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By 2030, artificial intelligence is projected to create more than 200,000 jobs. Industry executives are detecting a shortage of trained personnel and calling for greater preparation
Interview published by La Razón
The literature on artificial intelligence (AI) is as abundant as it is diverse. There is debate about how many jobs it will create, how many it will destroy, and what kind of training it will require for new generations.
Some technology leaders, such as Elon Musk, argue that in the future, people will only work for pleasure, because “artificial intelligence will do everything.” Others, such as Jensen Huang, CEO of Nvidia, argue that AI will generate more and better jobs.
On the more pessimistic side, Dario Amodei, CEO of Anthropic—the world’s second-largest AI company after OpenAI—warns that it could eliminate up to half of all administrative jobs in just four years, according to Professor Maha Hosain Aziz in The New York Times.
Whatever the scenario, one thing seems clear: universities and vocational training must adapt if they want to remain competitive. The emergence of AI is not a passing trend; it is a structural disruption that is already transforming the nature of work and redefining the skills needed to thrive.
The impact is already here
The International Monetary Fund estimates that 60% of jobs in advanced economies and 40% in emerging markets are already exposed to AI. The Inter-American Development Bank estimates that 980 million jobs could be affected next year, and the World Economic Forum predicts that 41% of employers will reduce their workforce by 2030 due to automation.
“AI will not replace us, but by those who know how to use it,” said Jean-Christophe Deslarzes, global CEO of The Adecco Group, during a recent visit to Madrid. His warning encapsulates a message repeated in forums and conferences: the challenge is not to compete with machines, but to learn to work with them. However, this transition is not easy. Many workers face a difficult decision: learn AI to remain relevant or be left behind. It is not merely a matter of acquiring technical skills but of developing an adaptable mindset capable of continuous relearning.
Training is not progressing at the same pace
93% of Spanish workers report familiarity with AI, but only 1 in 10 have received training at their company, according to the report Artificial Intelligence and Future Employability by Planeta Formación y Universidades.
“We are dealing with a technology that is evolving so quickly that there is no time to incorporate new profiles with sufficient experience.”
“We are dealing with a technology that is evolving so quickly that there is no time to bring in new profiles with sufficient experience,” explains Mario Cortés Flores, director of Intelligent Apps & Power Platform at Tokiota. Although he does not yet see this as a critical problem, he warns: “Many companies are retraining their employees thanks to their knowledge of the business, but there will come a point when this will not be enough.” The gap between knowledge and application is widening every month. While algorithms are being refined and generative AI tools are entering offices, design studios, and law firms, formal and corporate training is progressing slowly.
Spain already has some 2,000 companies dedicated to AI, and it is expected to generate some 200,000 related jobs by 2030. However, the supply of professionals does not meet the demand. A study by IndesIA predicts that by 2025 there will be more than 3,000 unfilled vacancies, and that two out of three positions related to AI or data analysis will be challenging to fill.
“Companies that train their teams in AI will have a clear competitive advantage. Those that won’t lag in productivity and innovation.”
“The paradigm shift is evident,” says André Ribeiro, senior vice president and general manager for Iberia at BTS. “Companies that train their teams in AI will have a clear competitive advantage. Those that won’t lag in productivity and innovation.”
The risk is not only economic but also strategic: companies that do not integrate artificial intelligence will lose agility and responsiveness relative to competitors. Ribeiro adds that “professionals trained in AI will lead the change, while a significant portion of the workforce will be relegated to lower value-added tasks, which will accentuate inequality of opportunity.”
Sixty-six percent of Spanish leaders believe that their employees must update their skills and responsibilities to adapt to the impact of AI, exceeding the global average of 60%, according to The Adecco Group. “What organizations are looking for are professionals capable of interpreting results, making data-driven decisions, and applying AI to generate tangible value,” says Iván López, global vice president of corporate sales at ODILO. Along these lines, Lucía Álvarez, general manager of Odigo Iberia, adds: “Leading in technology does not mean knowing about code or algorithms, but rather guiding teams in constantly changing environments.”
The most in-demand profiles include data engineers, machine learning specialists, business analysts with AI knowledge, and also hybrid roles: marketing, legal, or healthcare professionals who integrate AI tools into their daily practice. Ander Serrano, partner and head of innovation at Evercom, is clear: “Professionals who cannot reorient their role will be left on the margins of the market.”
How can training outside companies be accelerated so that AI does not replace employees? The data is not encouraging. According to the IndesIA Barometer, university degrees in AI and data analysis account for only 2.2% of themore than 7,000 courses offered in Spain. The concentration is uneven: Madrid and Catalonia account for 59% of bachelor’s degrees and 45% of master’s degrees. Fewer than 0.5% of the country’s 1,519 doctorates address AI, and they are offered only in Madrid, Catalonia, and the Basque Country.
The Learning Heroes school, which focuses on disruptive technologies, has observed a 37% increase in demand for AI training, particularly in generative AI and its marketing applications.
“STEM subjects are a good starting point, but they must be complemented with languages, art, and philosophy to encourage different ways of thinking,” Ribeiro insists. Creativity and critical thinking are becoming key skills for coexisting with increasingly intelligent machines.
Meanwhile, some countries are leading the way. Stanford and MIT universities have redesigned part of their programs to include ethical AI, prompt engineering, and data analysis. In Germany, the government is promoting the AI Made in Europe program, which funds the retraining of industrial workers for digital jobs. In Singapore, citizens can access the SkillsFuture Credit, a public training credit, to pay for courses in AI and automation throughout their working lives.
Spain, although lagging, is beginning to move. The National Digital Skills Plan aims to invest more than €3 billion by 2026 to improve the population’s technological training. The challenge, according to experts, will be to translate that investment into practical programs that are accessible to all sectors.
“Education in the 21st century can no longer respond to the model of the industrial revolution,” says Iván López. “Knowledge no longer occurs only in classrooms. Podcasts, videos, simulations, and microlearning are transforming the way we learn.” The very nature of work is also being redefined. Professions such as law, translation, and advertising are incorporating generative tools that automate part of their tasks. But far from eliminating these professions, they are forcing them to reinvent themselves. The lawyer of the future will need to know how to use ChatGPT to draft contracts faster, and the advertising creative will need to master AI to generate personalized campaigns at scale. The change is already here.
Hybrid talent: the key to the future
Experts agree that the future does not belong to pure engineers or classical humanists, but to hybrid professionals. Those capable of combining analytical thinking, human sensitivity, and technological understanding.
Mario Cortés sums it up this way: “Generative AI forces us to do things differently and, consequently, to think differently. People who know how to apply it correctly will be the ones who really succeed. This requires a balanced combination of technical skills, adaptability, and imagination.”
In this new paradigm, lifelong learning is no longer an option but a professional obligation. It will no longer be enough to obtain a university degree; it will be necessary to retrain every few years. The change is already here.
The gap between technological adaptation and training: the new bottleneck
The artificial intelligence (AI) revolution is not only transforming business models, but also the very concept of talent. From marketing to banking, consulting to customer service, experts agree on one diagnosis: the gap between technological adoption and professional training threatens to become the new bottleneck for competitiveness.
Ander Serrano, partner and head of innovation at Evercom, argues that the challenge for sectors such as communication and marketing is not so much technical as human. “In our sector, purely human qualities intuition, empathy, and creativity remain the most valuable. What we need are profiles capable of combining these skills with technological knowledge.”
The rise of generative AI has skyrocketed the demand for specialized talent: in Europe, the hiring of freelancers with these skills has grown by 300% in just two years, according to data from Malt. But supply is not keeping up. Serrano sees this as an opportunity to increase productivity and create more added value, but also as a threat: This view is shared by André Ribeiro, senior vice president and partner at BTS, who warns that the lack of specific training in AI “is not only an operational obstacle, but also a major strategic risk.” According to Ribeiro, only 28% of Spanish users of AI tools have received specific training.
Along the same lines, Iván López, Global VP of Corporate Sales at ODILO, emphasizes that the most critical demand is concentrated in AI applied to business: “Organizations are looking for professionals capable of translating data into tangible decisions and results.” López argues that training must be continuous, dynamic, and personalized. “The goal is no longer to accumulate certificates, but to generate applicable knowledge.”
From a technological perspective, Mario Cortés Flores, Director of Intelligent Apps & Power Platform at Tokiota, confirms that the shortage of qualified professionals is a reality. His recipe for the medium term combines technology and humanism: “Generative AI forces us to think differently. We need profiles with technical knowledge, adaptability, and imagination. STEM subjects are foundational, but the study of languages, the arts, or philosophy must complement them. Only then will we be able to think outside the box.”
In an environment where the presence of women remains limited, Lucía Álvarez, Managing Director of Odigo, calls for a different kind of leadership: “Leading in technology is not just about knowing code, but about guiding teams in constantly changing environments. Empathy and clear communication are as critical as technical knowledge. Innovation arises when there are different voices at the table.”