Problem addressed
Europe faces a critical digital skills gap, with forecasts indicating a shortage of up to 3.9 million ICT professionals by 2027 (McKinsey). Simultaneously, over 100 million workers across the continent will require reskilling to remain employable in a rapidly evolving labour market driven by automation and digitalisation (McKinsey). Traditional talent selection and training processes are slow, resource-intensive, and often biased, prioritising formal qualifications and past experience over actual potential. This excludes many individuals, particularly those from vulnerable or underrepresented backgrounds, who could thrive in ICT roles if given the opportunity.
This mismatch has both social and economic consequences: companies struggle to innovate due to lack of qualified staff, while millions of people risk unemployment or underemployment. In Portugal, for example, reducing the number of NEETs (young people not in employment, education, or training) could raise national GDP by up to 1%, according to the Bank of Portugal. If left unaddressed, the talent gap will further exacerbate inequality, limit social mobility, and hinder Europe’s competitiveness in the digital economy.
MIT responds to this challenge by rethinking how talent is identified, using AI and psychometric analysis to assess potential rather than background. This allows for more inclusive, scalable, and data-driven reskilling, unlocking access to digital careers and promoting economic resilience.
Innovative solution
MIT (Machine-driven Identification of Talent) is an innovative solution that transforms how talent is identified and reskilled for the ICT sector. Unlike traditional approaches, which rely on CVs, previous experience, or formal education, MIT leverages artificial intelligence, machine learning, and psychometric analysis to assess individuals’ potential for success in digital careers, before they acquire technical skills.
The platform delivers a one-on-one introductory course in JavaScript and captures behavioural and cognitive data through user interactions. These include response times, error patterns, navigation behaviour, decision-making processes, and perseverance across tasks. A predictive model, developed in collaboration with a team of psychologists, was trained to identify the psychometric traits most strongly associated with successful rapid reskilling.
This data-driven approach allows organisations to uncover hidden talent, streamline selection processes, reduce bias, and lower the cost and time of reskilling initiatives. By removing subjective barriers and focusing on future potential, MIT promotes inclusion and diversity, particularly among individuals with limited access to traditional educational or professional pathways.
Fully digital, scalable, and adaptable to different sectors or geographies, MIT supports both private companies retraining internal talent and public-sector programmes focused on workforce transitions. It improves efficiency and fairness in talent identification, enabling a more inclusive and sustainable digital transformation.
Key results and benefits
MIT has already demonstrated significant results in pilots with major corporate partners. An illustrative example is a reskilling initiative where 700 candidates were evaluated using MIT’s predictive model. While traditional methods have an average success rate of 6%, Code for All, with the MIT platform achieves an 87.5% success rate in selecting candidates who completed training and were successfully integrated into ICT roles. This translates into a cost reduction per successful reskill from €117,000 to €8,114, generating savings of over €4.5 million.
Beyond economic efficiency, MIT delivers strong social benefits. It promotes fair access to digital careers by identifying talent based on potential, not prior experience or background. This has a particular impact on vulnerable groups, including individuals at risk of job displacement due to automation, and people from low-income or underrepresented communities.
For companies, MIT enables strategic workforce transformation by identifying and retraining internal staff for future-ready roles, reducing dependency on external recruitment. For individuals, it opens up new professional pathways and improves employability in a high-growth sector.
The platform also shortens selection time, improves candidate matching, and increases the success rate of reskilling programmes, laying the foundation for a more inclusive, cost-effective, and data-informed approach to addressing the ICT skills gap at scale.
Potential for mainstreaming
MIT was designed to be scalable, adaptable and fully digital, with minimal human intervention. Its architecture allows for rapid deployment across different industries and countries, making it suitable for both private sector workforce transformation and public employment or training initiatives.
The platform’s ability to assess potential rather than qualifications makes it particularly effective in identifying talent in non-traditional pools, which is essential for scaling reskilling programmes that are inclusive and future-oriented.
Code for All is already preparing for European expansion, targeting regions with similar labour market challenges. Additionally, the MIT platform also aligns with the EU’s digital and social priorities, including the European Skills Agenda and Digital Decade goals. With its demonstrated cost-effectiveness, proven impact on inclusion, and adaptability to diverse contexts, MIT has strong potential to become a model for large-scale, data-driven reskilling across Europe and beyond.
