Global Perspectives on AI Competence Development: Analyzing National AI Strategies in Education and Workforce Policies

Abstract

Advancements in artificial intelligence (AI) signal a significant shift toward more automated and data-driven workplaces, emphasizing the need for Human Resource Development (HRD) to prepare the workforce with adequate AI competencies for AI-empowered environments. AI policies and initiatives play a crucial role in providing the frameworks and actions that guide HRD efforts. In this study, we analyzed education and workforce policies in national AI strategies (NAISs) from 50 countries to delineate educational policy priorities, strategies, and support resources for developing an AI-competent workforce. Our analysis revealed that only 13 countries demonstrated high-level prioritization with clear objectives and comprehensive measures, primarily developed economies in Europe. We identified six categories of educational and training strategies focused on AI talent preparation and workforce reskilling. Additionally, four types of support resources were highlighted as key investments to enhance the success of these educational and training strategies. The findings have significant implications for HRD practice, particularly in designing and implementing AI-focused, workplace-oriented, and inclusive HRD curricula, programs, and policies that consider contextual and cultural factors. The results suggest the need for further HRD education research to explore emerging theories, AI workforce training models, pedagogical strategies, and the impact of contextual and cultural elements on workforce competency development.

Keywords

artificial intelligence national AI strategies workforce AI competencies human resource development

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References

Acemoglu

Restrepo

(2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188–2244. https://doi.org/10.1086/705716

Agrawal

Gans

J. S.

Goldfarb

(2019). Exploring the impact of artificial intelligence: Prediction versus Judgment. Information Economics and Policy, 47(1), 1–6. https://doi.org/10.1016/j.infoecopol.2019.05.001

Beebeejaun

Gunputh

R. P.

(2023). A study of the influence of artificial intelligence and its challenges: The impact on employees of the legal sector of Mauritius. Global Business Review, Article, 09721509231193803. https://doi.org/10.1177/09721509231193803

Benešová

Tupa

(2017). Requirements for education and qualification of people in Industry 4.0. Procedia Manufacturing, 11(2017), 2195–2202. https://doi.org/10.1016/j.promfg.2017.07.366

Bessen

(2019). Artificial intelligence and jobs: The role of demand. In The economics of artificial intelligence: An agenda (pp. 291–307). University of Chicago Press.

Bogoslov

I. A.

Corman

Lungu

A. E.

(2024). Perspectives on artificial intelligence adoption for European union elderly in the context of digital skills development. Sustainability, 16(11), 4579. https://doi.org/10.3390/su16114579

Bughin

Hazan

Lund

Dahlström

Wiesinger

Subramaniam

(2018). Skill shift: Automation and the future of the workforce. McKinsey Global Institute, 1(2018), 3–84.

Cachat-Rosset

Klarsfeld

(2023). Diversity, equity, and inclusion in artificial intelligence: An evaluation of guidelines. Applied Artificial Intelligence, 37(1), Article 2176618. https://doi.org/10.1080/08839514.2023.2176618

Daly

Hagendorff

Mann

Marda

Wagner

Wang

Witteborn

(2019). AI, governance and ethics: Global perspectives. Social Science Research Network.

10.

Deranty

J. P.

Corbin

(2022). AI and work: A critical review of recent research from the social sciences (pp. 1–17). AI & Society.

11.

Dexe

Franke

(2020). Nordic lights? National AI policies for doing well by doing good. Journal of Cyber Policy, 5(3), 332–349. https://doi.org/10.1080/23738871.2020.1856160

12.

Ding

A. C. E.

Shi

Yang

Choi

(2024). Enhancing teacher AI literacy and integration through different types of cases in teacher professional development. Computers and Education Open, 6, Article 100178. https://doi.org/10.1016/j.caeo.2024.100178

13.

Djeffal

Siewert

M. B.

Wurster

(2022). Role of the state and responsibility in governing AI: A comparative analysis of AI strategies. Journal of European Public Policy, 29(11), 1799–1821. https://doi.org/10.1080/13501763.2022.2094987

14.

Dondi

Klier

Panier

Schubert

(2021) Defining the skills citizens will need in the future world of work (Vol. 25, p. 2021). McKinsey & Company.

15.

Ekuma

(2024). Artificial intelligence and automation in human resource development: A systematic review. Human Resource Development Review, 23(2), 199–229. https://doi.org/10.1177/15344843231224009

16.

Engstrom

D. F.

D. E.

Sharkey

C. M.

Cuéllar

M. F.

(2020). Government by algorithm: AI in federal administrative agencies. NYU School of Law, Public Law Research Paper, pp. 20–54.

17.

European Commission . (2018). Coordinated plan on artificial intelligence.

18.

European Commission

(2022). Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators. Publications Office of the European Union.

19.

Fatima

Desouza

K. C.

Dawson

G. S.

(2020). National strategic AI plans: A multi-dimensional analysis. Economic Analysis and Policy, 67, 178–194. https://doi.org/10.1016/j.eap.2020.07.008

20.

Frey

C. B.

Osborne

M. A.

(2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019

21.

Gallardo-Gallardo

Collings

D. G.

(2021). Talent management for the future of work. In New directions in the future of work (pp. 35–54). Emerald Publishing Limited.

22.

Gianecchini

Caterina

Campagnolo

(2018). Digital revolution equals digital competencies? What we expect for workers’ competencies in industry 4.0. In Human resource management and digitalization. The effects of industry 4.0 on human resource. Giappichelli Routledge.

23.

Grover

Pea

(2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38–43. https://doi.org/10.3102/0013189x12463051

24.

Guenduez

A. A.

Mettler

(2023). Strategically constructed narratives on artificial intelligence: What stories are told in governmental artificial intelligence policies? Government Information Quarterly, 40(1), Article 101719. https://doi.org/10.1016/j.giq.2022.101719

25.

Guo

Zheng

Zhai

(2024). Artificial intelligence in education research during 2013–2023: A review based on bibliometric analysis. Education and Information Technologies, 29(13), 1–23. https://doi.org/10.1007/s10639-024-12491-8

26.

Hjaltalin

I. T.

Sigurdarson

H. T.

(2024). The strategic use of AI in the public sector: A public values analysis of national AI strategies. Government Information Quarterly, 41(1), Article 101914. https://doi.org/10.1016/j.giq.2024.101914

27.

Hoffmann

(1999). The meanings of competency. Journal of European Industrial Training, 23(6), 275–286. https://doi.org/10.1108/03090599910284650

28.

Jarrahi

M. H.

(2018). AI and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586. https://doi.org/10.1016/j.bushor.2018.03.007

29.

Lang

(2023). Workforce upskilling: Can universities meet the challenges of lifelong learning? The International Journal of Information and Learning Technology, 40(5), 388–400. https://doi.org/10.1108/ijilt-01-2023-0001

30.

Latif

Zhou

Guo

Gao

Shi

Nayaaba

Zhai

(2024). A systematic assessment of OpenAI o1-preview for higher order thinking in education. arXiv preprint arXiv:2410.21287.

31.

Lee

G. G.

Shi

Latif

Gao

Bewersdorf

Nyaaba

Zhai

(2023). Multimodality of AI for education: Towards artificial general intelligence. arXiv preprint arXiv:2312.06037.

32.

Lee

V. R.

Wilkerson

M. H.

Lanouette

(2021). A call for a humanistic stance toward K–12 data science education. Educational Researcher, 50(9), 664–672. https://doi.org/10.3102/0013189x211048810

33.

Liu

Tian

Kim

Serikawa

(2019). The cognitive internet of vehicles for autonomous driving. IEEE Network, 33(3), 65–73. https://doi.org/10.1109/mnet.2019.1800339

34.

Mahood

Van Eerd

Irvin

(2014). Searching for grey literature for systematic reviews: Chal- lenges and benefits. Research Synthesis Methods, 5(3), 221–234. https://doi.org/10.1002/jrsm.1106

35.

Manyika

Chui

Miremadi

Bughin

George

Willmott

Dewhurst

(2017b). A future that works: AI, automation, employment, and productivity. McKinsey Global Institute Research, 60, 1–135.

36.

Manyika

Lund

Chui

Bughin

Woetzel

Batra

Sanghvi

(2017a). Jobs lost, jobs gained: Workforce transitions in a time of automation. McKinsey Global Institute, 150(1), 1–148.

37.

Mei

Feng

Cavallaro

(2023). Evaluate and identify the competencies of the future workforce for digital technologies implementation in higher education. Journal of Innovation & Knowledge, 8(4), Article 100445. https://doi.org/10.1016/j.jik.2023.100445

38.

Mikalef

Lemmer

Schaefer

Ylinen

Fjørtoft

S. O.

Torvatn

H. Y.

Niehaves

(2022). Enabling AI capabilities in government agencies: A study of determinants for European municipalities. Government Information Quarterly, 39(4), Article 101596. https://doi.org/10.1016/j.giq.2021.101596

39.

Muzam

(2023). The challenges of modern economy on the competencies of knowledge workers. Journal of the Knowledge Economy, 14(2), 1635–1671. https://doi.org/10.1007/s13132-022-00979-y

40.

OPSI . (2020). AI Strategies & public sector components. https://oecd-opsi.org/projects/ai/strategies/ (Accessed 10 October 2023).

41.

Organization for Economic Cooperation and Development . (2019). AI in society. https://doi.org/10.1787/eedfee77-en

42.

Parry

S. B.

(1996). Just what is a competency?(and why should you care?). Training, 35(6), 58.

43.

Radu

(2021). Steering the governance of artificial intelligence: National strategies in perspective. Policy and society, 40(2), 178–193. https://doi.org/10.1080/14494035.2021.1929728

44.

Rampersad

(2020). Robot will take your job: Innovation for an era of artificial intelligence. Journal of Business Research, 116, 68–74. https://doi.org/10.1016/j.jbusres.2020.05.019

45.

Randstad . (2024). AI skills gap widens: 71% of AI talent are men, while only 22% of baby boomers receive training - reveals Randstad data. https://www.randstad.com/press/2024/ai-skills-gap-widens/

46.

Rasdi

R. M.

Idris

F. H.

Krauss

S. E.

Omar

M. K.

(2024). Exploring artificial intelligence competencies for the future workforce: A systematic literature review using the PRISMA protocol. In Human factors and ergonomics Malaysia biennial conference (pp. 189–204). Springer.

47.

Robinson

S. C.

(2020). Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI). Technology in Society, 63, Article 101421. https://doi.org/10.1016/j.techsoc.2020.101421

48.

Saheb

(2023). Topical review of AI national policies: A mixed method analysis. Technology in Society, 74, Article 102316. https://doi.org/10.1016/j.techsoc.2023.102316

49.

Santana

Díaz-Fernández

(2023). Competencies for the AI age: Visualisation of the state of the art and future perspectives. Review of Managerial Science, 17(6), 1971–2004. https://doi.org/10.1007/s11846-022-00613-w

50.

Schiff

(2022). Education for AI, not AI for education: The role of education and ethics in national AI policy strategies. International Journal of Artificial Intelligence in Education, 32(3), 527–563. https://doi.org/10.1007/s40593-021-00270-2

51.

Schreier

(2012). Qualitative content analysis in practice. (pp. 1–280). Sage.

52.

Schwab

(2017). The fourth industrial revolution. Crown Currency.

53.

Shah

(2023). AI and the future of education: Teaching in the age of artificial intelligence. John Wiley & Sons.

54.

Shi

Choi

(2024). A systematic review of artificial intelligence in supporting teaching practice: Application types, pedagogical roles, and technological characteristics. In Zhai

Krajcik

(Eds.), Uses of artificial intelligence in STEM education (pp. 321–347). Oxford Academic.

55.

Strack

Carrasco

Kolo

Nouri

Priddis

George

(2021). The future of jobs in the era of AI. Boston Consulting Group.

56.

Swanson

R. A.

(2022). Foundations of human resource development. Berrett-Koehler Publishers.

57.

Tian

Shen

Wei

Liu

(2023). The application of artificial intelligence in medical diagnostics: A new frontier. Academic Journal of Science and Technology, 8(2), 57–61. https://doi.org/10.54097/ajst.v8i2.14945

58.

Toll

Lindgren

Melin

Madsen

C. Ø.

(2020). Values, benefits, considerations and risks of AI in government: A study of AI policy documents in Sweden. eJournal eDemocracy Open Gov.

59.

Trakadas

Simoens

Gkonis

Sarakis

Angelopoulos

Ramallo-González

A. P.

Skarmeta

Trochoutsos

Calvο

Pariente

Chintamani

Fernandez

Irigaray

A. A.

Parreira

J. X.

Petrali

Leligou

Karkazis

(2020). An AI-based collaboration approach in industrial manufacturing: Key concepts, architectural extensions and potential applications. Sensors, 20(19), 5480. https://doi.org/10.3390/s20195480

60.

United Nations Department of Economic and Social Affairs . (2023). World economic situation and prospects 2023. https://desapublications.un.org/publications/world-economic-situation-and-prospects-2023

61.

van Noordt

Medaglia

Tangi

(2023). Policy initiatives for AI-enabled government: An analysis of national strategies in Europe. Public Policy and Administration, Article 09520767231198411. https://doi.org/10.1177/09520767231198411

62.

World Economic Forum J . (2020). The future of jobs report 2020.

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