SME-TEAM: Leveraging Trust and Ethics for Secure and Responsible Use of AI and LLMs in SMEs
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Abstract (arXiv)
Artificial Intelligence (AI) and Large Language Models (LLMs) are revolutionizing today's business practices; however, their adoption within small and medium-sized enterprises (SMEs) raises serious trust, ethical, and technical issues. In this perspective paper, we introduce a structured, multi-phased framework, "SME-TEAM" for the secure and responsible use of these technologies in SMEs. Based on a conceptual structure of four key pillars, i.e., Data, Algorithms, Human Oversight, and Model Architecture, SME-TEAM bridges theoretical ethical principles with operational practice, enhancing AI capabilities across a wide range of applications in SMEs. Ultimately, this paper provides a structured roadmap for the adoption of these emerging technologies, positioning trust and ethics as a driving force for resilience, competitiveness, and sustainable innovation within the area of business analytics and SMEs.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 4 of its 55 references that are in the map. First posted on arXiv 12 Sep 2025.
Builds on
4 of 55 references.
References · 4
- 2023A Comprehensive Overview of Large Language Modelscited by 648
- 2023Explainability for Large Language Models: A Surveycited by 333
- 2025From Prompt Injections to Protocol Exploits: Threats in LLM-Powered AI Agents Workflowscited by 58
- 2024Generative AI in Cybersecurity: A Comprehensive Review of LLM Applications and Vulnerabilitiescited by 21
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Citing papers per year: 2026: 1.
1 paper.