Artificial Intelligence and the Professions of the Future

Publicado: 07/09/2026 | Actualizado: 07/09/2026

Planeta Formación Universidades

Artificial Intelligence is already changing the tasks people perform, the skills companies look for and the professional profiles with the strongest growth prospects. Its impact is not limited to creating new technology jobs. It is also reshaping existing roles in marketing, finance, education, human resources, design and business management.

The figures help put that transformation into perspective. The World Economic Forum estimates that major trends reshaping the labour market, including AI, will create 170 million jobs by 2030 while displacing 92 million, resulting in a net gain of 78 million roles. At the same time, 39% of the skills workers use today are expected to change or become outdated during that period.

That is why talking about the professions with the brightest future is not about trying to guess which job will be fashionable five years from now. It is more useful to understand which sectors are growing, which tasks technology can take over and, above all, which skills will help people work alongside it.

How is Artificial Intelligence transforming the job market?

The first transformation is taking place inside existing jobs. AI can summarise information, analyse huge amounts of data, generate content, automate processes and detect patterns in seconds. As a result, some tasks are becoming less important while new ones are emerging.

But being exposed to AI does not mean that a job is going to disappear.

Research published by the International Labour Organization in 2025 estimates that one in four jobs worldwide has some degree of exposure to generative AI. Its key conclusion is that job transformation is much more likely than complete replacement, as most occupations still involve tasks that require human input (International Labour Organization, 2025).

This can already be seen in everyday working situations:

A marketing professional can use AI to create an initial draft, but still needs judgement to define the strategy and assess the final result.
A financial analyst can automate part of the data processing and spend more time interpreting what the figures actually mean.
An HR team can streamline administrative tasks and focus more on recruitment, talent development and people management.
A developer can use coding assistants, but still needs to know what to build, how to test it and how to solve problems when something goes wrong.
A teacher can use AI to create resources or personalise activities without replacing their pedagogical role.

This is also why the uses of artificial intelligence in everyday life and how to make the most of them are becoming increasingly connected to the professional world. Many tools first become familiar outside the workplace and later become part of everyday business processes.

The same applies to the debate around AI and the future of human creativity. The question is no longer simply whether a machine can write, design or generate an image. Professional value increasingly lies in giving technology direction, context, critical judgement and a clear purpose.

Types of artificial intelligence and their impact on companies

There is no single application of AI. The term covers technologies designed to solve very different problems, and companies often combine several of them.

From a business perspective, it is easier to understand them by looking at what they can actually do.

Generative AI
Produces text, images, audio, video or code. It is increasingly used in communications, marketing, design, programming, customer service and content creation.
Predictive AI and machine learning
Uses data to identify patterns and generate predictions. It can help forecast demand, detect fraud, estimate risks or understand customer behaviour.
Natural language processing
Allows systems to work with large volumes of written or spoken information. It is used in virtual assistants, document analysis, message classification and automatic information extraction.
Computer vision
Analyses images and video. Its applications range from manufacturing and healthcare to logistics, security and quality control.
Intelligent automation and recommendation systems
Help personalise services, organise information and automate repetitive processes or decisions.

AI adoption in business is accelerating. In 2025, 20% of EU companies with ten or more employees were already using at least one AI technology, compared with 13.5% the previous year. Among large companies, the figure exceeded 55% (Eurostat, 2025).

The change, however, is not simply a matter of buying a tool. When a company introduces AI, it also needs people who can work with data, define the right problems, interpret results and manage the risks involved.

That is where areas such as Big Data become even more relevant. A company can generate huge amounts of information, but data has little value if nobody knows how to clean it, analyse it and turn it into decisions.

AI adoption also brings issues that previously received less attention in many teams, including privacy, cybersecurity, bias, transparency and the responsible use of automated systems.

The professions with the brightest future in the digital age

Technology is driving some of the professional profiles expected to grow fastest over the coming years.

According to the Future of Jobs Report 2025, the fastest-growing professions in percentage terms through 2030 include Big Data Specialists, FinTech Engineers, AI and Machine Learning Specialists, and Software and Applications Developers (World Economic Forum, 2025).

Some of the profiles gaining ground are:

AI and Machine Learning Specialist, developing, training or applying AI models.
Big Data and Data Analytics Specialist, working with large volumes of information and turning them into useful insights.
Data Scientist, combining statistics, programming and business knowledge.
Software Engineer or Developer, particularly in projects where AI is being integrated into applications and services.
Cybersecurity Specialist, an increasingly important role as organisations become more digital.
FinTech professionals, working at the intersection of finance and technology.
Automation and Digital Transformation Specialists, connecting technological tools with business processes.
AI governance, ethics and regulation professionals, helping organisations use these systems responsibly and within regulatory frameworks.

Growth is not limited to technology. The World Economic Forum also points to strong prospects for jobs related to renewable energy, environmental engineering, education and care (World Economic Forum, 2025).

That matters when looking at the most in-demand careers in Spain in 2026. Good career prospects do not automatically mean becoming an AI engineer.

In fact, the OECD notes that fewer than 1% of workers are expected to need advanced AI-specific skills, such as programming or developing machine-learning models. For a much larger proportion of the workforce, it will be more important to know how to use technology, analyse and interpret data and combine those capabilities with management and problem-solving skills (OECD, 2026).

In other words, the opportunity is not limited to working in AI. It also lies in becoming better at another profession by knowing how to use AI within it.

Upskilling and Reskilling: What to study to avoid falling behind?

The question is no longer only which jobs will disappear and which new ones will emerge. For many professionals, a more useful question is which part of their current skill set needs to change.

Two concepts help explain the options:

Upskilling means developing new skills to progress within an existing profession.
Reskilling means acquiring a different set of capabilities to move into another role or professional field.

A marketing professional learning data analytics is upskilling. If that same person decides to move into data science and builds an entirely new technical foundation, the process is much closer to reskilling.

The need for both will be significant. The World Economic Forum estimates that, out of every 100 workers, 59 will need some form of training before 2030. In addition, 77% of employers plan to upskill their workforce in response to the growth of AI (World Economic Forum, 2025).

For anyone considering a professional change, upskilling and reskilling: how to reinvent your career in times of change offers a useful way to distinguish between strengthening an existing profile and preparing for a different career path.

Which skills are worth developing will depend on the role, but several areas appear repeatedly:

AI and Big Data, among the fastest-growing skills.
Technological literacy, to understand and use new digital tools.
Networks and cybersecurity.
Analytical thinking and problem-solving.
Creativity, especially when technology takes over part of the execution.
Communication, leadership and collaboration.
The ability to keep learning throughout a career.

The combination matters. OECD research shows that AI increases the importance of working with and interpreting data, while human capabilities such as problem-solving, creativity and innovation remain essential (OECD, 2026).

The same can be seen in AI in education: impact, challenges and opportunities. Knowing how to operate an AI tool is only one part of the job. Teachers still need pedagogical expertise to decide when to use it, how to assess its output and what role it should play in learning.

Why study a Master's in Artificial Intelligence

An AI master's degree makes particular sense when the professional goal goes beyond learning how to use individual tools.

For professionals who want to understand how AI can be applied to strategy, processes and business decisions, the Master's in Artificial Intelligence & Machine Learning for Business can help connect the possibilities of these technologies with real business challenges.

Other profiles may be looking for a more specialised and technical approach. In that case, the Official University Master's Degree in Artificial Intelligence provides a route to deepen knowledge in areas such as machine learning, data processing, intelligent systems and other AI technologies.

Before choosing an artificial intelligence master's degree, an Online Master's in Artificial Intelligence, a University Master's Degree in Artificial Intelligence or any other specialisation, three questions are worth asking:

Do I want to learn how to use AI or how to develop AI-based solutions?
Is my career goal closer to technology itself or to its application in business?
Which skills appear repeatedly in the jobs I want to apply for?

These questions help avoid one of the easiest mistakes to make during a period of rapid technological change: studying a trend without being clear about what it is supposed to add to a professional profile.

There are strong reasons to pay attention to this field. Stanford's AI Index Report 2025 found that 78% of organisations surveyed were using AI in 2024, up from 55% in 2023 (Stanford Institute for Human-Centered Artificial Intelligence, 2025).

But perhaps the most useful conclusion for anyone thinking about their career is simpler. Technology is moving quickly, but it still needs people who know how to turn it into useful solutions.

The goal is not to compete with Artificial Intelligence, but to develop profiles capable of using it, questioning it and combining it with human expertise. Once we know the direction we want to take, choosing the right training becomes much easier.