Charlotte Mattfolk has been working with future analysis for 26 years and founded IAMAI based on one insight: "AI will change the world, and I wanted to build something that would make that happen." IAMAI is a platform for the development of intelligent ecosystems, and Mattfolk's perspective is clear: AI must be integrated throughout the entire value chain in order to create real business value.
She highlights how American and Chinese tech companies were early to build data-driven ecosystems that not only collect data but also enable continuous learning. Europe, on the other hand, has largely built digital services on other people's infrastructure.
"We build what is at the very top of the stack, but they still sit on the base data and we are dependent on them," she says.
From operational to intelligent
According to Mattfolk, achieving long-term competitiveness requires Europe to develop its own AI tech stacks. This means not only digital infrastructure, but also physical access to energy, data centers, hardware, and software. An example from a US Senate hearing shows how these components together create the conditions for AI-driven growth.
But for AI to work, access to data is required – and this is where Europe faces a paradox.
"If we don't get the opportunity to share more data now, then we can't have any agentic AI experiences here," says Mattfolk.
GDPR and other regulations make it difficult in practice to share the data required for AI solutions to be scaled up.
With innovation come opportunities – and challenges
The conversation also touches on future technology. Smartphones as global access points will face competition from AI-powered glasses and humanoid robots. These "new smartphones" function both as data collectors and assistants, with the ability to understand and respond to human behavior.
"We will see many new devices that collect data and create value," explains Mattfolk.
A clear example is Elon Musk's strategy to build a coherent data ecosystem between electric cars, robots, space travel, and language models. Controlling data flows from multiple sources creates unique competitive advantages for AI training. Exciting, isn't it?
But what does this actually mean for organizations and leadership? According to Mattfolk, AI will be able to take over parts of operational management: "AI will be very good at leading and distributing work, but coaching and support will still be a human task."
Finally, Mattfolk points to a changing logic in business life. Instead of repeating established processes, AI-driven systems will be self-improving and continuously create value.
“We have talked about learning organizations, but this is something completely different. Every process can become intelligent and adapted to needs.”
Charlotte Mattfolk concludes with a call to action: Europe must be part of the next wave of AI. For industry, it is no longer a question of digitization as a side project, but of building intelligent companies from the ground up.
An industry for the future
AI is no longer a question of the future, but a strategic necessity. To harness its full potential, industry needs to understand how ecosystems, data sharing, and technology infrastructure interact. It's about more than algorithms—it's about building structures that enable real-time learning.
An "AI tech stack" is the collection of resources required to develop and operate AI solutions: from energy and connectivity to cloud services, models, and applications. A "data ecosystem" refers to a holistic approach where data is collected, refined, and used in a circular process for innovation.
By investing in these capabilities, industry can gain a competitive edge in an increasingly knowledge-driven world.
Listen to the entire interview on the Beyond Tomorrow podcast here.
