I started this research because I thought that Europe’s AI infrastructure was too fragmented and that Europe might need an additional coordination mechanism.
During the development of the idea, I received criticism that Europe already has many coordination mechanisms. Rather than defending my original proposal, I decided to test whether an additional overarching mechanism was actually necessary.
The result surprised me. I did not find sufficient evidence to establish the empirical necessity of another overarching coordination mechanism.
However, the research pointed to a different problem that may be more important: the time between a coordination decision and its real effect across the system.
AI technology is developing very quickly, while governance, standardisation, infrastructure and implementation operate on different timescales. In some of the cases examined, this mismatch appears to matter. The study therefore suggests that Europe should measure not only what coordination mechanisms, programmes and infrastructures it creates, but also how long it takes for their decisions and outputs to produce effects across the wider AI ecosystem.
I describe this as time-to-effect.
The formal result of the study is H0 NOT REJECTED: the evidence did not establish the necessity of an additional overarching coordination mechanism. This does not mean that the existing European AI coordination architecture is optimal. The more specific findings point to weaknesses at the interfaces between existing mechanisms and to cases where coordination takes time to produce system-level effects — even when mechanisms for remediation already exist.
A short Policy Brief is attached, translating these findings into practical policy priorities — including interface measurement, interoperability, time-to-effect, incentive testing and escalation triggers.
The full Research Report, evidence base and supporting methodological records are publicly available on Zenodo.
Comments and feedback are welcome.
Zenodo / DOI:
https://doi.org/10.5281/zenodo.22143707
- Tags
- AI Infrastructures
Comments
In reply to I like the "time-to-effect"… by Jose Carretero
Thanks, Jose. I think you captured the key point very well. The question may be less about adding coordination and more about how quickly existing coordination translates into real capabilities. That is exactly what I mean by time-to-effect.
I like the "time-to-effect" idea.
In large technology organisations, adding another governance layer often doesn't fix fragmentation if the interfaces between the existing ones are still slow.
For AI this seems especially important. A good decision on standards, infrastructure or policy can arrive too late if it then takes a year to move through funding, procurement and implementation.
Measuring how fast decisions actually become usable capabilities could be more valuable than creating another coordination body.