Artificial intelligence has become a much meaningful part of Microsoft Dynamics 365 Business Central.
But for organisations already using Business Central, or considering implementing it, the important question is no longer whether AI will affect ERP. It is which AI capabilities in Business Central are most worth adopting?
Some AI features can already remove administrative work from finance, sales and operations teams. Others can make information held within Business Central considerably easier to interrogate. Then there is the emerging generation of AI agents that can take responsibility for parts of a business process rather than simply assisting the person completing it.
The opportunity is significant. However, companies should approach AI in Business Central in terms of practical use cases rather than simply trying to “adopt AI”.
The starting point should be identifying high-volume, repetitive or information-heavy processes where automation or better access to data could deliver a measurable improvement.
1. Start With Copilot For Everyday Business Central Tasks
For many organisations, Microsoft Copilot is the most logical entry point.
Copilot acts as an assistant within Business Central rather than operating independently. It can help users analyse information, create content, find records and work with Business Central data through more natural interactions. Crucially, the employee remains in control of the action being taken.
That makes it well suited to relatively low-risk productivity improvements.
Rather than employees navigating menus or extracting information into spreadsheets before they can investigate it, AI can make interacting with ERP data significantly more intuitive. The potential value is therefore not simply that individual tasks become slightly faster. It can reduce the effort required to get useful information from Business Central in the first place.
For companies beginning their AI journey, this is an attractive place to start because it allows AI to support existing processes without immediately handing responsibility for those processes to an autonomous system.
2. Use AI To Improve Forecasting And Decision-Making
The next opportunity is using AI to make better use of the operational and financial data already held within Business Central.
Microsoft's Sales and Inventory Forecast functionality, for example, can use historical information to predict future sales and inventory requirements. This can help organisations optimise stock levels and reduce the risk of shortages or unnecessary stockholding.
This can be particularly valuable in industries where demand, stockholding and working capital are closely connected.
A distributor could use predictive insight to identify potential inventory shortages earlier. A manufacturer could get a clearer view of changing demand. Finance teams can similarly use AI-supported analysis to identify trends and potential problems sooner.
Cash-flow forecasting, identifying inventory risks and analysing performance trends all demonstrate how AI can help organisations move from retrospective reporting towards more proactive decision-making.
This is potentially one of the strongest applications of AI in ERP. Most businesses already have substantial amounts of operational data. The challenge is converting it into information people can act on quickly.
AI can help shorten that distance between data and decision.
3. Prioritise AI Where Manual Administration Is Highest
For many organisations, the quickest return will not come from sophisticated predictive models at all. It will come from automating repetitive administrative work.
Finance is an obvious example. Invoice processing typically involves reading supplier documents, identifying relevant information, matching it against existing records and entering data into the ERP platform. Multiply that process across hundreds or thousands of invoices and the administrative overhead becomes considerable.
Business Central's emerging Payables Agent is designed to tackle exactly this type of process. It can capture information from vendor invoices and use Business Central data and rules to help create the relevant records, reducing reliance on manual data entry.
This illustrates an important principle for AI adoption: Start with repetitive work that follows recognisable rules.
Invoice processing, expenses, data entry, reconciliation and similar workflows are generally better early candidates than processes heavily dependent on subjective judgement.
The objective should not simply be “using AI”. It should be establishing whether AI can remove a meaningful amount of low-value work while maintaining appropriate oversight and control.
4. Explore The Sales Order Agent For High-Volume Order Processing
Sales administration is another area where AI agents could have a noticeable impact.
The Sales Order Agent can help handle incoming customer enquiries, interpret natural-language requests, prepare quotes and create sales orders. It can also support multi-step interactions where further information is required.
The potential is particularly interesting for wholesalers, distributors and manufacturers processing significant numbers of repeat or relatively standard orders.
Instead of someone manually reading an email, finding the customer account, identifying the requested products and creating the corresponding order, an agent can increasingly handle parts of that workflow.
The important point is that this represents a step beyond traditional AI assistance.
Copilot helps someone do the work. An agent can increasingly do some of the work on their behalf.
That distinction matters when organisations consider governance. The more autonomy an AI system has, the more important defined permissions, validation rules, exception handling and human approval become.
5. Consider AI For Expense Management
Expense processing offers another relatively contained opportunity.
Business Central's emerging Expense Agent is designed to capture receipts, extract information, create expense lines, match receipts with transactions and prepare expense reports for review.
Again, this is attractive because the objective is clear and measurable. Companies can assess how long employees currently spend preparing and approving expenses, how frequently information is entered incorrectly and how much finance resource is devoted to correcting or processing submissions.
That gives organisations a sensible benchmark against which AI adoption can be judged. If an AI capability cannot identify a tangible operational problem it improves, its business case should probably be questioned.
6. Look Beyond Standard Functionality With Custom AI Agents
The biggest longer-term opportunity may come from processes that are specific to the organisation.
Standard Business Central AI capabilities will address common use cases. But businesses inevitably have workflows that reflect their industry, operating model or customers.
Custom AI agents can extend Business Central data into experiences delivered through Microsoft Teams, websites and customer or employee portals. These agents can also connect Business Central information with automated workflows using Microsoft Power Automate.
This opens considerably broader possibilities.
A service organisation might create an agent that retrieves information about contracts, customers and outstanding work. A distributor could automate elements of order enquiries. A finance team might create an internal assistant capable of retrieving relevant Business Central information without employees having to manually navigate multiple records.
But custom development should generally come after organisations have understood what Microsoft's standard capabilities can achieve.
There is little value in creating a bespoke AI solution for a problem that Business Central already solves.
AI Adoption Should Follow The Process, Not The Hype
The strongest approach to AI in Business Central is therefore unlikely to begin with technology.
It should begin with processes.
Look for areas characterised by:
- High levels of repetitive manual work
- Large volumes of transactions or documents
- Frequent data entry or rekeying
- Time spent searching for information
- Predictable processes with clear business rules
- Decisions that could benefit from faster access to operational data
Then assess which combination of Business Central, Copilot, AI agents and Microsoft Power Platform technologies could improve them.
AI should also be introduced with appropriate controls. Agents capable of undertaking transactions need clearly defined permissions, exception handling and approval processes. Businesses should remain particularly careful where actions can affect payments, customer commitments, financial records or other consequential processes.
The goal is not maximum automation. It is appropriate automation with measurable business value.
What Should Companies Adopt First?
For most organisations, a sensible Business Central AI roadmap would be progressive.
Start with Copilot to improve productivity, information discovery and analysis while employees remain firmly in control.
Then target repetitive processes such as invoice, expense and sales-order administration where the potential saving can be measured relatively easily.
Use predictive capabilities where Business Central contains enough reliable historical information to improve forecasting around sales, inventory, cash flow or other operational decisions.
Introduce AI agents selectively where business rules, permissions and human oversight can be clearly defined.
Finally, consider custom agents and automation where the potential business value justifies creating something specific to your organisation.
That approach turns AI from an abstract transformation programme into a series of targeted operational improvements.
For organisations using Business Central, that may ultimately be the most important change AI brings. ERP has traditionally depended on people going into the system to enter, find and interpret information. Increasingly, AI can help bring that information to the user, interpret it and, where appropriate, act upon it.
The question for businesses is therefore becoming less “What can AI do in Business Central?” and more “Which processes no longer need to work the way they do today?”
Ready To Explore AI In Business Central?
Akita can help organisations assess where AI, Copilot and automation can add genuine value within Microsoft Dynamics 365 Business Central, from improving everyday productivity to automating finance and operational processes.
Whether you're already using Business Central or planning a wider ERP transformation, the right starting point is identifying where AI can deliver a measurable improvement rather than adopting it for its own sake. Get in touch with our experts today.
