Artificial intelligence (AI) is becoming a fundamental pillar for productivity advancement in Europe, according to the latest report from the European Investment Bank (EIB). The study highlights that the adoption of AI and the analysis of large volumes of data have been responsible for nearly 12% of total productivity growth since 2019 in the European Union. Although the gap with the United States and China remains significant, experts agree that a well-defined European strategy could help regain ground in key sectors. Pablo López-Aranguren, digital manager at Mutualidad, points out that AI is already driving growth and productivity in the EU. OECD figures suggest that these technologies could add between 0.4% and 1.3% to annual labor productivity growth over the next decade in economies with high adoption. Additionally, average labor productivity in European companies has increased by 4% thanks to AI, with no net job destruction observed in the short term. However, productivity per hour in the EU remains 38% lower than that of the US, according to data from the European Employers Institute. From the employers' association Adigital, it is confirmed that companies that have integrated AI are more competitive, although they warn that the macroeconomic impact is still limited. The IMF estimates that AI could raise European productivity by 1.1% accumulated over five years, while the ECB predicts that with accelerated adoption, the boost could reach between 1.5 and more than 4 percentage points in the next decade. The EIB report emphasizes the need to invest in innovation, data centers, and energy infrastructure to avoid dependence on external suppliers. In 2024, private investment in AI in the US reached $109.1 billion, representing 81% of the global total, compared to $9.3 billion in China and $8 billion in the EU. Initiatives like InvestAI aim to reduce this gap. AI is transforming sectors such as financial services, manufacturing, healthcare, and critical infrastructure. Tim Pfaelzer from Veeam highlights that the greatest benefits are seen in data-intensive industries, where AI improves forecasting, automates processes, and facilitates more agile decision-making. In services, automation and accelerated analysis allow for more coherent decision-making, especially in sectors with high customer interaction and regulatory demands. Adigital identifies telecommunications, information technology, and professional activities as the most advanced sectors in AI adoption, although improvements are also observed in logistics, industry, energy, and commerce. In insurance and finance, penetration is particularly high: 92% of EU banks already use AI, and two-thirds of insurers employ generative AI, according to EIOPA. Traditional European companies are also innovating. Siemens Energy, Schneider, and ABB lead the manufacturing of electrical equipment for AI data centers, while EssilorLuxottica stands out in smart glasses thanks to partnerships with Meta. Roche, for its part, operates the largest hybrid cloud AI factory in the pharmaceutical sector, accelerating the development of therapies and diagnostics. Europe maintains leadership positions in key technology segments, such as semiconductor equipment production in the Netherlands and Germany (ASML, ASM International, BE Semiconductor, Aixtron) and in power semiconductors (Infineon, ST Microelectronics), essential for AI infrastructure. Anis Lahlou from Aperture Investors emphasizes that Europe combines a robust industrial ecosystem with a regulatory framework that prioritizes digital sovereignty and energy resilience, factors that position it as a key player in the global AI value chain. However, the investment gap persists. In 2023, software spending represented 1.8% of GDP in the EU compared to 2.7% in the US. Nevertheless, the adoption of advanced digital technologies in European companies already matches that of the US (77% vs. 78%). The distribution of AI adoption is uneven: countries like Finland, Denmark, and the Netherlands exceed 55% of companies using generative AI, while Italy and Greece barely reach 20%. In Spain, Madrid, Catalonia, the Basque Country, and the Valencian Community lead in adoption. Additionally, large companies have implementation rates of 44%, compared to 28% for SMEs, which face greater investment and training barriers. Tim Pfaelzer underscores that the impact of AI depends on sector maturity, data availability, and responsible management capacity. Vanguard warns that the concentration of investment in traditional sectors could affect European competitiveness, although an acceleration in AI adoption and institutional reforms could reverse this trend. Álvaro Fernández from Capital Group highlights that government strategy is key: China promotes AI as strategic infrastructure, the US favors innovation with light regulation, and Europe prioritizes regulation and privacy, which slows adoption. Corporate culture and labor flexibility also influence the speed of implementation. Pfaelzer advocates for clear and practical regulation, along with continuous investment in infrastructure and skills, especially for SMEs and startups. Experts agree that AI can help Europe close the gap if obstacles are overcome and it is approached as a common project. European regulation, modernization of infrastructure, and the use of renewable energy offer competitive advantages to attract investments. Adigital concludes that for AI to drive business competitiveness, Europe needs stable policies, multi-year funding, and a clear industrial strategy, as well as common data infrastructures and public AI services that facilitate access for SMEs and administrations. As Pablo López-Aranguren notes, data is the essential resource of AI, and Europe has a strategic volume in industrial, healthcare, and financial sectors. The challenge will be to transform this potential into a competitive advantage, balancing data protection with innovation. Source: cincodias.elpais.com