A different view by Jaime Porta

A few years ago, digital transformation was something you planned carefully and executed slowly. It meant large programs, long discussions about systems and architecture, and a clear separation between “strategy” and “execution.” AI followed the same path. It was powerful, but distant. Something reserved for companies with strong IT teams, large budgets, and the patience to deal with complexity.

That’s the mindset many people still have today.

I see it quite often when I talk to friends who run small and medium-sized businesses. For them, AI is mostly tools like ChatGPT or Claude. Useful for writing a quick email or generating a piece of text, maybe even for brainstorming ideas. But still something disconnected from their daily operations.

When the conversation moves beyond that, when I explain that AI can actually be integrated into their processes, the reaction is usually predictable. It sounds interesting, but also complex. Too complex. Something that probably requires a team, time, and investment they simply don’t have.

After hearing this a few times, I stopped trying to explain it in theory. And started showing it in practice.

A few weeks ago, I had this exact discussion with a friend who runs a small business selling products both online and offline. Like many SMEs, his setup is functional but far from optimized. He has an eCommerce platform, manages customers, processes orders, follows up manually, and spends a significant part of his day on repetitive tasks that don’t really add value but still need to be done.

We agreed on a simple experiment. No big promises. No long-term plan. Just a weekend to see what could be done.

The idea was not to build something perfect, but something real.

We used Make.com as the integration layer, connecting his existing systems. On top of that, we added OpenAI to interpret requests and generate structured actions. The goal was straightforward: take the things he already does every day and make them easier, faster, and in some cases, automatic.

What we built was surprisingly simple.

Instead of navigating through systems, he could just describe what he wanted. The AI would interpret the request, structure the information, and trigger the right action through the workflow. Creating a customer, placing an order, checking pending deliveries, or reviewing customer status all became conversational.

One of the most interesting moments was when we connected image input. He could take a picture of a business card, and the system would extract the data and create a new customer automatically. We also tested voice commands. On his way to the office, he can now ask for a list of customers who hadn’t bought anything in the last few months and get a clear list of people to call by the time he

Behind the scenes, the setup was not complicated. Input comes in as text, voice, or image. The AI processes it and translates it into structured data. The automation layer routes the request. The existing systems execute it. That’s all.

But the impact was immediate.

At some point, he stopped asking how it worked and started using it naturally. That’s when you know something has changed. It was no longer about AI, or automation, or technology. It was simply a better way to run his day.

In a large organization, this would be described as a productivity improvement initiative. It would likely involve multiple teams, a roadmap, KPIs, and a business case. In his case, it was just a practical improvement. Less time on manual tasks. Faster execution. Better follow-up with customers.

And that difference matters.

Because it highlights something important. The barrier to adopting AI is no longer technical. It’s conceptual. Many SMEs don’t need more tools. They need a different way of thinking about the tools they already have access to.

If you look at it from that perspective, the entry point becomes much simpler.

It can start with very basic use cases. Writing or replying to emails faster, without overthinking every sentence. Generating product descriptions or marketing content in minutes instead of hours. Preparing social media posts or blog drafts without starting from a blank page. Summarizing customer interactions or meeting notes so nothing gets lost. Even drafting simple offers or proposals based on previous ones.

These are not revolutionary changes.

But they are cumulative.

And once you take that first step, it becomes easier to move into more integrated scenarios, like the one we built over that weekend. Connecting AI to your customer data. Automating parts of your sales process. Identifying opportunities that would otherwise be missed. Supporting daily decisions with better information, delivered at the right moment.

This is where the real value starts to appear.

From my perspective, this is also where my role has evolved over time. It’s no longer just about defining strategies or selecting platforms. It’s about translating complexity into something that works in real life. Taking the potential of AI and turning it into practical, usable solutions that fit the context of each business, regardless of its size.

Because the truth is, AI is no longer reserved for big organizations. It’s becoming accessible, flexible, and increasingly easy to integrate.

What makes the difference now is not who has access to the technology, but who is willing to experiment with it.

And sometimes, all it takes is a weekend to change how a business operates.