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Europe is falling behind in the artificial intelligence (AI) race, struggling to keep pace with the rapid innovation strides made by the United States and China. A complex interplay of factors is driving this disparity, including inadequate funding, a fragmented market, cumbersome regulatory frameworks, and a persistent talent gap that hinders the region's ability to attract and retain top AI expertise.
One of the main reasons for Europe's sluggish progress in artificial intelligence is the limited availability of venture capital and a weak stock market. Between 2012 and 2020, venture capital investments in the U.S. were ten times higher than those in the Euro area. Private investment in AI within the European Union (EU) accounts for less than 10% of the global total, while China and the United States together represent 80%. Specifically, U.S. private investment in AI is thirty-five times greater than that of Germany, the largest market in Europe, with figures of $249 billion compared to just $7 billion.
This lack of investment is partly attributable to the European banking model, which focuses on risk assessment and enforces strict regulations that limit investments in startups. Furthermore, large institutional investors, who are typically more willing to take on riskier investments, make up a smaller portion of the venture capital market in Europe compared to the U.S.
Territorial fragmentation regarding innovation significantly obstructs AI developments, as does the incompleteness of the European digital market. The concentration of AI Innovation Development Centers is primarily found in a few regions, specifically Île-de-France, Oberbayern, and Noord-Brabant. The inadequacies of the digital market compel companies to navigate the complex regulatory frameworks of twenty-seven states, which limits their ability to compete effectively on both European and global scales. This fragmentation further slows the internationalization efforts of national champions, as member states compete against each other for dominance on the continent.
The regulatory framework in Europe significantly impacts the development of AI, particularly in relation to the European Artificial Intelligence Act (AI Act). While the AI Act aims to regulate "high-risk" AI systems, some commentators suggest that it may stifle innovation. Others argue that the stringent standards and bureaucratic hurdles could hinder the growth of AI startups in Europe.
Europe faces significant obstacles in leveraging data to drive innovation. The scarcity of available data, coupled with limited access to existing datasets, hinders the continent's progress. This is exacerbated by the dominance of non-European "Big Tech" companies, which own the majority of the world's data, leaving many European SMEs at a disadvantage.
The European digital market's fragmentation further complicates the creation of a common data set. Private businesses, institutions, and other stakeholders often fail to collaborate and share data, hindering the development of a cohesive AI ecosystem. This deficiency has far-reaching consequences, weakening technology research and development activities and slowing the adoption of AI technologies by non-specialist companies.
Talent and Skills
To capitalize on the AI opportunity, Europe must develop its talent and skills. Companies need to invest in building the right expertise to drive AI adoption and innovation. By addressing these challenges, Europe can unlock its full potential and become a leader in the AI landscape.
Many components still need to be finalised before Europe can effectively compete with the United States or China. One crucial step is the development of a digital single market, which is essential for establishing a robust, integrated ecosystem for artificial intelligence (AI) and innovation. Enhancing interconnectivity between existing innovation clusters and creating new ones can lead to valuable synergies and economies of scale. Additionally, simplifying the process for EU startups to expand beyond their country of origin is vital.
Moreover, Europe must tackle the issue of data availability and access by promoting collaboration and data sharing between businesses and institutions. It is also important for Europe to prioritise action in key areas to accelerate its progress in AI: continuing to nurture a vibrant ecosystem of deep tech and AI startups, speeding up digital transformations, advancing the digital single market, developing the right talent and skills, and thinking strategically about how to navigate potential disruptions in society.
