The discourse at ITW 2026 underscored a critical issue in AI: achieving sovereignty in artificial intelligence depends not just on data location, but also on a thorough approach to infrastructure and governance. As global leaders in technology and telecommunications convened, a pressing question emerged: What defines AI sovereignty in an era where data and computing power are important to national security and economic growth?
Moderated by Mehdi Paryavi, CEO of the International Data Center Authority, the panel included insights from industry veterans like Peter John Alexander of MeetKai and Travis Ewert of Digital Realty. They engaged in a lively discussion that explored the nuances of AI sovereignty, revealing that it involves a range of controls throughout the AI lifecycle, from model ownership to operational governance.
Ewert emphasized that sovereignty should be seen as an ongoing effort rather than a fixed goal. He stressed the need for stable frameworks from the beginning to enable nations to effectively manage their AI ecosystems. This view challenges the traditional belief that simply housing data domestically is enough for sovereignty.
The economic implications of this debate were starkly articulated by Alexander, who highlighted the structural opportunities AI offers for countries aiming to retain talent and boost local economies. "AI allows people to stay at home," he remarked, suggesting that nations investing strategically in AI infrastructure can rapidly transform their economies. However, those lacking foundational investments in technology and regulatory support risk becoming dependent on external powers, particularly the US and China.
Alessandro Lombardi of Elea Data Centres provided a poignant example of the pitfalls of regulatory misalignment. He noted that Brazil, despite its capacity and population, often routes its data offshore due to prohibitive regulations and taxes. This situation illustrates the disconnect between sovereign AI aspirations and the necessary infrastructure, highlighting that without significant investment in local capabilities, countries merely export their dependencies.
The key takeaway from the panel was clear: creating regulations without supporting infrastructure development is misguided. Countries that impose restrictions on data flows without building their own capabilities risk perpetuating a cycle of dependency on foreign AI systems. This emphasizes the urgency for governments to align their regulatory frameworks with the realities of infrastructure investment.
As discussions around AI sovereignty continue to evolve, the consensus emerging from ITW 2026 serves as a reminder that true independence in the AI domain requires a multifaceted strategy, where infrastructure and regulatory policies work together. The challenge ahead is to makes sure that nations do not fall behind in the race for AI dominance and that they invest wisely to lay the groundwork for a sovereign future in artificial intelligence.
Quick answers
What is the core issue discussed at ITW 2026 regarding AI sovereignty?
The panel discussed that AI sovereignty is not just about data location but requires comprehensive infrastructure investment and governance.
Why is infrastructure investment critical for AI sovereignty?
Without local infrastructure, countries risk becoming dependent on foreign powers and losing control over their AI ecosystems.
What example did Lombardi provide to illustrate regulatory challenges?
Lombardi noted that Brazil sends much of its data offshore due to regulatory barriers, despite having the capability to support domestic infrastructure.
