The Adoption of Artificial Intelligence in SMEs Social Media Marketing: Study of Organisational Routines
(2025) ENTN19 20251Department of Business Administration
- Abstract
- This thesis explores how new ventures develop routines for using artificial intelligence (AI) in social media marketing. As AI tools become more accessible, many small companies begin using them without formal rules or training. The study focuses on small and medium-sized enterprises (SMEs) in the early stages of development and examines how AI use begins and spreads within teams.
The research is based on ten semi-structured interviews with employees and founders of ventures already using AI for social media marketing. Following the Gioia methodology (Gioia et al. 2013), we developed a three-part model that explains how routines form through bottom-up adoption, peer-to-peer diffusion, and evolving norms for AI use.
Our findings show that... (More) - This thesis explores how new ventures develop routines for using artificial intelligence (AI) in social media marketing. As AI tools become more accessible, many small companies begin using them without formal rules or training. The study focuses on small and medium-sized enterprises (SMEs) in the early stages of development and examines how AI use begins and spreads within teams.
The research is based on ten semi-structured interviews with employees and founders of ventures already using AI for social media marketing. Following the Gioia methodology (Gioia et al. 2013), we developed a three-part model that explains how routines form through bottom-up adoption, peer-to-peer diffusion, and evolving norms for AI use.
Our findings show that employees often start using AI tools like ChatGPT on their own, then share tips and feedback with colleagues. These informal actions gradually turn into shared routines within teams. We also propose a modified framework based on El-Awad’s (2019) model of learning in new ventures, showing how AI changes the way routines emerge and develop.
This thesis contributes to research on AI in entrepreneurship by illustrating how routines can develop from individual actions even without formal processes. It also offers insight into how early-stage ventures are adapting their ways of working as AI becomes part of everyday marketing practice. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9206569
- author
- Meimere, Renate LU and Mach, Marek LU
- supervisor
-
- Ziad El-Awad LU
- organization
- course
- ENTN19 20251
- year
- 2025
- type
- H1 - Master's Degree (One Year)
- subject
- keywords
- Artificial Intelligence, Social Media Marketing, Organisational Routines, Small and Medium-Sized Enterprises (SMEs), Bottom-up Learning.
- language
- English
- id
- 9206569
- date added to LUP
- 2025-07-01 08:36:37
- date last changed
- 2025-07-01 08:36:37
@misc{9206569, abstract = {{This thesis explores how new ventures develop routines for using artificial intelligence (AI) in social media marketing. As AI tools become more accessible, many small companies begin using them without formal rules or training. The study focuses on small and medium-sized enterprises (SMEs) in the early stages of development and examines how AI use begins and spreads within teams. The research is based on ten semi-structured interviews with employees and founders of ventures already using AI for social media marketing. Following the Gioia methodology (Gioia et al. 2013), we developed a three-part model that explains how routines form through bottom-up adoption, peer-to-peer diffusion, and evolving norms for AI use. Our findings show that employees often start using AI tools like ChatGPT on their own, then share tips and feedback with colleagues. These informal actions gradually turn into shared routines within teams. We also propose a modified framework based on El-Awad’s (2019) model of learning in new ventures, showing how AI changes the way routines emerge and develop. This thesis contributes to research on AI in entrepreneurship by illustrating how routines can develop from individual actions even without formal processes. It also offers insight into how early-stage ventures are adapting their ways of working as AI becomes part of everyday marketing practice.}}, author = {{Meimere, Renate and Mach, Marek}}, language = {{eng}}, note = {{Student Paper}}, title = {{The Adoption of Artificial Intelligence in SMEs Social Media Marketing: Study of Organisational Routines}}, year = {{2025}}, }