The process of internationalization may be more difficult for emerging markets' artificial intelligence startups (AI startups) due to several challenges. These challenges include weak institutions, limited financial support, political instability, lack of adequate local infrastructure. Significantly less research has being done on entrepreneurial ecosystems, especially in emerging markets. Therefore, this study aims to address the current state of the entrepreneurial ecosystem, in emerging markets and AI startups internationalization process. As a result, the study focuses on the challenges faced by AI startup within the Nigerian and South African entrepreneurial ecosystem, to address how the entrepreneurial ecosystem affects AI startups internationalisation process. To answer the research question, qualitative research was carried out using semi structure interviews with different case companies from South Africa and Nigeria. Although these countries are similar in nature, AI startups face various internal challenges in terms of government policies, institutions, and infrastructure. Based on the findings, it was noticed that there is a relationship between the entrepreneurial ecosystem and the growth and survival of AI startups. The elements of an Entrepreneurial ecosystem (social, cultural, and material elements) also influence the internationalisation of AI startups within an entrepreneurial ecosystem space. Entrepreneurial ecosystem challenges were identified which discourages or hinder the growth of AI startups within the Nigerian and South African markets. In conclusion, we noticed that African AI startups prefer to practice their business model in the home markets and flourish their confidence levels before seeking internationalization opportunities. Most of the case AI startups prefer to start internationalization from close psychic market before going distance international markets. However, these AI startups adopt network relationship approach through key business partners for international expansion.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-113848 |
| Date | January 2022 |
| Creators | Dahanayake, Hansika, Muna, Claudia Bih |
| Publisher | Linnéuniversitetet, Institutionen för marknadsföring (MF) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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