mlsanityData to 14 Oct 2026

SME-TEAM: Leveraging Trust and Ethics for Secure and Responsible Use of AI and LLMs in SMEs

arXiv 2509.10594 ↗First posted 12 Sep 2025cs.LG cs.AI cs.CRcited by 1

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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

  1. 2023A Comprehensive Overview of Large Language Modelscited by 648
  2. 2023Explainability for Large Language Models: A Surveycited by 333
  3. 2025From Prompt Injections to Protocol Exploits: Threats in LLM-Powered AI Agents Workflowscited by 58
  4. 2024Generative AI in Cybersecurity: A Comprehensive Review of LLM Applications and Vulnerabilitiescited by 21

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