Master's in AI University of Alicante 2026: new curriculum and what it means for companies

Key data

Companies seeking specialized talent in Artificial Intelligence have had, since October 2026, a clearer reference for what graduates of the Master's in AI from the University of Alicante know—and don't know. The Resolution of September 22, 2026 formalizes the curriculum modification following the favorable report from the Valencian Agency for Evaluation and Foresight (AVAP) of June 29, 2026.

The curriculum redesign eliminates any elective component: all 60 credits are entirely mandatory (51 ECTS of courses + 9 ECTS of Master's thesis). This means all graduates follow exactly the same educational pathway, which facilitates profile evaluation by recruitment departments.

What does this regulation establish?

The resolution sets the new structure of the Master's Degree in Artificial Intelligence at the University of Alicante, based on Royal Decree 822/2021 on the organization of official university education. The curriculum is configured as follows:

The areas of knowledge covered by mandatory courses are:

• Machine learning
• Deep learning
• Computer vision
• Natural language processing (NLP)
• Intelligent robotics
• Architectures for Artificial Intelligence

The modification was validated by AVAP through a favorable report issued on June 29, 2026, complying with the procedure established in Royal Decree 822/2021 for the modification of official university curricula.

Economic and operational impact

For companies, the impact is not regulatory in the sense of direct legal obligation, but it does have concrete operational consequences in three areas:

1. Talent recruitment and selection. Since the curriculum is 100% mandatory with no electives, all graduates of this master's program share the same competency map. HR departments and technical managers can anticipate with greater precision what these candidates know and don't know, reducing the time and cost of evaluation in selection processes.

2. Complementary training. The absence of external internships in the official curriculum means graduates arrive without work experience accredited by the university. Companies hiring these profiles will need to plan a more intensive onboarding period or seek candidates who have supplemented their training through other means.

3. Talent demand planning. The curriculum redesign focusing on areas such as AI architectures, intelligent robotics and NLP points toward where demand for specialized profiles is heading. Technology companies and digital transformation departments can align their hiring plans with these emerging competencies.

Who does it affect?

• Technology companies that hire engineers and AI specialists, machine learning or computer vision experts.
• HR and recruitment departments that evaluate candidates with AI qualifications from the University of Alicante.
• Digital transformation managers that plan data and artificial intelligence teams.
• AI startups seeking junior profiles with solid technical training in deep learning, NLP or robotics.
• Technology consulting firms that incorporate specialized talent for client projects.
• Students and future candidates evaluating this master's as a professional specialization pathway.
• Teachers and researchers from the University of Alicante linked to the program.

Practical example

A software development company based in Alicante is looking to hire a computer vision specialist for an automated industrial inspection project. They receive the CV of a graduate from the Master's in AI at the UA with the new curriculum.

Thanks to the 100% mandatory structure of the curriculum, the technical manager knows with certainty that this candidate has taken courses in computer vision, deep learning and AI architectures, in addition to completing a 9 ECTS Master's thesis. There are no alternative pathways that could have excluded any of these subjects.

However, the recruitment manager also knows that the curriculum does not include external internships, so the candidate likely has no experience in real industrial environments. This information allows them to design a specific technical test and plan an adaptation period of 2-3 months before assigning autonomous responsibilities on the project.

What should companies do now?

1. Update candidate profile sheets for AI roles: include the 6 areas of the new curriculum (machine learning, deep learning, computer vision, NLP, intelligent robotics and AI architectures) as verifiable competencies in candidates from the UA.
2. Review onboarding processes for junior AI profiles: given that the curriculum does not include external internships, plan a more structured adaptation period with internal technical mentoring.
3. Communicate to recruitment teams that all graduates of this master's program follow the same educational pathway, which simplifies comparison between candidates.
4. Evaluate whether the master's profile fits your team's needs: the focus on intelligent robotics and AI architectures may be especially relevant for companies in industrial automation or cloud infrastructure.
5. Consider collaboration agreements with the UA (thesis projects, scholarships, voluntary internships) as a way to access talent before graduation and compensate for the absence of internships in the official curriculum.

Official source

View complete regulation at official source

Notice: This article is for informational purposes only and does not constitute legal advice. For specific decisions, consult a qualified professional. Source: https://www.boe.es/diario_boe/txt.php?id=BOE-A-2026-20525