Agentic AI in 6G Software Businesses: A Layered Maturity Model
On the map: LLM agents and tool use → Software engineering coding agents
Abstract (arXiv)
The emergence of agentic AI systems in 6G software businesses presents both strategic opportunities and significant challenges. While such systems promise increased autonomy, scalability, and intelligent decision-making across distributed environments, their adoption raises concerns regarding technical immaturity, integration complexity, organizational readiness, and performance-cost trade-offs. In this study, we conducted a preliminary thematic mapping to identify factors influencing the adoption of agentic software within the context of 6G. Drawing on a multivocal literature review and targeted scanning, we identified 29 motivators and 27 demotivators, which were further categorized into five high-level themes in each group. This thematic mapping offers a structured overview of the enabling and inhibiting forces shaping organizational readiness for agentic transformation. Positioned as a feasibility assessment, the study represents an early phase of a broader research initiative aimed at developing and validating a layered maturity model grounded in CMMI model with the software architectural three dimensions possibly Data, Business Logic, and Presentation. Ultimately, this work seeks to provide a practical framework to help software-driven organizations assess, structure, and advance their agent-first capabilities in alignment with the demands of 6G.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 9 of its 41 references that are in the map. First posted on arXiv 5 Aug 2025.
Builds on
9 of 41 references.
References · 9
- 2025AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challengescited by 167
- 2019A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problemscited by 157
- 2025LLMs for Explainable AI: A Comprehensive Surveycited by 42
- 2021The Road Towards 6G: A Comprehensive Surveycited by 40
- 2017Guidelines for including grey literature and conducting multivocal literature reviews in software engineeringcited by 38
- 2025Internet of Agents: Fundamentals, Applications, and Challengescited by 31
- 2025The Future is Agentic: Definitions, Perspectives, and Open Challenges of Multi-Agent Recommender Systemscited by 14
- 2025Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiencescited by 12
- 2024Large language models in 6G security: challenges and opportunitiescited by 5
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
Similar, not cited
Close in wording, no citation either way
- 2026Governing the Agentic Enterprise: A Governance Maturity Model for Managing AI Agent Sprawl in Business Operations
- 2026Agentic AI in Industry: Adoption Level and Deployment Barriers
- 2026Assistance to Autonomy: A Systematic Literature Review of Agentic AI across the Software Development Life Cycle
- 2026A Practical Guide to Agentic AI Transition in Organizations
- 2025Agentic AI in Product Management: A Co-Evolutionary Model
- 2026From Agentic to Autogenic Network Management for AI-Native 6G and Beyond: A Standards Perspective
- 2026Agentic AI in Engineering and Manufacturing: Industry Perspectives on Utility, Adoption, Challenges, and Opportunities
- 2026Governance by Design: Architecting Agentic AI for Organizational Learning and Scalable Autonomy