The Role of Artificial Intelligence in Corporate Software License Management: A Survey of Challenges, Solutions, and Future Directions

Abstract

Corporate software license management has become. This refers to the movement of containers by trucks. It is a crucial but very complex operation. It is encountering surging expenses, greater legal liabilities and. inherent inefficiencies of manual tracking. Failure to manage these. Exposing assets can lead to severe financial consequences for an organization. legal risks. In response, Artificial Intelligence (AI) has emerged. It has ability to change how we consume technology and AI. oversight to proactive, intelligent automation. This survey provides. A close look at the use of AI in Software Licensing at present and the future. A top notch curated selection of 13 seminal texts. Academic and industry publications. Our review synthesizes. research on four major themes: automatic number-plate recognition, . Smart Compliance Checking and Cost Prediction. Machine learning and natural intelligence share similar structures. Language Processing (NLP). The analysis reveals a significant gap. A separation of academic solutions found for one-off tasks. Reading and the important role of ITSM in application parsing and the management of integrated, end-to-end managerial tools. Furthermore, a disconnect exists. theoretical risk identification and the limited remediation. strategies available in practice. The survey concludes that the. Innovation is taking a new directional shift. fragmented tools toward holistic solutions. We foreshadow the. the rise of unified AI-powered Software-as-a-Service or SaaS platforms that are the needed evolution to resolve these identified. Fill in loopholes and merge advancements into a common strategy asset for modern enterprises.

Introduction

The text discusses the growing complexity of software license management (Software Asset Management – SAM) and the need for AI-driven solutions to address inefficiencies, risks, and compliance challenges in modern organizations. Traditional SAM systems rely heavily on manual tracking and static processes, which often lead to errors, high costs, license underutilization, and legal risks such as vendor audits and penalties.

To overcome these limitations, the paper highlights the importance of AI-based approaches, including Natural Language Processing (NLP) for contract analysis, Robotic Process Automation (RPA) for repetitive tasks, and Machine Learning (ML) for predictive analytics and license optimization. These technologies enable more proactive, automated, and efficient software license management.

The literature survey shows various advancements in AI for license tracking, compliance, and cloud-based automation, but also identifies key gaps such as lack of unified systems, legal ambiguity, difficulty in tracking AI-generated software, and limited real-world integration.

To address these issues, the paper proposes “Licensly”, an AI-powered SaaS platform that integrates multiple technologies like RAG (Retrieval-Augmented Generation), NLP, and ML. Licensly aims to provide automated license discovery, compliance monitoring, contract analysis, cost optimization, and real-time decision support.

Conclusion

This article aims at surveying the use of Artificial Intelligence to corporate software license management, looking at 13 key publications to unpack how a landscape of fragments. AI solutions suggest the necessity for a coordinated strategy. platform. Our review confirms that traditional approaches to. Software Asset Management (SAM) is not enough. The licensing agreements are getting more difficult. the cost, and major compliance risks [2], [11]. [2], [11]. AI technologies. Crucial Enablers of ML, NLP, RPA Including RAG. making SAM an active strategic function The proposed. Licensly platform exemplifies an integrated path forward.

References

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Copyright

Copyright © 2026 Prof. M. S. Sawalkar, Rushikesh Navale, Lav Parab, Shashwat Patil. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.