features with Business Central licenses rather than charging for them separately. Agent capabilities and Copilot Studio usage may be billed differently. Licensing changes over time, so confirm current terms with Microsoft or your partner.
Does Copilot in Business Central post transactions automatically?
No. The built-in Copilot features suggest text, matches or document lines, and a user reviews and accepts them before anything is saved or posted. The agents Microsoft has previewed are also designed around human review of their output.
Is our data safe when we use Copilot?
Copilot works within each user's Business Central permissions, and Microsoft states that customer data isn't used to train the underlying AI models. Administrators decide which features are enabled. Review Microsoft's current documentation alongside your own data policies before enabling features broadly.
Does AI work in Business Central on-premises?
Copilot features are built for Business Central online, and Microsoft's newest AI capabilities arrive in the cloud product first. If AI matters to your roadmap, that's one more factor in the online versus on-premises decision.
