Some personal reflections on AI, what makes us human and the future we are building at Everything Now.
I’ve been thinking a lot about AI lately.
The question for me is bigger than what it can do today. I’m interested in what it means for the way we work, the value we create and the businesses we are building.
This is a personal reflection. I am not trying to predict the future. I’m trying to understand where we are, what history can teach us and how that understanding can help us make better decisions.
At Everything Now, this is particularly personal.
We are a strategic studio born in the age of AI. We don’t have decades of established structures or processes to protect. We have the opportunity to build our business around what technology makes possible.
At the same time, we need to understand what makes us human. What makes us different. What gives our work meaning and value beyond what technology can produce.
I want to build a studio that understands technology as deeply as it understands people.
One that uses AI to expand our capabilities while protecting the qualities that make our contribution distinctive: judgment, creativity, curiosity, empathy, relationships, taste and an understanding of culture.
These are the human qualities I believe we must protect and develop, even as technology becomes increasingly capable.
Two recent experiences have pushed me to think much more deeply about this.
The first is an AI project we are developing with Magnus. It is forcing us to question some of the assumptions we have built our professional lives around.
The second was Arena by Design Hotels in Oaxaca, where I had the opportunity to listen to Juan Enríquez, a Mexican-American futurist, investor and author whose work explores how technological revolutions transform society, business and even our understanding of right and wrong.
His presentation challenged me to look beyond AI itself and consider the technological revolutions that came before us.
One of the ideas I found particularly interesting connects to his book Right/Wrong: How Technology Transforms Our Ethics: technology does not only change what we can do. It changes what we consider acceptable, valuable and ultimately right.
I started thinking about how people must have felt when something they had spent their entire lives learning suddenly became easier, cheaper or less valuable.
What happened to those people? Their professions? Their businesses?
And what can we learn from their experience?
We have been here before
When Gutenberg introduced the printing press to Europe, the economics of knowledge changed.
For centuries, reproducing information required enormous amounts of human effort. Books were scarce, access to knowledge was limited, and the people and institutions controlling that knowledge held considerable power.
Printing changed that.
Over time, books became more accessible, information travelled further and entirely new professions emerged around publishing, editing, translation and the distribution of knowledge.
Knowledge remained valuable. The way it was produced, distributed and valued changed completely.
When something becomes abundant, its value changes.
That is something I think about constantly when I see how quickly AI can produce work that once required days of research, writing or analysis.
Producing information is becoming easier. Knowing what matters, what is relevant and what to do with it is another question.
Technology alone does not transform businesses
Electrification offers another interesting lesson.
When factories first introduced electric motors, many simply replaced their existing power systems without fundamentally changing how production worked.
The greatest productivity gains came later, when businesses redesigned their factories, workflows and operating models around what electricity made possible.
They had to rethink the system, not just replace the technology.
I see something similar happening with AI.
We are all experimenting. Writing faster, researching faster, producing more. But I wonder how much of that is genuine transformation and how much is simply doing the same things with different tools.
If AI allows us to do ten times more of something that does not really matter, what have we achieved?
At Everything Now, this is becoming an important principle.
We do not want to use AI simply to produce more presentations, more reports or more content.
We want to use it to:
Understand our clients better.
Challenge assumptions.
Identify opportunities.
Improve the quality of our thinking.
Question whether some of the work we have traditionally considered necessary should exist at all.
The value of work is changing again
Computers and the internet offer a more recent example.
Entire professions were transformed as software took over activities that once required considerable human effort.
At the same time, new industries emerged, new skills became valuable and individuals gained capabilities that previously required entire teams.
AI is taking this transformation further.
It is moving into the work involved in creating, interpreting and acting on information.
And that changes the economics of professional services.
For a business like ours, this is impossible to ignore.
We operate in an industry where clients have traditionally paid for expertise, experience, strategic thinking and the work required to translate those things into recommendations and actions.
As AI reduces the cost of execution, we need to be very clear about where our value actually comes from.
I do not believe it comes from the number of hours we spend preparing a presentation.
It comes from understanding the problem. Knowing which questions to ask. Connecting business objectives with culture, creativity and human behaviour. Making recommendations we can stand behind.
And ultimately, helping our clients make better decisions.
What we are learning at Everything Now
Building a studio during this transition is both exciting and uncomfortable.
We are learning as we go. Testing new ways of working, questioning how we structure our teams and reconsidering what capabilities we need to develop internally.
But there is something I am becoming increasingly clear about.
We cannot prepare for the future by continuing to train ourselves exclusively for the past.
My team and I are deliberately shifting our attention away from skills whose primary value comes from repetitive execution.
We are focusing on developing capabilities that allow us to work with AI, direct it, question it and use it to achieve better outcomes.
That means learning how to:
Design more intelligent workflows.
Ask better questions.
Interpret information critically.
Connect ideas across disciplines.
Turn insights into decisions.
Experiment and learn continuously.
Challenge the way we have always done things.
The foundations of our profession remain essential. We still need to understand strategy, marketing, business and creativity.
The way we apply that knowledge is changing.
I do not want my team to become better at work that technology is making less valuable. I want us to develop the skills that will make us more valuable in the future.
That future cannot be built around technology alone.
The more we understand what AI can do, the more attention we need to give to what makes us human.
Our ability to build trust. To understand emotions and cultural nuances. To recognise when something feels wrong, even when the numbers suggest otherwise. To challenge a client when necessary. To take responsibility for our recommendations.
Human relationships, responsibility and lived experience remain central to the work we do.
Learning to appreciate the cracks
There is another change happening in the way I think, and it is a very personal one.
I used to be a perfectionist. Perhaps because perfection was difficult to achieve. It required time, experience, effort and endless revisions. Getting something exactly right felt like an accomplishment.
AI is changing my relationship with perfection.
Today, producing something that looks polished, complete and technically perfect is becoming increasingly easy.
And strangely, that is making me appreciate imperfections more.
The gaps. The cracks. The things that do not quite fit. The questions that remain unanswered.
Those are often the places where something interesting begins.
A perfectly structured answer can make us feel that the problem has been solved, even when we have not asked the right question.
A beautiful presentation can hide weak thinking. A convincing analysis can create certainty where there should be doubt.
And an imperfect idea can open the door to something entirely new.
In an age of increasingly perfect outputs, our ability to recognise what is missing may become more valuable than our ability to produce something flawless.
Sometimes, it is through the cracks that light gets in.
We spend so much time trying to eliminate imperfections, when sometimes they are precisely what allows us to see something differently.
I am not arguing for mediocre work or lower standards.
I am learning to understand the difference between quality and perfection.
Quality matters. Accuracy matters. Craft matters.
Perfection can also become a distraction. It can encourage us to close questions too early, remove the unexpected and settle for an answer that looks finished.
Innovation often begins with something unresolved.
At Everything Now, I want us to remain curious about those gaps and cracks. To question apparently perfect answers, challenge what technology produces and leave room for experimentation, intuition and unexpected connections.
Perhaps one of the most important skills we can develop is knowing when not to accept the perfect answer.
Developing people, not just capabilities
There is another question I think about often.
If AI can perform many of the tasks through which younger professionals traditionally learned their craft, how do we make sure they develop the experience and judgment needed to become future leaders?
We cannot simply remove the learning process because technology can produce the output.
We need to rethink how people learn, gain experience and develop expertise.
As someone building a team, I see that as one of my most important responsibilities.
I want my team to become confident using technology and equally confident challenging it.
To develop the curiosity to explore unfamiliar ideas, the judgment to recognise weak conclusions and the courage to disagree when something does not make sense.
These are the capabilities I believe will matter more as AI becomes part of almost everything we do.
Understanding the past is helping me think about the future
Studying previous transformations gives me perspective.
History does not promise that everything will work out.
People lost jobs. Businesses disappeared. Entire industries had to reinvent themselves. The benefits of technological progress were not always distributed equally.
But history does remind us that the value of human contribution has changed many times before.
Understanding those changes is far more useful than simply fearing them.
I do not know exactly where AI will take us. Nobody does.
But working on our own AI project, combined with the ideas Juan Enríquez shared at Arena, has given me something I was not expecting.
More confidence. And more direction.
I still do not have all the answers. I am beginning to understand the questions we should be asking:
What will become abundant?
What will become more valuable?
What should we stop doing?
What should we protect?
What skills should we develop?
What kind of company do we want to build in response?
For Everything Now, this is not an exercise in predicting the future.
It is about making better decisions today.
I want us to be a studio shaped by technology, but defined by people.
A studio where AI helps us think further, explore more possibilities and deliver better outcomes. Where our team develops the capabilities the future will demand rather than simply preserving the skills of the past.
And where we never confuse greater efficiency with greater value, or a perfect output with an original idea.
We started Everything Now to bring clarity to complexity, connect strategy with creativity, challenge conventional thinking and make a meaningful difference to the businesses we work with.
Those ambitions have not changed.
The tools are changing. The economics are changing. The skills we need are changing.
And perhaps I am changing too.
I am learning to value what we can make better, faster and more precise. I am also learning to appreciate what remains imperfect, unexpected and unresolved.
Sometimes the most important thing is not having the perfect answer.
It is noticing the crack that everyone else is trying to cover.
That is where I want to take Everything Now.
Written by Yamil Errasti
Managing Director
