The biggest opportunity, for the biggest sectors in the Netherlands

The sector under pressure

At almost every company we speak to, we see the same pattern. Finding good people remains a structural challenge. Margins are under pressure and costs are hard to pass on to the customer. And international competitors are making big strides in efficiency.

From that position, automating with AI is not only seizing an opportunity, it is a necessity. You feel it not just in the numbers, but on the work floor: processes that can and must be better. Orders entered by hand. Supplier lists that come in by email every month and have to be retyped. Excel sheets alongside the ERP system, because adapting the system takes time and expertise that is not there.

These are the problems we run into at almost every company. And AI will be an important part of the solution: offloading part of every colleague's work so you get more done with the same team. With your data and the right instructions, AI can take over a lot of repetitive manual work, leaving your people more time for what matters.

Three concrete examples

1. Retyping incoming orders and lists

Orders come in as email, as PDF, sometimes as a loose Excel file. Supplier lists come back every month, and every supplier uses its own format. Someone has to transfer that into the ERP. That costs hours a week, and it is exactly the kind of work where mistakes creep in, because it is too dull to stay sharp on.

AI can read those documents, prepare the data in the right format, and indicate how confident it is. What is clear goes through. What deviates lands on a pile for a human. Your colleague shifts from entering to checking.

2. The questions that come back every day

"Where is my order?" "Do you have this in stock?" "What did we charge this customer last year?" Each one answerable, but someone has to click through three screens, or interrupt a colleague who was in the middle of something. The information is there, it is just spread across ERP, warehouse, mailboxes and a few sheets. AI can answer that question in plain language by looking in all those sources at once.

3. Spotting patterns in customer behaviour for personalisation

Every customer leaves a trail: what they buy, how often, in which style, in which price range. That information sits somewhere in the system, but nobody looks at it structurally. A salesperson remembers a few regular customers by heart, the rest of the customer base goes unused. Chances for a repeat purchase or a targeted offer are lost because nobody has time to go through all the purchase history.

AI reads that purchase history and recognizes the pattern behind it: this customer buys the same style every season, that customer always responds to a certain price segment. As soon as something comes in that fits, a signal follows. Not a general mailing to the whole customer list, but a targeted offer to whoever actually has use for it. Your salesperson does not have to guess who to approach, the system has already worked that out.

In all three cases AI does the groundwork and the judgement stays with your people. Not a replacement, but time given back to colleagues who are now stuck in retyping, looking things up, or guessing. These are only a few concrete examples of what is possible for companies in the sector. Every company has its own bottlenecks, and the best application depends on where most of your time is lost.