Agentic AI in 6G Software Businesses: A Layered Maturity Model

TL;DR

This paper explores the adoption of agentic AI in 6G software businesses, identifying key motivators and barriers, and proposes a layered maturity model to guide organizational readiness and development.

Contribution

It introduces a structured thematic mapping of factors affecting agentic AI adoption and presents a preliminary layered maturity model based on CMMI for 6G software organizations.

Findings

Identified 29 motivators and 27 demotivators for adoption.

Categorized factors into five high-level themes.

Proposed a layered maturity model for organizational assessment.

Abstract

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.