AI for business: what works and where to start?

What can AI really do for business in 2026?

Over the last two years AI for business has moved from experimental to usable. A few categories now work reliably enough to put into production:

• Reading and summarising documents. Categorising emails, reading contracts, processing incoming invoices. Less time spent on inbox and document admin.
• Generating text in a fixed structure. Quotes, standard letters, product descriptions, job ads. You supply the frame, AI fills it in consistently.
• Image and handwriting recognition. Receipts, timesheets, photos of products or workplaces become readable data.
• Conversations into notes. Phone calls, video calls, and meetings get transcribed automatically with summary and action items.
• First-line customer questions. A chatbot answering based on your documentation catches 60 to 80 percent of routine questions.
• Predictive analysis. Which customers might churn, which prospects are promising, when does a machine need maintenance.

Where AI isn't ready yet

Fair is fair. There are use cases where AI in 2026 shouldn't be deployed without human oversight:

• Autonomous financial or legal decisions
• Complex medical assessments
• Creative work where brand consistency and originality are both essential
• Situations where your business is liable for mistakes an AI makes

In all these cases AI can support, but not replace. Always put a human in the loop if the outcome has serious consequences.

Three questions to answer first

Before you start an AI project, answer these three. They decide whether your project will succeed.

1. What's the concrete problem?

"Doing something with AI" isn't a problem. "Our timesheets come in Friday evening and need to be in admin by Monday" is. Start at a pain point where measurable time or money is at stake.

2. Is the process stable?

AI works well on processes that follow recognisable patterns. Does your process change every quarter? Then stabilise first, automate after. We cover this in our article on business automation.

3. What's your fallback?

AI makes mistakes. Build in up front what happens when the system isn't sure. Does it send the task to a staff member? Does it ask a clarifying question? Does it refuse to answer and escalate? An automation without a fallback is an accident waiting to happen.

What it costs

For businesses AI projects vary widely in cost. A few rough numbers:

• Small workflow with AI component: €1,500 to €5,000 one-off. For example: categorise and route incoming requests.
• AI-generated quotes or reports: €5,000 to €10,000 one-off. With input form, calculation rules, integrations.
• Internal knowledge chatbot on your own documentation: €7,500 to €15,000 one-off. Including indexing, chat interface, integration.
• Predictive model on your own data: €10,000 and up. Preparing the data is often the biggest part of the budget.

Plus AI usage (tokens) costs €20 to €300 a month, depending on volume. For more detail: see our article on automation costs.

Here's how to start

1. Make a list of recurring tasks. Anything that happens more than once a week and costs time goes on the list.
2. Sort them by pain. Which take the most time? Where do things go wrong most often? Which frustrate your team?
3. Pick one to start. One. Not three at the same time. Not reorganising your whole business.
4. Build small and working. Four weeks of development, then your team uses it. If it works, move on to the next.

Or let us do these steps. Take the inspiration quiz and get a personalised top three in two minutes.