AI is not digital transformation: Why waiting is no longer an option (and where the quick wins are)
In every conversation we have with clients (mainly SMEs in Flanders) we see the same pattern. They feel that AI could mean something for their business, maybe even spark a revolution in how they deliver products or services. They see markets and customer needs shifting at lightning speed. They know they have to act, because their competitors aren’t standing still either. However, not all companies investing in AI are seeing the promised productivity boost. In fact, many companies barely see economic return from their AI initiatives. Where does it go wrong? The technology is available, insanely capable, and affordable. This is not a technology problem; it is a people problem. What are these companies doing wrong? How do you make the right choices, allocate budgets efficiently, and actually integrate AI successfully?
Standing still is going backwards
Every time a promising technology emerges and attracts attention and investments, the same pattern returns:
- The technology improves
- Costs drop sharply
- Usage explodes
- The rules of the game change
We saw this with electricity, the internet, smartphones, and cloud. Artificial Intelligence belongs in the same league. It is more than digitisation. We can no longer ignore it.
The question is no longer “Should we do something with this?” but “How are we going to tackle it?”
If you wait, you fall behind — especially at today’s adoption speed.
AI is more than a digital transformation
Classic digitization is about replacing old tools with new ones: A becomes B. A typewriter becomes Word. A taxi becomes Uber. We used to do something one way, and now we do it another. Our brain understands that.
AI adoption is more complex. It’s closer to the arrival of the iPhone. It didn’t just replace the mobile phone; it reshaped how we bank, navigate, shop, communicate, and work. Large Language Models do the same. They don’t replace a single tool, they change how we think and operate.
To succeed with AI, companies must dare to rethink things radically:
- What can we eliminate?
- What can be automated without losing quality?
- What new services can we offer that were impossible yesterday?
It’s not about replacing, but about simplifying, enriching and even reinventing.
Start small, but start now!
So how do you actually get started? Here are the steps to success.
Step 1: Get your data in order
Ironically, SMEs are sitting on mountains of data, but can’t access them. Quotes, customer questions and product information are scattered across Excel files, polluted ERP systems and CRM fields full of duplicates.
As long as your data is fragmented and messy, AI is powerless. AI needs context.
So don’t begin with a massive IT overhaul. Start with a pragmatic clean-up. Set up a simple, central place where you bring data together, clean it up and make it usable.
Step 2: Start with some quick wins
I’m convinced every SME has at least three simple AI quick wins within reach - no big budgets required:
- Automate repetitive work
Think: generating quotes, summarising reports, or processing incoming emails. - Unlock knowledge
An internal AI assistant, trained on internal HR policies or technical datasheets for example, can immediately give correct answers to employees’ questions. At Unikoo, we have even built an internal AI platform that facilitates knowledge sharing between colleagues. - Let your first agents handle small but time-consuming tasks
Early agents can already operate autonomously in narrow tasks. A drafting agent creates the first version, a validation agent checks it. These exist today, and they work.
Start small. Build experience. Experiment. You’ll learn how the tech behaves, where the pitfalls are, and where real investment is needed. Every step you take now is one your competitors will have to catch up on later.
Step 3: Think further, achieve more
A surprising number of companies cling to old ways of working because “that’s how we’ve always done it”. If you enrich bad processes with AI, they’re still fundamentally bad processes.
What’s missing to get real value from AI is a critical mindset and guts.
- guts to break open processes.
- guts to review habits, responsibilities and workflows.
- guts to admit that a large part of today’s work could actually be done better, faster and more consistently.
That is exactly why AI adoption goes wrong. We too often get stuck in the quick wins. We use AI to make easy tasks more efficient, but we avoid the complex use cases where the real added value lies.
The technology is ready. The tools exist. The use cases are everywhere. The only question is: do you dare to truly rethink your processes before your competitor do?
Think beyond the obvious. Surround yourself with experts.
As always: business must meet technology.
Looking for tech experts to help you with this? Our tech team is ready to support you!
