Artificial intelligence is becoming a bigger part of ERP systems, offering businesses new ways to analyze information, automate routine tasks, and make better decisions. For small and midsize businesses (SMBs), these capabilities can be especially valuable. They can save time, improve efficiency, and give employees access to information that might otherwise take hours to find.
But there’s an important question businesses need to ask before relying on AI: How accurate is accurate enough?
An AI tool that predicts customer demand with 92% accuracy may still be useful, even when it occasionally misses the mark. A search assistant that sometimes pulls up the wrong document is probably still faster than searching through hundreds of files manually.
However, the stakes change when AI starts handling financial transactions, account reconciliations, or other critical business processes. In those situations, an occasional mistake can have consequences that extend well beyond the original error.
For businesses considering AI-powered ERP, understanding where those mistakes might happen is just as important as understanding what the technology can do.
Not All AI Mistakes Carry the Same Risk
The impact of an AI error depends largely on what the system is doing when it makes a mistake.
If AI produces an inaccurate summary, answers a general business question incorrectly, or creates a report with misleading information, someone will likely notice. The user can check the original data, correct the problem, and move on. It’s inconvenient, but the damage is usually limited.
Now consider AI working inside a financial process.
Suppose an AI-powered tool misreads a vendor statement and records an incorrect balance. That error may become part of the financial close, affect financial reports, and influence decisions based on those reports. The longer it goes unnoticed, the more difficult and expensive it can become to correct.
The problem isn’t simply that AI made a mistake. It’s that the mistake entered a business process where other activities depend on accurate information.
This is why businesses need to look beyond general accuracy claims. A system that performs well when answering questions may not be ready to handle financial transactions without additional safeguards.
Why Smaller Businesses Need to Pay Attention
Larger companies often have several layers of oversight designed to catch errors before they become bigger problems. Controllers review financial entries, internal auditors test procedures, and operations teams check information before it moves through the organization.
Many SMBs don’t have that luxury.
A single controller may be responsible for financial reporting, account reconciliations, and overseeing the entire monthly close. There may not be another person available to review every transaction or question every AI-generated result.
That doesn’t mean smaller businesses should avoid AI. It simply means they need to be more thoughtful about where they use it and how much responsibility they give it.
An occasional error in a general business report may be manageable. An incorrect financial entry that goes unnoticed until an audit or customer dispute is an entirely different matter.
AI can be a valuable resource for businesses of every size, but its capabilities need to match the importance of the work it’s being asked to perform.
Questions to Ask Before Choosing an AI-Powered ERP
Not all ERP vendors approach AI in the same way. When evaluating a solution, businesses should look beyond impressive demonstrations and broad promises about accuracy.
Here are several questions worth asking:
What happens when the AI gets something wrong?
A vendor should be able to explain how the system handles incorrect results, identifies problems, and allows users to correct them. If the answer is vague, that’s a reason to ask more questions.
Can the system handle your actual business data?
A polished demonstration using clean, carefully prepared information doesn’t necessarily reflect how AI will perform in your business. Real-world data often includes inconsistent naming conventions, older records, missing information, and customized fields.
Ask the vendor to demonstrate how the system handles those situations. You want to see how it performs under realistic conditions, not just when everything goes according to plan.
Can users see where the answers come from?
Transparency matters. If an AI tool produces an answer, users should have a way to trace it back to the original information. Without that visibility, checking the accuracy of a result becomes much more difficult.
Are financial tasks treated differently from general searches?
This is particularly important. Looking up last quarter’s top customers is not the same as reconciling vendor statements or determining revenue recognition timing.
Financial processes require stronger controls and more careful oversight. A vendor should be able to explain how its AI capabilities account for those differences.
Making AI Work for Your Business
The goal isn’t to eliminate every possibility of an AI error. That’s unrealistic. Any technology that makes predictions or interprets information will occasionally get something wrong. Human reviewers can make mistakes, too.
Instead, businesses need to understand which processes can tolerate an occasional error and which require a much higher level of accuracy.
Start by looking at where AI is being used, or where you plan to introduce it. Consider the consequences if the information is incorrect. Could an employee easily catch and correct the problem? Or could it affect financial records, customer relationships, or important business decisions before anyone notices?
Solutions such as Acumatica are part of a growing shift toward bringing AI capabilities into everyday ERP operations. But choosing an AI-enabled ERP system should involve more than looking at the features and automation it offers. Businesses also need to understand how those capabilities fit into their existing processes and controls.
Ultimately, AI should make running a business easier, not introduce new risks that go unnoticed. The best approach is to use it where it can deliver real value while maintaining the appropriate level of human oversight.
AI doesn’t have to be perfect to be useful. But businesses do need to know when an occasional mistake is acceptable and when it isn’t. To learn more about Acumatica’s flexible, cloud-based ERP solution, contact us or schedule your free consultation today.