AI feels like the new ISO certification for many companies. Everyone is talking about it. Customers ask about it. Employees are experimenting with it. Suppliers promise golden opportunities. And meanwhile, the entrepreneur wonders: do we really need to do something with this now, or will this also blow over?

The comparison with ISO is understandable. ISO also started as something external for many companies. A customer asked for it. A tender made it mandatory. A supplier had to show that processes were in order. What started as a certificate eventually forced companies to look more carefully at their processes, responsibilities and assurance.

Something similar is happening with AI. Only faster. And deeper.

Why the ISO comparison works

The comparison with ISO works because many organisations still approach AI as a necessary requirement. Something you need to create policy for. Something your employees need to know something about. Something you do not want to fall behind on.

That is recognisable. Because ISO was never just about the certificate. The real impact was in the questions underneath:

• Which processes do we actually have?
• Who is responsible for what?
• How do we safeguard quality?
• Where are the risks?
• How do we make sure it does not remain dependent on one person?

AI raises similar questions, but now about knowledge, information, productivity and decision-making.

But AI is fundamentally different

ISO was mainly about documenting, standardising and proving. AI is about accelerating, combining and changing. It does not only affect the quality of processes, but also the way people think and work.

An employee who uses AI well can prepare quotations faster, analyse customer questions, conduct market research, summarise meetings, develop scenarios or make internal knowledge more accessible.

But an employee who uses AI incorrectly can also share confidential information, adopt wrong assumptions, draw incorrect conclusions or become dependent on answers that have not been critically checked.

There is also an overload of AI offerings

Many entrepreneurs now feel resistance when they hear the word AI. Not because the topic is unimportant, but because the offer comes from everywhere. Tools, training courses, gurus, prompts, webinars and promises are all competing for attention.

That creates noise. One person says AI will take over everything. Another says you will be behind tomorrow if you do not start today. And someone else is mainly selling a trick.

For SMEs, family businesses, manufacturing companies, logistics organisations and technical service providers, the question is much more practical:

• What does it actually deliver for us?
• Which risks do we need to control?
• Which people need to learn how to work with it?
• Where is the direct time gain?
• Where does it affect customer contact, planning, knowledge or operations?

That is exactly why AI should not be approached as hype, but as a business capability.

The Gartner Hype Cycle as a useful thinking framework

The Gartner Hype Cycle clearly shows how new technology is often received. First there is enthusiasm. Then exaggeration. Then disappointment. Only after that comes the phase in which organisations calmly discover where technology truly adds value.

AI is exactly in that transition for many companies. The hype is visible. Expectations are high. But the real value only emerges when AI is connected to concrete work processes, clear responsibilities and practical leadership.

Waiting until everything has fully crystallised may sound safe, but it is not always safe. Those who wait too long miss the learning curve. Those who jump in blindly create chaos. The skill lies in starting in a controlled way.

Why it is wise to start now

For many SMEs, this is the right moment to start with AI. Not because everything is already perfect. Precisely not. But because you still have room now to learn, experiment and create policy before AI enters the organisation everywhere by itself.

In practice, employees are often already using AI. Sometimes visibly, sometimes invisibly. They ask ChatGPT questions, have texts rewritten, create summaries or use AI functions in software without the organisation having clear agreements in place.

So AI is already there. You are just not steering it yet.

What AI means for SMEs, manufacturing and logistics

In technical, logistics and production-oriented companies, a lot of knowledge sits in people’s heads. In planners. In mechanics. In work planners. In salespeople. In project leaders. In entrepreneurs who have been steering for years based on feeling and experience.

AI can help unlock that knowledge, combine it faster and make it more practically available. Think of:

• preparing customer questions faster;
• creating better quotation structures;
• making internal work instructions more accessible;
• summarising meetings and monitoring follow-up;
• gathering market information;
• making HR, safety or quality documents searchable;
• analysing processes and making improvement opportunities visible.

That sounds operational. But the impact is strategic. Because companies that learn faster, process information faster and prepare decisions better build an advantage.

AI also affects succession and leadership

For successors, young leaders and entrepreneurs in development, AI is especially relevant. Not because they need to understand every technical detail, but because they need to learn how to lead in an organisation where knowledge, information and pace are changing.

Leadership is then no longer just about working harder or responding faster. It is about asking better questions:

• Where do we use AI, and where do we not?
• Which information should never simply be entered into an AI tool?
• How do we check the quality of output?
• Which processes can become smarter?
• How do we prevent people from confusing convenience with truth?

AI therefore requires technical understanding, but above all mature responsibility.

What should you do as an entrepreneur now?

Do not start with the question of which tool you should buy. Start with the question of where AI affects your organisation.

1. Map current usage

Ask where employees are already using AI. Not to punish them, but to make visible what is already happening.

2. Create simple rules

Define what is and is not allowed. Think of customer data, personal data, confidential information, source checking and final responsibility.

3. Choose concrete work processes

Start with processes where there is direct gain: email, quotations, planning, reporting, knowledge sharing, meetings, marketing or internal documentation.

4. Train people practically

You do not learn AI by only talking about it. People need to practise with it using their own work, their own questions and their own context.

5. Lead behaviour, not just technology

The greatest gain is not in the tool, but in the way people use it. Critical thinking remains necessary. Perhaps more than ever.

The core

AI resembles ISO because it forces companies to look more consciously at processes, risks and responsibilities. But AI goes further. It changes how people work, learn, communicate and decide.

Those who only see AI as certification, policy or hype miss the point. Those who learn to use AI practically while staying sharp on quality, safety and responsibility are building an organisation that learns faster and leads better.