I am grateful to have had the opportunity to present one of my research projects at the CORA Conference. Special thanks go to Prof. Dr Marianne Saam and Dr. Anne Jurkat for their support, inspiring discussions and for giving me the opportunity to contribute to this exchange.

As well, I would like to thank all participants for the interesting questions and reflections.

My presentation explores how innovation capacity and AI diffusion are related across countries using publicly available secondary data.

Four key takeaways:

• Innovation capacity comes first. Countries with stronger innovation systems tend to experience faster subsequent AI adoption, even when accounting for initial AI adoption levels and development differences.
• AI and robots follow different diffusion patterns. AI adoption is closely linked to innovation-system inputs, while industrial robot adoption does not show the same empirical pattern in these data.
• The productivity channel remains an open question. The evidence for AI affecting productivity through diffusion is promising but not causally identified and is sensitive to sample composition.
• Different technologies may run on different diffusion clocks. AI software can spread within a few years, whereas capital-intensive robot diffusion likely unfolds over a much longer horizon-a hypothesis to be tested with longer-term IFR data.

The central contribution of this work is not a causal claim, but a more credible picture of the cross-national relationship between innovation capacity and technology diffusion.

You can find the presentation here:
https://sabrinaschork.com/wp-content/uploads/2026/09/cora2026_schork_presentation.pdf