Copying orders from PDFs. Matching supplier price lists line by line to your own product range. Correcting product data in Excel. Your team usually knows exactly where the work gets stuck. The harder question is where to start automating without disrupting your entire operation.
Do not start with a broad AI strategy. Start with one recurring workflow, one owner and one number that needs to improve.
This article explains which business processes are suitable for an AI agent, what manual work costs today and how to move from a small, controlled start to a working solution.
Choose one workflow, not a company-wide programme
A broad AI roadmap can look useful, but it does not change the work that will be waiting in the inbox again tomorrow morning. The first step becomes concrete when you choose one workflow that occurs frequently.
Consider processing time per order, handling time per supplier price list or the percentage of complete product records. Record the current situation and decide which outcome matters. This allows you to assess afterwards whether the solution genuinely delivers value.
A narrow scope does more than reduce risk. It also makes clear who needs to decide, which data is required and where human control must remain.
Which business processes are suitable for an AI agent?
A workflow is a promising candidate when it meets four conditions:
- The work occurs frequently. Daily or weekly volume makes improvement worthwhile.
- The required information already exists. For example, in emails, PDFs, Excel files, portals or the ERP.
- Someone owns the process. This person understands the exceptions and can make decisions about how the work should be done.
- The pain is measurable. In minutes, errors, lead time, costs or lost margin.
For wholesalers and B2B organisations, common examples include:
- Order processing: reading orders from email, PDF, portals or Excel, checking them and preparing them for the ERP. See OrderPilot.
- Procurement matching: linking supplier and competitor price lists to your own product range. See QuotePilot.
- Product data: reading supplier files, flagging missing fields and making product information usable. See ProductDataPilot.
- Invoice checking: comparing invoices and credit notes with orders and receipts.
- Service work: preparing answers to recurring questions about orders, deliveries and products.
Does your process not appear in this list? Test it against the four conditions. Volume, available information, ownership and measurable pain matter more than the label.
Put a number on the current work first
Many organisations recognise the frustration but do not know the cost. Without a baseline, automation remains a discussion based on instinct.
For one workflow, record:
- how many items pass through it each week;
- how many minutes each item takes, including checks and corrections;
- how often something goes wrong and what recovery costs;
- how much time passes between receipt and confirmation;
- how much work depends on a small number of experienced employees.
For labour time, the first calculation is straightforward:
weekly volume × minutes per item ÷ 60 × total internal hourly cost × 52
This is not yet the complete business case. Errors, additional shipments, credit notes and customer enquiries need to be added. Dependence on a few specialists and the need to hire more people as the business grows also belong in the decision.
Want to apply this calculation to orders? Read What does manual order processing cost?.
Give routine work to the agent and exceptions to your people
Good automation treats normal processing and exceptions differently.
The AI agent reads, recognises, checks and prepares work within agreed boundaries. If information is incomplete, a price differs or a decision requires expertise, the work goes to an employee.
You determine in advance:
- what the agent may do independently;
- when work must be stopped;
- which exceptions go to which team member;
- which actions require human approval;
- how errors and failed processing are handled.
Human control is not a fallback. It is part of the design. Routine work goes to the agent; judgement stays with your people.
Your ERP and other systems keep doing what they do best
Automating business processes with AI usually does not mean migrating first. The agent connects to the information and systems already in place: mailboxes, files, portals, ERP, PIM or WMS.
Your ERP can continue to manage inventory, orders, invoicing and delivery. The agent improves the work before or between those systems. Only when poor data, fragile integrations or a blocking platform are the real cause does the technical foundation need attention first.
The right integration depends on the system. It may be an API, an existing connector, structured file exchange or custom development when no standard route is available.
Learn more about how rb2 uses AI agents for clearly defined workflows.
Live evidence: OrderPilot at INSPIRED Pet Nutrition
INSPIRED Pet Nutrition is a British pet food brand. A seven-person service team spent 15 to 30 minutes manually processing each order.
OrderPilot reads order emails and attachments, checks the customer, product, quantities and discrepancies, and prepares the order for the ERP. Exceptions remain with the team.
In this specific workflow, order processing became 9 times faster and processing costs per order fell by 60 to 80 per cent. A working solution, including the interface, AI engine and ERP integrations, was live within six weeks.
Read the full INSPIRED case.
How to start without a major programme
The route consists of separate decisions:
- Free 30-minute conversation. We assess whether the work has enough volume, repetition and ownership to investigate further.
- Paid Prove session. Together with the people who know the work, we examine the problem, exceptions, data, systems, ownership and the outcome that matters. The fee is fixed in advance.
- Evidence-based decision. The outcome is to build, improve the data, process or an integration first, or not proceed. A concrete build plan and separate proposal with a fixed build fee only follow after a positive build decision.
- Put the agent to work. After delivery, a fixed monthly price per agent covers management, monitoring and improvement.
You do not need to commit to a major AI programme upfront. You only need to identify which recurring work you want to improve first.
Where does work get stuck in your operation every week?
In 30 minutes, we can determine whether one workflow is a promising candidate for an AI agent. If it is not, we will tell you that too.