Understanding the Low Adoption of AI in South African Medium Sized Organisations

13 pages•Published: July 18, 2022

Abstract

Anecdotal evidence suggested that South African Small to Medium Enterprises (SME) who have access to Artificial Intelligence (AI) tools as part of their enterprise resource planning software are not adopting these tools. This was seen as a problem because the SME sector forms the foundation for economic growth and the adoption of AI in this sector could enhance its ability to compete on a global stage. Hence the purpose of this research is to understand this lack of adoption. This qualitative study follows an interpretive philosophy and an inductive approach. Seven medium sized companies were selected across a variety of industry sectors and executives from each company were interviewed. The findings reveal that even though the participants generally have a clear understanding of the benefits of AI adoption and can articulate use cases, there are inhibiting factors preventing adoption. Primary among these inhibiting factors is the fear of losing control of critical business processes to a machine-based algorithm and the perceived lack of IT maturity to adopt and manage these AI tools. The value of these findings is that they provide an understanding of the barriers to AI adoption as well us highlighting the South African characteristic of reliance on informal networks to guide adoption decisions.

Keyphrases: ai adoption, artificial intelligence, smes

In: Aurona Gerber (editor). Proceedings of 43rd Conference of the South African Institute of Computer Scientists and Information Technologists, vol 85, pages 257-269.

Links:	https://easychair.org/publications/paper/8J4rB
	https://doi.org/10.29007/c4rr

BibTeX entry

@inproceedings{SAICSIT2022:Understanding_Low_Adoption_AI,
  author    = {Franz Schoeman and Lisa Seymour},
  title     = {Understanding the Low Adoption of AI in South African Medium Sized Organisations},
  booktitle = {Proceedings of 43rd Conference of the South African Institute of Computer Scientists and Information Technologists},
  editor    = {Aurona Gerber},
  series    = {EPiC Series in Computing},
  volume    = {85},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/8J4rB},
  doi       = {10.29007/c4rr},
  pages     = {257-269},
  year      = {2022}}

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