Agentic AI Frameworks in SMMEs: A Systematic Literature Review of Ecosystemic Interconnected Agents

This study examines the application of agentic artificial intelligence (AI) frameworks within small, medium, and micro-enterprises (SMMEs), highlighting how interconnected autonomous agents improve operational efficiency and adaptability. Using the PRISMA 2020 framework, this study systematically id...

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Main Authors: Peter Adebowale Olujimi, Pius Adewale Owolawi, Refilwe Constance Mogase, Etienne Van Wyk
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:AI
Subjects:
Online Access:https://www.mdpi.com/2673-2688/6/6/123
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author Peter Adebowale Olujimi
Pius Adewale Owolawi
Refilwe Constance Mogase
Etienne Van Wyk
author_facet Peter Adebowale Olujimi
Pius Adewale Owolawi
Refilwe Constance Mogase
Etienne Van Wyk
author_sort Peter Adebowale Olujimi
collection DOAJ
description This study examines the application of agentic artificial intelligence (AI) frameworks within small, medium, and micro-enterprises (SMMEs), highlighting how interconnected autonomous agents improve operational efficiency and adaptability. Using the PRISMA 2020 framework, this study systematically identified, screened, and analyzed 66 studies, including peer-reviewed and credible gray literature, published between 2019 and 2024, to assess agentic AI frameworks in SMMEs. Recognizing the constraints faced by SMMEs, such as limited scalability, high operational demands, and restricted access to advanced technologies, the review synthesizes existing research to highlight the characteristics, implementations, and impacts of agentic AI in task automation, decision-making, and ecosystem-wide collaboration. The results demonstrate the potential of agentic AI to address technological, ethical, and infrastructure barriers while promoting innovation, scalability, and competitiveness. This review contributes to the understanding of agentic AI frameworks by offering practical insights and setting the groundwork for further research into their applications in SMMEs’ dynamic and resource-constrained economic environments.
format Article
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institution Kabale University
issn 2673-2688
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publishDate 2025-06-01
publisher MDPI AG
record_format Article
series AI
spelling doaj-art-ef9554e5ea9d4c9881d0d3d1c544f6732025-08-20T03:30:24ZengMDPI AGAI2673-26882025-06-016612310.3390/ai6060123Agentic AI Frameworks in SMMEs: A Systematic Literature Review of Ecosystemic Interconnected AgentsPeter Adebowale Olujimi0Pius Adewale Owolawi1Refilwe Constance Mogase2Etienne Van Wyk3Department of Informatics, Faculty of Information and Communication Technology, Tshwane University of Technology, Pretoria 0001, South AfricaDepartment of Computer Systems Engineering, Faculty of Information and Communication Technology, Tshwane University of Technology, Pretoria 0001, South AfricaDepartment of Informatics, Faculty of Information and Communication Technology, Tshwane University of Technology, Pretoria 0001, South AfricaFaculty of Information and Communication Technology, Tshwane University of Technology, Pretoria 0001, South AfricaThis study examines the application of agentic artificial intelligence (AI) frameworks within small, medium, and micro-enterprises (SMMEs), highlighting how interconnected autonomous agents improve operational efficiency and adaptability. Using the PRISMA 2020 framework, this study systematically identified, screened, and analyzed 66 studies, including peer-reviewed and credible gray literature, published between 2019 and 2024, to assess agentic AI frameworks in SMMEs. Recognizing the constraints faced by SMMEs, such as limited scalability, high operational demands, and restricted access to advanced technologies, the review synthesizes existing research to highlight the characteristics, implementations, and impacts of agentic AI in task automation, decision-making, and ecosystem-wide collaboration. The results demonstrate the potential of agentic AI to address technological, ethical, and infrastructure barriers while promoting innovation, scalability, and competitiveness. This review contributes to the understanding of agentic AI frameworks by offering practical insights and setting the groundwork for further research into their applications in SMMEs’ dynamic and resource-constrained economic environments.https://www.mdpi.com/2673-2688/6/6/123agentic AIecosystemic interconnected agentsoperational efficiencysystematic reviewSMMEs
spellingShingle Peter Adebowale Olujimi
Pius Adewale Owolawi
Refilwe Constance Mogase
Etienne Van Wyk
Agentic AI Frameworks in SMMEs: A Systematic Literature Review of Ecosystemic Interconnected Agents
AI
agentic AI
ecosystemic interconnected agents
operational efficiency
systematic review
SMMEs
title Agentic AI Frameworks in SMMEs: A Systematic Literature Review of Ecosystemic Interconnected Agents
title_full Agentic AI Frameworks in SMMEs: A Systematic Literature Review of Ecosystemic Interconnected Agents
title_fullStr Agentic AI Frameworks in SMMEs: A Systematic Literature Review of Ecosystemic Interconnected Agents
title_full_unstemmed Agentic AI Frameworks in SMMEs: A Systematic Literature Review of Ecosystemic Interconnected Agents
title_short Agentic AI Frameworks in SMMEs: A Systematic Literature Review of Ecosystemic Interconnected Agents
title_sort agentic ai frameworks in smmes a systematic literature review of ecosystemic interconnected agents
topic agentic AI
ecosystemic interconnected agents
operational efficiency
systematic review
SMMEs
url https://www.mdpi.com/2673-2688/6/6/123
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AT refilweconstancemogase agenticaiframeworksinsmmesasystematicliteraturereviewofecosystemicinterconnectedagents
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