Developing of monitoring and forecasting system to tackle the challenges facing the labour market caused by AI technologies penetration

  • Project idea information

    Priority

    Innovative and socially responsible Danube region - Increase competences for business and social innovation

    Project Idea Promoter
    (name of the institution)

    Bulgaria Economic Forum

    Needs and challenges
    (Needs, main problems or challenges to be addressed)

    Reports predict that by 2030 between 400 and 800 million jobs could be lost worldwide due to Artificial Intelligence (AI) technologies penetration. This process will cause serious social challenges and problems and may lead to increased social inequality. Socio-economic, legal and ethical impacts have to be carefully addressed. The EU should prepare for socio-economic changes brought about by AI. These are some of the areas to be supported in this regard: support business-education partnerships; set up dedicated training and retraining schemes for professionals; foresee changes in the labour market and skills mismatch; encourage Members States to modernise their education and training systems. The following needs, problems and challenges should be addressed in the Danube Region:
    • Lack of system for monitoring and predicting the changes in the labour market as a result of AI penetration
    • Lack of structured transnational cooperation in the Danube region in relation to the restructuring of the labour market

    Objectives
    (main and specific objectives to be achieved)

    The main project objective is to strengthen competences for business and social innovation in the Danube region by establishing a structured transnational cooperation and a common transnational platform for monitoring and forecasting changes in the labour market due to the increasing penetration of artificial intelligence (AI) technologies.
    To make the data about the labour market trends in regard to AI technologies penetration available to all socio-economic stakeholders by establishing a common transnational platform for monitoring and forecasting.
    To open new job opportunities to meet social needs of individual employees affected by AI technologies penetration by providing them with relevant professional training and retraining
    To intensify the cooperation of key actors ( e.g. businesses, business associations, educational institutions, R&D structures, employment agencies, trade unions, labour market organisations) by establishing a transnational network.

    Main results and core outputs

    The main result will be increased competences of individuals and stakeholders to adapt to the fast changes of the labour market caused by AI technologies penetration.
    By learning to identify, understand and forecast trends in the labour market caused by AI technologies spread the project stakeholders will be able to better respond to societal challenges and needs in the region shaping, and when necessary, adapting their approach to provide relevant innovative learning systems.
    Main outputs:
    • Survey of the current status of the penetration of AI technologies in project countries;
    • Methodology for monitoring, evaluating and forecasting changes in the labour market caused by penetration of AI technologies;
    • Common transnational platform for monitoring and forecasting changes in the labour market due to the increasing penetration of AI technologies;
    • Transnational network for exchange of experience and knowledge transfer for providing innovative learning systems

    Main foreseen activities

    • Conduction of national surveys of the current status of the penetration of artificial intelligence (AI) technologies in each project partner country;
    • Elaboration of common methodology for monitoring, evaluating and forecasting changes in the labour market caused by penetration of artificial intelligence (AI) technologies
    • Creation of Common transnational platform for monitoring and forecasting changes in the labour market due to the increasing penetration of artificial intelligence (AI) technologies
    • Establishing of Transnational network for exchange of experience and knowledge transfer for providing innovative learning systems (e.g. training and retraining schemes for professionals)
    • Organisation of workshops and trainings for the relevant stakeholders, including opening and closing conferences.

    Innovative character of the project idea

    The monitoring and forecasting of the trends and changes of the labour marked caused by the AI technologies penetration is a innovative approach not only for the Danube region but also for the EU and it is a recommended measure by the European Commission in its latest documents.

    Estimated Total Budget
    (in EUR)

    EUR 2 100 000

    Estimated duration
    (in months)

    30

  • Partners involved at this stage

    ERDF Partners

    -

    IPA Partners

    -

    Associated Strategic Partners

    -

  • Partners requested

    ERDF Partners

    Business and branch associations, educational institutions, organisations with digital competences and experience in AI, policy makers, trade unions, labour market organisations, NGOs, industry representatives, SMEs., R&D structures, employment agencies

    IPA Partners

    Business and branch associations, educational institutions, organisations with digital competences and experience in AI, policy makers, trade unions, labour market organisations, NGOs, R&D structures, employment agencies

    Associated Strategic Partners

    Business and branch associations, educational institutions, organisations with digital competences and experience in AI, policy makers, trade unions, labour market organisations, NGOs, R&D structures, employment agencies

  • Contact Person

    Name

    Liliya Georgieva

    Address

    86, Vitosha bld

    Country

    Bulgaria

    Telephone number

    E-mail address

    Is the applicant the project's potential Lead Partner?

    If not, is the potential Lead Partner already being chosen?

Programme co-funded by European Union funds (ERDF, IPA, ENI)