Sage Journals: Discover world-class research

Abstract

Artificial intelligence (AI) is increasingly embedded in entrepreneurial activity across emerging economies, reshaping how small and medium-sized enterprises (SMEs) identify opportunities, mobilise resources and participate in innovation ecosystems. Yet existing work remains fragmented, with limited attention to how AI interacts with contextual features such as institutional voids, infrastructural constraints and policy experiments that characterise emerging economies. This study conducts a bibliometric and systematic literature review (BSLR) to map the intellectual structure and thematic evolution of research at the intersection of AI, entrepreneurship and innovation, and develops a multi-level conceptual framework that explains how AI operates as a cognitive, organisational and institutional actor within entrepreneurial ecosystems in these contexts. Synthesising 100 peer-reviewed articles published between 2017 and 2025, the article identifies four interrelated thematic domains: AI-augmented entrepreneurial cognition and decision-making; digitally mediated venture formation and learning processes; adaptive ecosystem structures, skills and resource orchestration; and institutional governance of intelligent technologies. The framework shows how AI-enabled tools can help entrepreneurs navigate uncertainty, extend their reach into digital markets and experiment with new business models, while also raising substantive concerns about algorithmic exclusion, bias and dependence on external platforms that constitute new forms of institutional inequality in emerging economy ecosystems. The study additionally identifies three emergent thematic frontiers requiring dedicated future inquiry: agentic AI and autonomous entrepreneurial action, AI and sustainability-oriented innovation, and ethical and responsible AI governance in resource-constrained regulatory environments. By situating AI-augmented entrepreneurship within the specific resource, relational and institutional conditions of emerging economies, the article contributes to debates on institutional evolution, regional development, and sustainable and inclusive innovation. It offers implications for policymakers, ecosystem builders and support organisations on how to design AI-related policies, infrastructures and capacity-building initiatives that strengthen local entrepreneurial ecosystems rather than deepen existing disparities, and outlines a future research agenda to examine these dynamics empirically across diverse emerging-country settings.

Keywords

Artificial intelligence emerging economies entrepreneurial ecosystems digital transformation

Get full access to this article

View all access options for this article.

References

Aria

, & Cuccurullo

(2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics , 11(4), 959–975.

Autio

, Kenney

, Mustar

, Siegel

, & Wright

(2014). Entrepreneurial innovation: The importance of context. Research Policy , 43(7), 1097–1108.

Autio

, Nambisan

, Thomas

L. D. W.

, & Wright

(2018). Digital affordances, spatial affordances, and the genesis of entrepreneurial ecosystems. Strategic Entrepreneurship Journal , 12(1), 72–95.

Birhane

(2021). Algorithmic injustice: A relational ethics approach. Patterns , 2(2), 100205.

Bruton

G. D.

, Ahlstrom

, & Li

H. L.

(2010). Institutional theory and entrepreneurship: Where are we now and where do we need to move in the future? Entrepreneurship Theory and Practice , 34(3), 421–440.

Brynjolfsson

, & McAfee

(2017). Machine, platform, crowd: Harnessing our digital future . W. W. Norton and Company.

Cockburn

I. M.

, Henderson

, & Stern

(2018). The impact of artificial intelligence on innovation. In The economics of artificial intelligence: An agenda (pp. 115–146). University of Chicago Press.

Cope

(2011). Entrepreneurial learning from failure: An interpretative phenomenological analysis. Journal of Business Venturing , 26(6), 604–623.

Davidsson

, & Wiklund

(2001). Levels of analysis in entrepreneurship research: Current practice and suggestions for the future. Entrepreneurship Theory and Practice , 25(4), 81–100.

10.

Donthu

, Kumar

, Mukherjee

, Pandey

, & Lim

W. M.

(2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research , 133, 285–296.

11.

, Almirall

, & Wareham

(2023). A typology of artificial intelligence affordances for innovation: A review and research agenda. Technological Forecasting and Social Change , 186, 122145.

12.

Falcke

, Zobel

A. K.

, Yoo

, & Tucci

(2024). Digital sustainability strategies: Digitally enabled and digital-first innovation for net zero. Academy of Management Perspectives , 38(3), 398–421.

13.

Faraj

, Pachidi

, & Sayegh

(2018). Working and organizing in the age of the learning algorithm. Information and Organization , 28(1), 62–70.

14.

Felin

, Koenigsberg

, & Lane

P. J.

(2022). Toward AI-augmented entrepreneurship: Reconfiguring entrepreneurial judgment and decision-making. Academy of Management Perspectives , 36(4), 783–800.

15.

Filatotchev

, Aguilera

R. V.

, & Wright

(2020). From governance of innovation to innovations in governance. Academy of Management Perspectives , 34(2), 173–181.

16.

Gatrell

, Muzio

, Post

, & Wickert

(2024). Here, there and everywhere: On the responsible use of artificial intelligence (AI) in management research and the peer-review process. Journal of Management Studies , 61(3), 739–751.

17.

George

, Merrill

R. K.

, & Schillebeeckx

S. J. D.

(2020). Digital sustainability and entrepreneurship: How digital innovations are helping tackle climate change and sustainable development. Entrepreneurship Theory and Practice , 44(5), 920–945.

18.

Gregoire

D. A.

, Barr

P. S.

, & Shepherd

D. A.

(2019). Cognitive processes of opportunity recognition: The role of structural alignment. Journal of Management Studies , 56(4), 713–740.

19.

Haefliger

(2020). Technology and institutional work in the emergence of new practice fields: Understanding data science in the innovation field. Technological Forecasting and Social Change , 155, 119982.

20.

Henry

, Foss

N. J.

, & Linder

(2023). Digital transformation and entrepreneurship: A review and research agenda. Technovation , 120, 102526.

21.

Hinings

, Gegenhuber

, & Greenwood

(2018). Digital innovation and transformation: An institutional perspective. Information and Organization , 28(1), 52–61.

22.

Isenberg

D. J.

(2010). How to start an entrepreneurial revolution. Harvard Business Review , 88(6), 40–50.

23.

Jobin

, Ienca

, & Vayena

(2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence , 1(9), 389–399.

24.

Kapasi

, & Galloway

(2023). Disrupting the entrepreneurial self: Generative AI, creativity, and the changing nature of opportunity development. Journal of Business Venturing Insights , 19, e00379.

25.

Khanna

, & Palepu

K. G.

(2010). Winning in emerging markets: A road map for strategy and execution . Harvard Business Press.

26.

Leonardi

P. M.

(2011). When flexible routines meet flexible technologies: Affordance, constraint, and the imbrication of human and material agencies. MIS Quarterly , 35(1), 147–167.

27.

Leonardi

P. M.

(2013). Theoretical foundations for the study of sociomateriality. Information and Organization , 23(2), 59–76.

28.

Leonardi

P. M.

(2020). COVID-19 and the new technologies of organizing: Digital exhaust, digital footprints, and artificial intelligence in the wake of remote work. Journal of Management Studies , 58(1), 249–253.

29.

Markides

C. C.

(2013). Business model innovation: What can the ambidexterity literature teach us? Academy of Management Perspectives , 27(4), 313–323.

30.

Moher

, Liberati

, Tetzlaff

, Altman

D. G.

, & the PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine , 6(7), e1000097.

31.

Nambisan

(2017). Digital entrepreneurship: Toward a digital technology perspective of entrepreneurship. Entrepreneurship Theory and Practice , 41(6), 1029–1055.

32.

Nambisan

, Wright

, & Feldman

(2019). The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy , 48(8), 103773.

33.

Orlikowski

W. J.

, & Scott

S. V.

(2008). Sociomateriality: Challenging the separation of technology, work and organization. The Academy of Management Annals , 2(1), 433–474.

34.

Phan

, Wright

, & Lee

S. H.

(2017). Of robots, artificial intelligence, and work. Academy of Management Perspectives , 31(4), 253–255.

35.

Politis

(2005). The process of entrepreneurial learning: A conceptual framework. Entrepreneurship Theory and Practice , 29(4), 399–424.

36.

Rafols

, Leydesdorff

, O’Hare

, Nightingale

, & Stirling

(2012). How journal rankings can suppress interdisciplinary research: A comparison between innovation studies and business and management. Research Policy , 41(7), 1262–1282.

37.

Roundy

P. T.

, Bradshaw

, & Brockman

B. K.

(2018). The emergence of entrepreneurial ecosystems: A complex adaptive systems approach. Journal of Business Research , 86, 1–10.

38.

Scott

W. R.

(2014). Institutions and organizations: Ideas, interests, and identities (4th ed.). Sage Publications.

39.

Shepherd

D. A.

(2015). Party on! A call for entrepreneurship research that is more interactive, activity based, cognitively hot, compassionate, and prosocial. Journal of Business Venturing , 30(4), 489–507.

40.

Shepherd

D. A.

, Williams

T. A.

, & Patzelt

(2015). Thinking about entrepreneurial decision making: Review and research agenda. Journal of Management , 41(1), 11–46.

41.

Snyder

(2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research , 104, 333–339.

42.

Spigel

(2017). The relational organization of entrepreneurial ecosystems. Entrepreneurship Theory and Practice , 41(1), 49–72.

43.

Stam

(2015). Entrepreneurial ecosystems and regional policy: A sympathetic critique. European Planning Studies , 23(9), 1759–1769.

44.

Stam

, & Spigel

(2017). Entrepreneurial ecosystems. In Blackburn

, De Clercq

, & Heinonen

(Eds), The SAGE Handbook of Small Business and Entrepreneurship (pp. 407–422). Sage Publications.

45.

Thelwall

, & Kousha

(2017). Academic journals: Web indicators for research evaluation. In Research evaluation in practice (pp. 227–246). Springer.

46.

Thomas

L. D. W.

, Autio

, & Gann

D. M.

(2014). Architectural leverage: Putting platforms in context. Academy of Management Perspectives , 28(2), 198–219.

47.

Tiberius

, & Hirth

(2019). Impacts of digitization on auditing: A Delphi study for Germany. Journal of International Accounting, Auditing and Taxation , 37, 100288.

48.

Tranfield

, Denyer

, & Smart

(2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management , 14(3), 207–222.

49.

Tschang

F. T.

, & Almirall

(2021). Artificial intelligence as augmenting automation: Implications for employment. Academy of Management Perspectives , 35(4), 642–659.

50.

von Briel

, Recker

, & Davidsson

(2021). Not all digital ventures are created equal: Implications for venture creation processes. Journal of Business Venturing , 36(1), 106053.

51.

Webb

J. W.

, Tihanyi

, Ireland

R. D.

, & Sirmon

D. G.

(2009). You say illegal, I say legitimate: Entrepreneurship in the informal economy. Academy of Management Review , 34(3), 492–510.

52.

Zeng

, Lu

, & Heng

(2023). The ethics and governance of AI in entrepreneurship: Towards a responsible innovation agenda. Technological Forecasting and Social Change , 191, 122519.

53.

Zupic

, & Cater

(2015). Bibliometric methods in management and organization. Organizational Research Methods , 18(3), 429–472.

Artificial Intelligence and Entrepreneurial Ecosystems in Emerging Economies: Rethinking Innovation,Governance and SME Development

Abstract

Keywords

Get full access to this article

References