{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2026-11-05","version":"1"},"project_desc":{"authoring_entity":[{"name":"Maddalena Honorati","affiliation":"World Bank","email":"mhonorati@worldbank.org"},{"name":"Piotr Lewandowski","affiliation":"IBS","email":"piotr.lewandowski@ibs.org.pl"},{"name":"Karol Mado\u0144","affiliation":"IBS","email":"karol.madon@ibs.org.pl"}],"title_statement":{"title":"Reproducibility package for Poland in the Age of Artificial Intelligence:  Is the Workforce Ready?","idno":"RR_POL_2026_707"},"data_statement":"The reproducibility package relies on open, limited-access and restricted data. For the source, access type, file location, and citation of each dataset, refer to the Datasets section and the README file.","software":[{"name":"Stata","version":"19.5 MP"}],"scripts":[{"title":"Reproducibility package for Poland in the Age of Artificial Intelligence: Is the Workforce Ready?","date":"2026-11","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_POL_2026_707","zip_package":"RR_POL_2026_707.zip","dependencies":"Stata dependencies are listed in the ado folder."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2026-11-05","abstract":"This paper documents the incidence and characteristics of workers\u2019 exposure to AI in Poland compared to other countries and examines the potential barriers that could limit workers\u2019 realized productivity gains. Polish workers are less exposed to AI compared to US and European workers and that the exposure gap is primarily driven by workers\u2019 lower use of computers at work. Second, when looking at workers\u2019 readiness to effectively adopt AI technologies, we find that Polish workers have lower transversal and cognitive skills (assumed to be complementary to AI) than comparator countries and have less opportunities to participate in upskilling and reskilling initiatives. The cross-country skill gap is significantly higher among AI exposed workers. Consistently, Polish workers report substantially higher perceived needs for digital skills training than comparable workers in other countries. However, workers\u2019 awareness of skill gaps is not uniform: it is high among more educated and younger workers, while not significant among older workers. Third, we do not find any systematic relationship between occupational exposure to AI and existing labor shortages in Poland. AI could mitigate existing labor shortages for legal, social and cultural professionals. Finally, the paper provides a framework to guide social protection, skills and employment policies to address AI-driven job displacement and equip workers with skills complementary to AI. We contribute to the literature on measuring workers\u2019 exposure to AI by comparing alternative task-based measures of AI-exposure and validating the AI exposure metrics against self-reported use of generative AI tools at work in Poland. ","geographic_units":[{"name":"Poland","code":"POL"}],"keywords":[{"name":"Artificial Intelligence"},{"name":"Poland"},{"name":"Ai Exposure"},{"name":"Labor Markets"},{"name":"Productivity"},{"name":"Skills"},{"name":"Task-Based Approach"}],"topics":[{"id":"J21","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Labor Force and Employment, Size, and Structure","parent_id":"J2"},{"id":" J23","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Labor Demand","parent_id":"J2"},{"id":" J24","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Human Capital \u2022 Skills \u2022 Occupational Choice \u2022 Labor Productivity","parent_id":"J2"},{"id":" O33","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Technological Change: Choices and Consequences \u2022 Diffusion Processes","parent_id":"O3"},{"id":" O47","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Empirical Studies of Economic Growth \u2022 Aggregate Productivity \u2022 Cross-Country Output Convergence","parent_id":"O4"}],"output":[{"type":"Working Paper","description":"Policy Research Working Paper (PRWP)","title":"Poland in the Age of Artificial Intelligence: Is the Workforce Ready?"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"Run time: ~30 minutes","disclaimer":"The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development\/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.","license":[{"name":"MIT License","uri":"https:\/\/opensource.org\/license\/mit"},{"name":"World Bank IGO Rider","uri":"https:\/\/github.com\/worldbank\/metadata-editor\/blob\/main\/WB-IGO-RIDER.md"}],"contacts":[{"name":"Maddalena Honorati","affiliation":"World Bank","email":"mhonorati@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"Programme for the International Assessment of Adult Competencies (PIAAC), Survey of Adult Skills, Cycles 1 and 2","note":"Filename: data\/raw_piaac1\/prg<cc>p1.dta (bel, cze, deu, dnk, esp, est, fin, fra, gbr, grc, hun, irl, isr, ita, ltu, nld, nor, pol, svk, svn, swe); data\/raw_piaac1\/SUF_PIAAC_STAT_AUT_NEU.dta; data\/raw_piaac1\/piaac_cyp.dta; data\/raw_piaac2\/prgpolp2.dta. Individual-level OECD survey data on adult literacy, numeracy and problem-solving skills and on task use at work. For more details, refer to the README file.","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","license":"PIAAC Remote Code Execution (RCE) Service Terms of Use","license_uri":"https:\/\/www.oecd.org\/content\/dam\/oecd\/en\/about\/programmes\/edu\/piaac\/data-materials\/cycle-2\/piaac-rce-service-terms-of-use.pdf","citation":"OECD. (2025). Survey of Adult Skills (PIAAC) [dataset]. Organisation for Economic Co-operation and Development. https:\/\/www.oecd.org\/en\/about\/programmes\/piaac\/piaac-data.html. Accessed February 2025.","uri":"https:\/\/www.oecd.org\/en\/about\/programmes\/piaac\/piaac-data.html"},{"name":"European Skills and Jobs Survey, Wave 2 (ESJS2), 2021","note":"Filename: data\/cedefop\/CEDEFOP_ESJS2_v13.dta. Individual-level survey of adult workers in the European Union on skills, digitalisation and training needs, produced by the European Centre for the Development of Vocational Training (Cedefop). Access requires submitting the request form at https:\/\/www.cedefop.europa.eu\/en\/access-microdata, stating the research purpose, organisation and planned analyses; a download link is sent by email on approval. For more details, refer to the README file.","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","citation":"Cedefop. (2021). Cedefop second European skills and jobs survey (1st edition) [dataset]. European Centre for the Development of Vocational Training. https:\/\/www.cedefop.europa.eu\/en\/projects\/european-skills-and-jobs-survey-esjs. Accessed May 2025.","uri":"https:\/\/www.cedefop.europa.eu\/en\/datasets\/dataset-european-skills-and-jobs-survey-2021-wave-2"},{"name":"European Union Labour Force Survey (EU-LFS), 2022","note":"Filename: data\/raw_lfs\/<cc>2022_y.dta (at, be, bg, ch, cy, cz, de, dk, ee, el, es, fi, fr, hr, hu, ie, is, it, lt, lu, lv, mt, nl, no, pl, pt, ro, se, si, sk). Annual individual-level Eurostat labour force microdata for 2022, including the job skills module. Access requires the replicator's organisation to be recognised as a research entity by Eurostat, followed by a research proposal through the Eurostat Microdata Access Portal for Scientific Use Files. For more details, refer to the README file.","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","license":"Eurostat microdata access agreement (Commission Regulation (EU) No 557\/2013)","license_uri":"https:\/\/ec.europa.eu\/eurostat\/documents\/203647\/771732\/How_to_apply_for_microdata_access.pdf","citation":"Eurostat. (2022). European Union Labour Force Survey (EU-LFS), annual microdata 2022 [dataset]. European Commission. https:\/\/ec.europa.eu\/eurostat\/web\/microdata\/access. Accessed April 2025.","uri":"https:\/\/ec.europa.eu\/eurostat\/web\/microdata\/access"},{"name":"System for Forecasting the Polish Labour Market","note":"Filename: outputs\/Figures_3_4_11_A1.xlsx (sheet Figure_11). Forecast occupational labour shortages and surpluses for Poland in 2040 (baseline scenario), produced for the Ministry of Family, Labour and Social Policy. The forecast values have been removed from the sheet because the data cannot be redistributed: the sheet retains the occupation codes and labels, and a replicator must rebuild the forecast columns from the source before Figure 11 can be reproduced. Access requires an account approved by the Ministry. To extract the data: log in, choose \"Modu\u0142 prognostyczny\" in the left panel, then \"scenariusz bazowy\"; in \"wybierz przekr\u00f3j\" select \"zawodowy\", in \"wybierz kategorie\" select \"Luka\", in \"Wybierz rodzaj grupy KZiS\" select \"\u015brednia\", in \"Zaw\u00f3d\" select all ISCO codes, select \"2040\" in \"Rok\", click \"poka\u017c wyniki\" and then \"zapisz\" under the table.","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","citation":"IBS, IPiSS and University of \u0141\u00f3d\u017a. (2022). System for Forecasting the Polish Labour Market [dataset]. Ministry of Family, Labour and Social Policy. https:\/\/prognozy.praca.gov.pl. Accessed April 2025.","uri":"https:\/\/prognozy.praca.gov.pl"},{"name":"World Bank Enterprise Surveys","note":"Filename: data\/other\/WBES_data.dta. Indicators built by the authors from the Formal Sector Enterprise Surveys microdata: share of firms with their own website (c22b), share using technology licensed from foreign companies (e6) and share with an internationally recognised quality certificate (b8), collapsed (mean) by country, year and industry (a4a). Merged into the regression dataset as impute_firms_website, impute_firms_foreign_tech and impute_firms_certificate (script 1_3_Table_3_data_prep). The underlying microdata require free registration through the Enterprise Surveys Data Access Protocol.","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","license":"World Bank Enterprise Surveys Data Access Protocol","license_uri":"https:\/\/login.enterprisesurveys.org\/en\/terms","citation":"World Bank. (2025). Enterprise Surveys [dataset]. World Bank Group. https:\/\/www.enterprisesurveys.org\/en\/data. Accessed June 2025.","uri":"https:\/\/www.enterprisesurveys.org\/en\/data"},{"name":"World Development Indicators","note":"Filename: data\/other\/macro_wbi.dta. Log of GDP per capita, PPP (current international $) (NY.GDP.PCAP.PP.CD), averaged over 2011\u20132016 for PIAAC Cycle 1 countries and over 2021\u20132022 for PIAAC Cycle 2. Merged into the PIAAC analysis datasets as a country-level control. ","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","citation":"World Bank. (2024). World Development Indicators [dataset]. World Bank Group. https:\/\/databank.worldbank.org\/source\/world-development-indicators. Accessed August 2024.","uri":"https:\/\/databank.worldbank.org\/source\/world-development-indicators"},{"name":"World Development Report 2020 Global Value Chain Data (EORA26 variant)","note":"Filename: data\/other\/EORA_piaac_yearly.dta; data\/other\/EORA_piaac_yearly_1d.dta. Country-sector global value chain participation measures (forward and backward participation, variables gvcfsh and gvcsf) from the WDR 2020 database, based on the EORA26 multi-region input-output tables and the methodology of Borin and Mancini (2019).\nSecondary citations: Borin, A. and Mancini, M. 2019. Measuring What Matters in Global Value Chains and Value-Added Trade. Policy Research Working Paper 8804, WDR 2020 Background Paper. Washington, DC: World Bank Group. https:\/\/doi.org\/10.1596\/1813-9450-8804.\nBorin, A. and Mancini, M. 2015. Follow the value added: bilateral gross export accounting. Banca d\u2019Italia, Temi di Discussione 1026.\nLenzen, M., Moran, D., Kanemoto, K. and Geschke, A. 2013. Building Eora: a global multi-region input-output database at high country and sector resolution. Economic Systems Research 25(1), 20\u201349. https:\/\/doi.org\/10.1080\/09535314.2013.769938.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","citation":"World Bank. (2020). WDR 2020 Global Value Chain data [dataset]. World Development Report 2020: Trading for Development in the Age of Global Value Chains. Washington, DC: World Bank. https:\/\/thedocs.worldbank.org\/en\/doc\/596971582220071531-0050022020\/WDR2020-GVC-data. Accessed March 2022.","uri":"https:\/\/thedocs.worldbank.org\/en\/doc\/596971582220071531-0050022020\/WDR2020-GVC-data"},{"name":"Workers' AI Exposure Across Development Levels","note":"Filename: data\/Figure_A2_data.dta; data\/other\/ai_exposure_lewandowski.dta; data\/other\/ai_exposure_long.dta; data\/other\/ai_exposure_lewandowski_europe.dta","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","citation":"Lewandowski, P., Mado\u0144, K. and Park, A. (2025). Workers' AI Exposure Across Development Levels, replication package [dataset]. IZA Discussion Paper No. 18235. IZA \u2013 Institute of Labor Economics. https:\/\/piotr-lewandowski.pl\/code_database\/replication-package-for-workers-exposure-to-ai-across-development-stages\/. Accessed June 2026.","uri":"https:\/\/piotr-lewandowski.pl\/code_database\/replication-package-for-workers-exposure-to-ai-across-development-stages\/"},{"name":"AI Occupational Exposure (AIOE) and underlying ability scores","note":"Filename: data\/other\/AIOE_Felten_isco_1d.dta; data\/other\/AIOE_Felten_isco_2d.dta; data\/other\/abilities_by_isco_1d.dta; data\/other\/abilities_by_isco_2d.dta; data\/other\/ability_base_isco_1d.dta; data\/other\/ability_base_isco_2d.dta; data\/other\/_binary_all.dta. Occupational AI exposure scores and the ability-level data they are built from, mapped to ISCO-08 1-digit and 2-digit occupations.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","citation":"Felten, E., Raj, M. and Seamans, R. (2021). AI Occupational Exposure (AIOE) data [dataset]. https:\/\/github.com\/AIOE-Data\/AIOE. Accessed August 2024.","uri":"https:\/\/github.com\/AIOE-Data\/AIOE"},{"name":"Generative AI and jobs: A refined global index of occupational exposure","note":"Filename: data\/other\/Final_Scores_Gmyrek_et_al_2025.dta; data\/other\/adoption_isco1d.dta. Occupational generative AI exposure scores by 4-digit ISCO-08 occupation from the International Labour Organization, obtained from the authors of the study on request; the scores are also published in Table A1 of Annex 1 of the ILO working paper. Contact for requests: gmyrek@ilo.org. Accessed 2026-01.","access_type":"Data access was granted directly to the study authors by the data owners\/managers. It was obtained with a custom data license that does not allow for redistribution and it is not included in the reproducibility package.","citation":"Gmyrek, P., Berg, J., Kami\u0144ski, K., Konopczy\u0144ski, F., \u0141adna, A., Nafradi, B., Ros\u0142aniec, K. and Troszy\u0144ski, M. (2025). Generative AI and jobs: A refined global index of occupational exposure [dataset]. ILO Working Paper 140. Geneva: International Labour Organization. https:\/\/doi.org\/10.54394\/HETP0387. Accessed January 2026."},{"name":"Employment by Sex and Occupation, ISCO-08 2-digit and 1-digit","note":"Filename: data\/other\/EMP_weights_p1.dta; data\/other\/EMP_weights_isco1d_p1.dta. Employment by occupation (thousands) used as weights to aggregate occupation-level measures (variables emp and emp_total, merged in script 1_3_Table_3_data_prep). Each country has one reference year (2010, 2012 or 2013). The files also contain ln_gdp_2011 and country_group, which match the Lewandowski, Mado\u0144 and Park (2025) replication package and are not used by the code.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/www.ilo.org\/rights-and-permissions#data","citation":"International Labour Organization. (2026). ILOSTAT database: Employment by sex and occupation \u2013 ISCO level 2 \u2013 19th ICLS (thousands) \u2013 Annual [dataset]. Geneva: ILO. https:\/\/ilostat.ilo.org\/. Accessed February 2026.","uri":"https:\/\/ilostat.ilo.org\/"},{"name":"Social Skill Indices by Country and Occupation","note":"Filename: data\/other\/country_level_SOCIAL_SKILLS_piaac_and_deming_ISCO3d.dta.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","citation":"Lewandowski, P. and Mado\u0144, K. (2026). Drivers of skill use at work (Deliverable 4.1) [dataset]. SkiLMeeT, Grant agreement no. 101132581. https:\/\/skilmeet.eu\/publications\/. Accessed June 2026.","uri":"https:\/\/skilmeet.eu\/publications\/"},{"name":"International Organization for Standardization (ISO) 3166 Country Identifiers Mapping","note":"Filename: data\/other\/countries_iso_more_countries.dta. Crosswalk between country names and ISO 3166 country codes.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/","citation":"Mado\u0144, K. (2026). ISO 3166 country identifiers mapping [dataset]. Zenodo. https:\/\/doi.org\/10.5281\/zenodo.22796417. Accessed September 2026.","uri":"https:\/\/zenodo.org\/records\/22796417"},{"note":"File location: data\/other\/country_level_SOCIAL_SKILLS_piaac_and_deming_ISCO3d.dta (variables social_skills_std_us, social_skills_std). O*NET occupational ability data, obtained through the replication package of Deming (2017), are used to construct the Social Skills Index. The underlying data are produced by O*NET, U.S. Department of Labor, Employment and Training Administration (USDOL\/ETA).","name":"Occupational Information Network (O*NET)","access_type":"Data is publicly available and included in the reproducibility package.\n","license":"Creative Commons Zero v1.0 Universal (CC0 1.0)","license_uri":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/","uri":"https:\/\/doi.org\/10.7910\/DVN\/CYPKZH","citation":"Deming, David. 2017. \"Replication Data for: The Growing Importance of Social Skills in the Labor Market\" [dataset]. Harvard Dataverse, V1. https:\/\/doi.org\/10.7910\/DVN\/CYPKZH. Accessed February 2025."}],"reproduction_instructions":"To reproduce the findings in this paper, a replicator must:\n1. **Secure Access to Data:** Access the datasets not included in the package. See the Datasets section for more details.\n2. **Run the Package:**\n  - Update the working directory in line 13 of the do-file `main`, and run it.\n\nSince not all the data is included, the package includes the results produced by replicators. These files can be used to review the results presented in the paper.\n","technology_environment":" Paper exhibits were reproduced on a computer with the following specifications:\n - OS: Windows 11\n - Processor:  Intel Core i7-11850H (2.50 GHz)\n - Memory: 32.0 GB"},"datacite":{"creators":[{"givenName":"Maddalena","familyName":"Honorati","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Piotr","familyName":"Lewandowski","nameType":"Personal","affiliation":[{"name":"IBS","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Karol","familyName":"Mado\u0144","nameType":"Personal","affiliation":[{"name":"IBS","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]}],"titles":[{"lang":"en","title":"Reproducibility package for Poland In The Age Of Artificial Intelligence: Is The Workforce Ready"},{"title":"RR_POL_2026_707","titleType":"Other"}],"publisher":"World Bank","publicationYear":"2026","types":{"resourceType":"Reproducibility package","resourceTypeGeneral":"Other"},"url":"https:\/\/reproducibility.worldbank.org\/index.php\/catalog\/study\/RR_POL_2026_707","language":"en"},"tags":[{"tag":"DOI"},{"tag":"Open Code"},{"tag":"Restricted Data"}],"schematype":"script"}