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Adopting AI in your business: a roadmap for SMEs
Adopting AI means picking one process, making it measurable, and letting software take over the parts that cost your team time. APPIQ Solutions starts with a risk analysis, builds a prototype you can walk away from, and scales only once that prototype holds up in daily use. A person decides what goes live at every step.
What does AI adoption actually mean?
Adoption means taking a process your team does by hand today and letting software handle parts of it. The software reads, sorts, drafts, or pulls information together. Your team checks the result and approves it.
The cut decides. Take one process that runs often, is written down, and produces a result you can judge. Without that cut the project stays a demo in a meeting room.
What are the three stages of an AI rollout?
We work in three stages. Each one produces a result you can judge before the next one starts.
- Understand: we walk through your workflows and name the places where time disappears. You get a list of candidates and the risk attached to each.
- Automate: one process gets built, connected, and tested in daily work. You get a running prototype your team actually uses.
- Scale: once stage two holds, further processes join and share data, approvals, and audit trails.
Which processes should you start with?
Start with the work that repeats every week and that someone already proofreads. The benefit shows up early and a mistake costs little.
- Inbox and inbound requests: read incoming mail, classify it, route it to the right person, prepare a reply draft.
- Quotes: fill the template, carry over line items from earlier conversations, flag anything that deviates.
- Booking: check availability, propose a slot, confirm it, send the reminder.
- Reports: pull figures from several systems and prepare a draft.
- Knowledge search: answer staff questions from your own documents and cite the source.
What are the risks and how do you stay in control?
Three risks show up in almost every project: your data ends up in the wrong place, you get locked into one vendor, or the model invents an answer. All three are manageable once you name them before anyone writes code.
Against data leakage, what matters is where the data sits and who can see it: EU hosting, separated access rights, no handover of customer data for training. Against lock-in, what matters is an architecture where the language model stays swappable and your process knowledge stays yours.
Against invented answers, called hallucinations in the field, two things work: the AI answers only from your own documents and names the source, and a person approves before anything leaves the house. We call that gated autonomy, meaning the system acts on its own up to the point where a human signs off.
What does AI adoption cost?
Cost follows four things: how many systems get connected, how clean your data is, how much approval logic the process needs, and whether we extend existing software or build new.
The first conversation is free. The risk analysis gives you a solid estimate before you commit. The prototype comes at a fixed price, and you can stop if the result does not convince you.
How do you start without a large budget?
Pick one process, not five. Put a number next to it that you already know today: handling time per case, cases per week, error rate. Then you can judge whether the next step is worth it.
A thirty minute call is usually enough to tell whether your case holds. Viktor Hermann has worked as a solution architect for over 8 years and will tell you when AI is the wrong answer here.
Frequently asked questions
Do I need my own data for AI to work in my company?
For generic writing tasks a general language model is enough. As soon as your products, prices, or contracts are involved, the AI needs access to your documents. They stay in your systems, and the model reads them at runtime.
Does my data have to go to the US?
No. We design the solution so processing and storage can stay inside the EU. Which models qualify is part of the risk analysis, because that choice narrows your options.
How long does a pilot take?
A pilot covering one process is a matter of weeks, not quarters. In one documented case, four apps shipped in 90 days. We agree the exact frame before we start.
What happens when the AI gets something wrong?
Every step with outside effect has a person in between. The AI produces a draft, your team approves it. Each run is logged so you can trace where an answer came from.
Does my team need AI skills?
No. Your team keeps working in the tools it knows. The AI sits behind the process, not in front of it. An hour or two of onboarding usually covers it.
What is the APPIQ Cognitive Engine?
ACE is our own platform. It orchestrates specialised AI agents across the software lifecycle, keeps project knowledge in a knowledge graph, and checks results against accumulating technical debt. You decide what gets accepted.