Have you ever found yourself in a situation where you and a fellow student gave identical answers to the same questions, yet received different marks? Or perhaps you and a colleague have the same knowledge and skills, but they receive a better job offer simply because they presented their strengths more convincingly in their CV?

Professor Simona Ramanauskaitė of Vilnius Gediminas Technical University, a member of the SustAInLivWork project developing an Artificial Intelligence Competence Centre in Kaunas, says that such experiences can provoke a sense of unfairness and lead people to question the entire system.

“However, the person making the decision is not necessarily acting with bad intentions – like any human being, they may be influenced by various circumstances: mood, fatigue, personal experience, and so on. If the assessment of competences were formalised – handed over to artificial intelligence (AI) or clearly defined by rules without free interpretation – the process would become more accurate and better reveal an individual’s true potential,” she emphasises.

According to Dr Ramanauskaitė, the formalisation of competences would not only identify gaps in an individual’s knowledge and skills, together with possible development paths, but would also provide a clearer structure. This would help define which specialists the labour market needs and would make recruitment easier for companies, enabling them to evaluate candidates’ suitability for specific positions more precisely.

Prof. dr. S. Ramanauskaitė

The Competence Portfolio – the CV Supplement of the Future

Dr Ramanauskaitė explains that the formalisation of competences involves defining the structure of different types of knowledge and skills and their interrelations. For instance, reading ability consists of letter recognition, understanding the meaning of words and sentences, and other essential elements. If even one of these is missing, the skill cannot be fully developed.

“With a detailed tree or graph structure, we can create a personal portfolio for each pupil, student, or employee, showing what knowledge and skills they have already acquired, their level of preparedness in different areas, and their possible directions for further improvement. This would allow for a more objective assessment of an individual’s competences as a whole and would form the basis for AI to provide personalised career recommendations,” she notes.

Constructing a competence tree or graph requires more than factual knowledge – it also draws on descriptions from various fields, the structure of learning materials, job advertisements, and data from scientific articles. In this way, it is possible not only to evaluate existing classifications of knowledge and skills but also to reflect the constantly changing needs of the market, as well as the emergence of new technologies and innovations.

How Can You Know Whether a Study Programme Will Lead to Your Dream Job?

According to the professor, the competence formalisation tool is currently being tested among university students. It shows which competences are developed by a particular study programme, how they evolve during the course of study, and how well a student’s existing knowledge and skills meet labour market requirements.

“If this tool were expanded and higher education institutions consistently developed competence portfolios for their students, these could become a reliable and formal supplement to CVs. Companies with access to such portfolios would be able to select suitable employees more objectively, while students would receive more precise recommendations on which competences to improve to keep pace with, or even get ahead of, market changes,” she explains.

At present, the labour market analysis focuses on Lithuania, but soon it is planned to integrate trends from other countries. This would allow for a deeper understanding of international dimensions and the specifics of different labour markets.

The SustAInLivWork researcher adds that the tool will be tested in other fields of study and is likely to be implemented across different universities. If the concept proves effective in higher education, it could eventually be applied in Lithuanian schools. Pupils would then be able to compare study programmes based on the competences developed, their links to the labour market, and assess which programmes best match their competence portfolios and career aspirations.

“This would involve evaluating whether a pupil’s existing level of competences matches the chosen programme. If they already know more than what the programme aims to teach, the studies may appear insufficient or unengaging. If there are too many gaps and their preparation is weak, they may lack the foundation to acquire higher-level skills during their studies. In such cases, it would be more appropriate to choose a different, more suitable programme, or to devote time to acquiring the missing competences before starting university,” she observes.

Many pupils and students are not always certain about the knowledge and skills required for particular roles, nor whether their chosen programme will provide the necessary competences. By linking competences developed in study programmes with those required by the labour market, one could assess in advance how well a programme aligns with various roles, career paths, and opportunities.

Labour Market Changes: Which Skills Will Be Needed Tomorrow?

Dr Ramanauskaitė points out that the growing impact of AI solutions on labour market dynamics is becoming increasingly visible.

“Interestingly, a significant number of companies still do not fully understand how to apply AI effectively in their operations. Yet, in order not to fall behind competitors, they are seeking employees capable of automating processes through generative AI (GenAI) solutions. This trend is most often observed in smaller companies,” she notes.

Meanwhile, leaders in the information and communications technology (ICT) sector had already been actively seeking specialists in AI, machine learning, sustainable technologies, cybersecurity, cloud computing, and other areas even before the rise of generative AI tools. From such professionals, employers expect the ability to quickly grasp new technologies, think critically, implement existing intelligent solutions as well as create new ones, oversee the entire IT ecosystem, and coordinate its various teams.

Recent developments also reveal a decline in the demand for entry-level programmers and customer service specialists. This trend is driven by the rapid advancement of generative AI: today, simpler software code can be generated automatically, while customer queries are increasingly handled by chatbots.

Nevertheless, this does not mean that these skills are becoming redundant. “On the contrary – programming basics and an understanding of IT are increasingly recognised as essential knowledge, not only within the ICT sector but beyond it,” the researcher stresses.

Thus, while these competences remain relevant, new skills are also becoming crucial: knowledge of AI technologies and their application, an understanding of sustainability and data privacy principles, user experience design and evaluation, and mastery of cloud computing and high-performance computing platforms. Equally important are soft skills such as critical thinking, adaptability, communication, creativity, and continuous learning.

SustAInLivWork: Lithuania’s First Competence Centre of Its Kind

SustAInLivWork is the first competence centre of its kind in Lithuania, systematically consolidating knowledge and skills in AI. It brings together four leading Lithuanian universities – Kaunas University of Technology, Vytautas Magnus University, Lithuanian University of Health Sciences, and Vilnius Gediminas Technical University – in partnership with Tampere University (Finland) and Hamburg University of Technology (Germany).
It is a long-term, cross-sectoral platform connecting science, business, the public sector, and society.

The SustAInLivWork project is funded by the Horizon Europe programme (No. 101059903) and by the European Union funds for 2021–2027 (Project No. 10-042-P-0001).