The conversation
AI is no longer only a technical topic. It is becoming a leadership topic.
In this episode of Business Transformation Journey, Ondrej Papanek speaks with Amir Elion, founder and senior advisor at Think Big Leaders, about how AI is changing leadership, middle management, team structures, decision-making, and the future of work. These are topics Amir regularly speaks about at conferences and corporate events.
Amir brings experience from product innovation, startups, enterprise organizations, and leading innovation programs at Amazon Web Services in the Nordics. Today, he helps leaders and organizations understand AI, build innovation mechanisms, and prepare for what comes next.
AI is not just a technology shift
Many leaders still treat AI as something technical — placing it in the hands of IT, engineers, or specialists, and waiting for someone else to explain what it means for the business.
That mindset is already becoming dangerous.
The barrier to using AI has dropped. Leaders no longer need to be technical experts, but they do need to understand what the technology can do, where it creates value, and where human judgment must remain in control.
"Don't sit on the fence and wait. If you do that, you will become irrelevant."
Takeaway: Leaders do not need to become technologists. They need to become better decision-makers in a technology-shaped world.
Rethinking jobs, skills, and what we hire for
One of the most provocative themes in the conversation is the idea that stable job descriptions may themselves be outdated. In most organizations, there is a job, a job description, and a more-or-less stable set of expectations. You get recruited based on it, measured on it, promoted through it. But in a world where tools and roles shift monthly, that assumption needs rethinking.
"If you don't bury your head in the sand, this is actually happening all around. A software engineer — if you ask them even three months ago what their role was and you ask them what their role is today, that's completely different."
The traditional model — give people skills, measure their performance against those skills, onboard and train accordingly — is breaking down. The skills keep changing. AI can perform many of them. What matters more now is curiosity and the ability to learn.
"Learn and be curious — another important leadership principle from Amazon. That kind of open mindset, the bias for action, because then even if the job shifts and the new tools come, you can learn a new way. You can design new ways of working."
For leaders, this means promoting a learn-and-be-curious mindset, enabling experimentation, and creating safety for mistakes. When deciding who gets new challenges, bet on adaptability, not just current expertise.
Middle managers must move beyond passing information
One of the strongest points from the conversation was the changing role of middle management. If a manager's main value is moving information up, down, and sideways, that role is at risk. AI can already help people access information faster, summarize context, and connect data across teams.
This does not make middle managers unnecessary. It makes their deeper value more important.
Middle managers need to interpret meaning. They need to help people understand why priorities are changing, how work is evolving, and what the shift means for their roles. They must create clarity, not just distribute updates.
They also need to model the behavior they expect from others. Curiosity cannot be delegated. Experimentation cannot be announced once in a weekly meeting. Leaders need to show what learning looks like in practice.
AI can move information. Leaders must create meaning.
Hybrid teams: humans and AI agents working together
The conversation goes beyond today's AI tools to the near future of hybrid teams. Any individual contributor may soon manage 10 AI agents, creating small teams for themselves. This raises leadership questions that go far deeper than previous digital transformations.
"We're going to have hybrid teams with AI agents and humans working together. We're going to maybe have different management paradigms. What is the role of a manager? Now, any individual contributor can manage 10 agents."
Unlike moving infrastructure to the cloud — which changed operations but not team structure — AI is reshaping the fundamental composition of teams. Communication, success metrics, and management paradigms all need rethinking.
Mechanisms beat good intentions
Amir draws on Amazon's approach to scaling innovation. Good intentions and energy alone don't work — you need mechanisms that help people execute.
"Good intentions, just putting energy into things doesn't work. You need to show people a mechanism that helps them. And I know some people perceive mechanism as a bureaucratic, negative thing. I don't think it is — it's a structure that helps us in this very complex, fast-moving, attention-grabbing, messaging world."
Amazon's Working Backwards methodology is one such mechanism: start with the customer, write an imaginary press release for the finished product, and work backwards through the details. The point isn't the specific framework — it's that leaders must provide structure, not just direction.
The real opportunity is simplification
AI exposes how complicated many organizations have become.
Old processes, outdated documentation, unclear ownership, and slow decision paths become visible when leaders try to delegate work to AI. If the process is unclear for people, it will also be unclear for the technology.
"Because if you're going to delegate things to AI, you need to teach it — this is how we do our reporting, this is how we do our content creation, this is how we do our onboarding. If you don't have these processes defined, you can't even start."
That is why AI is not only an efficiency tool. It is also a mirror.
It shows where work has become too heavy, where decisions are stuck, and where organizations are still following rules that no longer make sense. And it forces a question that should have been asked years ago: do we even need this process?
"People come to me and say, we want to do something with AI. And I stop and say — why? What is the value? What are you trying to change? Maybe AI is part of the solution. Maybe it's not. Maybe the problem is the whole process."
Strong leaders will use AI to simplify, not just accelerate. They will ask what can be removed, what can be clarified, and where people should focus their attention.
What leaders can do right now
- Stop waiting for perfect certainty. Start with small experiments that are safe, visible, and connected to real work.
- Create a learning rhythm. Teams should explore AI together, reflect on what they learn, and turn useful lessons into better ways of working.
- Simplify before you automate. Ask what process should be improved before you try to layer AI on top of existing complexity.
- Build mechanisms, not mandates. Give people structure that helps them execute on innovation, not just instructions to "be more innovative."
- Hire for curiosity. When the landscape shifts monthly, adaptability matters more than any specific skill set.
Three questions for leaders
- If AI can move information faster than you, what value do you bring as a leader?
- Where are you protecting an old way of working because it still feels familiar?
- What process in your organization should be simplified before you try to automate it?
AI will not wait for leaders to feel ready. The leaders who succeed will be those who stay curious, take responsible action, and help their teams learn in motion. That is what makes AI a business transformation topic — not just a technology topic.
Following this episode, host Ondrej Papanek published a companion article: "Is Your Leadership Mindset Ready for AI?" expanding on the key themes from the conversation.