The emergence of generative AI will determine the competitiveness of companies in the short term. And while our companies have a lot of room for improvement in this race to adopt disruptive technologies, they’re not faring too badly. indicators of National Astronomical Observatory … Technology and Society (ONTSI) They point out that our country is in a middle position in the EU in corporate adoption of AI, at 11.4% compared to the European average of 13.5%. “Surprisingly, countries such as the United States (5.7%) and the United Kingdom (4.1%) have lower numbers, according to the OECD,” said Director-General Nuria Avalos. Indiaan employer association that promotes the use of data and AI in businesses and small businesses.
Additionally, the European Commission (Digital Decade 2025) highlights our country’s commitment to advances in artificial intelligence, including the National Artificial Intelligence Strategy 2024 and the Green Algorithms Plan to make AI more sustainable. We have initiatives such as the Barcelona Supercomputing Center (BSC) and the National Supercomputing Center. We are pioneers in launching a regulatory “sandbox” for high-risk AI systems to help companies and startups adapt to future European legislation. We also participate in European networks of excellence such as ELLIS and projects such as OpenGPT-X.
And while the large-scale basic models of generative AI are in the hands of large foreign multinationals with deep pockets and sufficient resources (ChatGPT, Copilot, Gemini…), Spain has published its own open source generative AI models such as MarIA and larger architectures such as ALIA (all developed in Spanish and the co-official languages).
With all these strengths, “Spain will have the necessary competencies and talent to develop generative AI models, especially in collaboration in consortia with European partners,” says Nuria Ábalos. Fran Monzonis, Al Chief Executive capgemini spain, He also believes that: “Spain has talent and first-class research centres, but we need more investment and public-private cooperation to win this competition.”The future lies in partnering with Europe and leveraging its strengths in areas such as communications, energy, banking and government, where AI will have a big impact.
When it comes down to earth, the AI is implemented in a very uneven way. According to ONTSI, AI tools are already deployed in 44% of large enterprises, but only 20.6% of medium-sized enterprises, 8.6% of small and medium-sized enterprises, and 7% of micro enterprises. “And according to our barometer, more than 97% of SMEs have not adopted AI, despite its direct impact on productivity and competitiveness. SMEs face the greatest difficulties in adopting the technology and face challenges that are not easy to overcome, such as lack of investment, specialized talent, knowledge and appropriate technological infrastructure,” says Nuria Avalos.
The most advanced areas for AI are in banking, insurance, telecommunications, energy, healthcare, and retail, where these tools are used for applications such as risk analysis, demand forecasting, and virtual assistants… But generative AI is making great strides because it can generate content, analyze conversations, and make decisions based on data. “It doubles productivity and opens the door to deeper automation. Spanish companies recognize the potential, but the challenge is how to make it a reality. Experimenting alone is not enough. We need a clear strategy, investment, and a cultural change that enables human-machine collaboration. This new paradigm “This brings us to a story about the ‘Agent Company of the Future,’ where agents handle most of the operational tasks and humans focus on strategic thinking, creativity, and empathy,” says Monzonis.
Nuria Ávalos says much remains to be done to implement one of the most innovative technologies of recent times. “One of the main challenges is inequality in access to digital infrastructure. Not all regions and sectors have the connectivity, processing power or cloud services needed to implement advanced solutions. technology gap This limits the competitiveness of small and medium-sized enterprises and those located in regions with less digital development, and increases regional differences. Another key challenge is the lack of talent specialized in artificial intelligence and data analysis. On the other hand, data management is also a major barrier. Many businesses don’t have the right systems in place to collect, structure, and utilize data securely and efficiently. There is also legal uncertainty in the face of evolving regulations such as the new European Artificial Intelligence Regulation (AI Law). In addition to this, there are also questions about return on investment. Although AI promises efficiency and innovation, many companies, especially those in traditional sectors, find the change costly or uncertain. Furthermore, although the government is promoting programs and aid, the institutional impact remains limited. For small businesses, the challenges are even greater. As limitations in scale, resources, and knowledge make AI adoption difficult, specific strategies must be designed to make this technology accessible and useful.
In summary, as Fran Monzonis also observes: “The big challenge for Spain is to combine investment, human resources and regulatory stability to avoid being left behind in the competition that will determine the competitiveness of companies in the coming years.”
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