Held under the Chatham House Rule, the discussion brought together perspectives from industry, research, and policy. While participants represented different regions and priorities, a striking degree of alignment emerged around the challenges ahead – and the role data spaces may play in addressing them.
One participant captured the spirit of the discussion in a simple yet powerful statement:
If data spaces did not exist today, we would have to invent them.
The remark resonated because it reflected a broader realization shared across the roundtable. The conversation was not primarily about technology. Technical interoperability, standards, and federated architectures continue to advance at an impressive pace around the world. Rather, the discussion focused on a complementary challenge: How to create the governance, trust, and economic incentives necessary to make large-scale data sharing work in practice.
This challenge has become particularly urgent in the age of AI.
Artificial intelligence is dramatically increasing demand for high-quality, trustworthy, and context-rich data. At the same time, organizations are becoming more cautious about how their data is accessed, combined, used, and monetized. As AI systems become more powerful, questions about accountability, transparency, provenance, and control are moving from the margins to the center of the debate.
The rise of AI is therefore exposing a critical governance gap. While the world has made significant progress in developing technologies for data exchange, the governance mechanisms required for a functioning global data economy remain unresolved.
Who determines the conditions under which data can be used? How can compliance be ensured? How can data contributors retain meaningful control? And how can value generated from data be distributed fairly?
These questions are no longer theoretical – they are central to whether large-scale data sharing can work in practice.
This is where data spaces increasingly come into focus. Rather than serving merely as technical infrastructures for data sharing, they emerge as governance frameworks that combine interoperability, trust mechanisms, and shared rules for participation. Sovereignty is not an obstacle to data exchange – it is a prerequisite. Organizations are willing to share valuable data only when they can rely on clear rules, transparent governance, and enforceable usage conditions. Data spaces establish exactly these conditions, enabling responsible and scaled data sharing while preserving the control and trust that participants require.
The discussion also highlighted the importance of ensuring that the future data economy is truly global.
Participants stressed that global interoperability cannot be achieved through technology alone. It also requires governance approaches capable of bridging different regulatory environments, economic realities, and societal expectations.
This perspective became particularly visible in discussions about equitable participation in data-driven value creation. Several participants raised concerns about scenarios in which data from less economically mature regions contributes to global innovation without corresponding participation in the value generated. The challenge, therefore, is not only to enable global data flows, but also to ensure that trust, data sovereignty, and value creation can be shared more broadly across regions and communities.
Another area of strong consensus concerned business value.
Participants repeatedly emphasized that the long-term success of data spaces will depend on their ability to create tangible economic benefits. Organizations will not participate because a technology is elegant or because a standard exists. They will participate when data spaces help them solve real problems, unlock new opportunities, reduce costs, improve compliance, or create new forms of collaboration.
The question is therefore shifting from “How do we build data spaces?” to “What value do data spaces create?”
The Global Data Spaces Roundtable pointed to a broader conclusion: the future of the data economy will not be defined solely by our ability to move data across boundaries. It will be defined by our ability to establish trusted governance for how data is shared, used, and transformed into value.
As AI accelerates this transformation, data spaces are increasingly being viewed not merely as a technological concept, but as a governance framework for the next generation of the global data economy – one that can integrate emerging markets, respect sovereignty, and create equitable value for all participants.
