AI Is Moving Fast And The Worst Thing You Can Do Is Nothing

Every day when I wake up, I open my laptop, read my emails, and check the news (also the AI news). And every day I see new models, new research papers, and new projects. There's a lot of things happening.

I feel haste. I feel urgency. I have the feeling that I have to do something with this information and also a little bit of FOMO. I see other companies taking actions and I think maybe we should do too.

All this creates a kind of pentup energy that I don’t really know where to put. It makes me feel like I should do something. And like every person in business I fall back on the most familiar reflex when something becomes too big, too fast, or too complex to handle: outsource it, hire help, make it someone else’s problem.

And with AI I think that it's the wrong way to look around about it.

Outsourcing AI Thinking Is Dangerous

We see this with many of our clients. They bring in external teams like us to build software, just like they hire plumbers to fix blocked pipes. They don’t train plumbers internally because it’s inefficient, and they don’t stand up full development teams from scratch because it takes enormous time, cost, and organisational effort. In most cases, outsourcing is simply the fastest and least disruptive way to keep the business running.

But the moment you hand it off, you also hand off the learning that comes with it. The thinking, the decisionmaking, the conversations you should be having internally about AI, those end up happening somewhere else, with someone who isn’t living your organisation’s reality.

And that’s the real risk. AI is topic simply too big, and it’s going to change the way we work too deeply, for any organization to outsource the understanding and the learning to an entity outside your own walls.

Why AI Is Different From Every "Disruptive" Technology Before

When we talk about technology, we often throw around the word “disruptive,” but AI genuinely earns it. Not because it’s louder or faster, but because it changes where work happens and who can do it. So the question becomes: why is AI different from all the other technologies we once thought would change everything? For me, it comes down to three simple but profound shifts.

1. Humans work inside systems, AI works across them

We all work in systems. Whether it’s CRM, email, development tools, ERP (you name it) our daily work happens inside these structured applications. But the real effort, the part no system truly handles, lives between those tools.

Whenever something is too complex or too unstructured to automate, we put humans there. They make judgment calls, chase information, talk to multiple teams, fix issues, and move processes from status A to status B. In practice, people act as the connective tissue that keeps all these systems aligned and moving.

They are the glue between applications, and that’s exactly the space where AI is starting to make an impact.

Those inbetween roles, those loops are now increasingly automatable. Five years ago this simply wasn’t realistic. Today, AI can take over more of that glue work, the work currently done by people, and in the future this will only accelerate.

2. AI automates what was previously not automatable

The AI market can be sliced in many ways, but the distinction that works best for me is this:

On one side, you have tools, the more traditional, incremental form of software development. A new feature here, a small improvement there, something that makes a product 5% better or a bit nicer to use. In the AI world, that’s things like translation features, summarisation buttons, or a smart autocomplete that fills in a few fields for you. Useful, but ultimately just extensions of what software has always done.

Then you have agents. And I’ll be honest, I don’t even like the word, because everyone calls everything an “agent” these days, and 9 out of 10 times it isn’t one. Because if you look carefully at what a true agent actually is, it’s something very different.

It's a software system that can take unstructured information, turn it into its own todo list, execute that list (or ask other AIs to do it), move between systems, pull data from your CRM, make decisions, and then produce structured, meaningful output. That’s not a nicer tool. That’s a different category of software entirely.

Because the truth is, our work is really just a bundle of tasks. Some of those tasks are incredibly difficult to automate (like building relationships, reading a room, having dinner with a client if you are a salesperson). Human connection isn’t something AI can replace so those parts of the task bundle are, for now, safe.

But the small, repetitive administrative tasks? Current AI systems can already automate many of these or help you complete them much faster. And everything in between. Those mixed bundles of judgment, admin, and minor decisions, AI will become increasingly capable of handling. And that capability will only continue to grow.

But how will people experience these shifts? How will we guide them through it? How will we make sure this transition strengthens, rather than unsettles, the organization?

Navigating the Human Side of an AI-Driven Workflow

Certain tasks will naturally shift from humans to AI, we see that happening little by little everyday. One or two tasks here, a small process there, nothing dramatic at first. The work doesn’t disappear. It simply stops being done by people.

And that’s where the real conversation begins. Because while tasks may move, the people doing them don’t vanish. Their identity, their sense of contribution, and the value they bring to the organisation are tied to that work. So we need to start talking about these things now, openly and honestly.

The Financial Pressure

A little while ago, we visited one of our retail clients. In many ways, their organisation was wellstructured: each department ran efficiently within its own vertical, people knew what they were responsible for, and they solved problems quickly. But the moment work had to move between those verticals, everything started to slow down.

They had people manually moving information from one system to another. Typing data into Excel, copying it into Outlook, pulling information back out of Outlook, adjusting formats, fixing small inconsistencies (“this should be five numbers instead of six”), and repeating that process dozens of times a day. None of it was strategic work. All of it was essential work.

And this is the reality for many organisations. These manual gluetasks easily cost €50,000 per person per year. Now imagine an AI system that can do 80% of that work for €500 a year.

What would you do then? What would your customers do? What would any business do if they had a hundred people performing those types of tasks?

This is where the financial motivation becomes impossible to ignore.

People Need To Be Part Of The Plan

This is where the human side becomes just as important as the financial one. If you’re not actively planning for how AI and automation will be introduced in your organisation, how people will be trained, how their roles may evolve, and how this new technology will find a place that feels fair and comfortable, then people simply get left out of the story.

Because if the discussion reaches the board without that human context, it turns into a numbersonly decision. On a spreadsheet, €550,000 versus €500 is not a dilemma; it’s a conclusion. And when that comparison involves dozens or hundreds of people, the choice becomes even more obvious.

That’s why it’s essential to build a human plan alongside the financial logic. People need to understand what’s coming, how it affects their work, and what their future looks like in an AIenabled organization. This shift is happening whether we want it or not but how people experience it is still very much in our hands.

The First Steps Every Company Should Take

We need to start having real conversations about AI, not because it's trendy, but because the world around us is moving whether we participate or not. Two years ago, for some organisations, “AI” meant buying a chatbot or automating a single workflow. But every day I open my laptop, read the news, or check new research, and the capabilities have grown again. Things we thought were impossible last year are suddenly standard.

Other companies are already acting on this. And if we aren’t even aware of what’s becoming possible, we can’t expect our organization to generate the ideas or innovations we’ll need to stay competitive.

The best ideas always come from people. But only if those people are informed, involved, and part of the conversation.

1. Remove the Fear Around Automation

Automation is already happening all around us, and one of the most important things organisations can do is make it a topic people feel safe discussing. It doesn’t have to be a scary word. In many industries (manufacturing is a great example) automation has been evolving for decades. Work that was once done with hammers, chisels, and manual effort is now done by robots, and often done better.

So automation itself isn’t the problem. The real challenge is helping people understand what it means for them. You need a plan for how your organisation will adapt, how roles might evolve, and how people will be supported through that change. When automation is part of an honest, structured conversation, it becomes something you manage, not something you fear. And that brings me to the second point.

2. Be Transparent

Transparency becomes critical the moment you start moving toward AI adoption. People need to understand what is happening, why it is happening, and how it will affect the way they work. When organisations stay quiet or vague, uncertainty fills the gaps. And uncertainty quickly turns into fear.

That’s why you need a clear roadmap. Not a perfect one, but one that shows direction, intent, and honesty. Let people see how you’re approaching this project, what decisions are being made, and where they fit into the story.

If we are upfront about the scale of the transformation, people can prepare, contribute, and adapt. But if we keep the process behind closed doors, AI becomes something that “happens to them” rather than something they are part of.

3. Enable Organisational Insight

Before you can do any of this successfully, you need a clear understanding of your own organisation. Your processes, your data, your people, and how work actually gets done. This has never been more important, because AI is now capable of automating the kinds of work that were previously considered impossible to automate.

Most companies have beautifully documented process diagrams and welldefined application flows. But everything between those flows, the real daytoday work, the unwritten parts of your job description, the informal steps people take to keep things moving? Those are rarely captured anywhere. And it’s exactly in that unstructured space where AI is beginning to make its impact.

Act or Be Acted Upon

Are you going to be the kind of organisation that embraces AI intentionally? One where people are informed, aligned, and understand how the company plans to work with AI as its capabilities grow?

Or will you become the organisation where AI simply “happens” to you? Two years pass, competitors have embraced AI, costs have dropped, efficiency has soared, and suddenly customers are asking why you can’t keep up.

If you reach that point, you no longer have the time or space to create your own framework, your own human story, or your own way of adapting to these changes. You’re forced into action instead of choosing it. And by not acting, by not even beginning the discussion, you’re still making a choice.

You’re choosing to end up in the group where AI happens to you rather than through you. And that is a position no organisation wants to find itself in, yet it is the silent reality many companies are drifting toward.

AI Is a Train Already Moving

AI is getting more capable every day, and ignoring it won’t slow it down. It’s a train already in motion, whether we like it or not. The only real question is whether we choose to take control of how it impacts us.

That starts with getting informed, involving more people, and having the conversations that matter. And I genuinely believe we are already taking good steps in that direction at CLEVR. More people are engaged, more discussions are happening, and that’s exactly what we need.

So talk about it. Think about it. Discuss it with your colleagues. The more we share our thoughts and questions, the better prepared we become.

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