eISSN: 3087-4270 editor@aimjournals.com
All Journals
Submit your article

International Journal of Advanced Artificial Intelligence Research

Open Access Peer Review International
Open Access

Analyzing Software Adoption in Enterprises: A Survey of Frameworks and Metrics

DOI https://doi.org/10.55640/ijaair-v03i07-05
pdf
Ms. Anamika Soni 1 ,
4 Assistant Professor, Department of Computer Sciences and Applications, Mandsaur University, Mandsaur, India

Abstract

The implementation and user acceptance of a system are no longer the only factors influencing enterprise software adoption. These are usability, integration, maintenance, security, and alignment with organizational goals of software products. This paper investigates the most important concepts and metrics used to estimate software adoption in enterprises. Apart from metrics of software adoption related to usage behavior, user experience, software quality, performance, security, reliability, resource efficiency, and organizational value, the literature review comprises adoption models that are empirically proved. According to the results, most of the studies that have been conducted have focused on behavioral intention or particular adoption scenarios, and the technological, business, security, and sustainability aspects have been examined separately. Organizations’ capacity to evaluate the overall efficacy and long-term success of software deployment is hampered by this fragmented viewpoint. As a result, the report emphasizes the necessity of an integrated assessment approach that incorporates organizational, commercial, technical, behavioral, and sustainability aspects. The study highlights research potential for creating thorough metrics and frameworks that might assist evidence-based assessment of corporate software adoption, as well as important shortcomings in current methods.

Keywords

Enterprise software adoption, Software quality, Reliability metrics

References

S. Singh, “Advancing Wireless Communications with Open Radio Access Network,” in 2025 6th International Conference on Data Intelligence and Cognitive Informatics (ICDICI), IEEE, Jul. 2025, pp. 682–687. doi: 10.1109/ICDICI66477.2025.11135206.
H. P. Cyril, N. D. Bhandarwar, S. Kumara, and S. Mathur, “Securing Containerised Applications Using Kubernetes-Based Orchestration in Software Development,” in 2026 International Conference on Intelligent Computing, Networks, and Security (IC-ICNS), 2026, pp. 1–6. doi: 10.1109/IC-ICNS68863.2026.11537887.
N. Adik, “The Rise of Open and Free Networks: A Community-Driven Paradigm for Decentralized Connectivity,” in 2025 IEEE First International Conference on Innovations in Engineering and Next-Generation Technologies for Sustainability (ICINVENTS), Coimbatore, India: IEEE, 2025, pp. 1–9, November. doi: 10.1109/ICINVENTS64613.2025.11402224.
Y. Muni, “A Review of Efficient Routing Architectures Using OSPF, BGP, and MPLS in Multi-Protocol Networks,” Eng. Technol. J., vol. 11, no. 01, Jan. 2026, doi: 10.47191/etj/v11i01.21.
A. Kashyap, “Digital Transformation through Enterprise Software: A Comprehensive Review of Implementation Strategies,” Int. J. Innov. Sci. Res. Technol., 2025, doi: 10.38124/ijisrt/25apr2189.
V. K. Sharma, “Cloud Computing IoT: 5G Focused IoT with Cloud Solutions,” Int. J. AI, BigData, Comput. Manag. Stud., vol. 6, no. 3, 2025, doi: 10.63282/3050-9416.IJAIBDCMS-V6I3P103.
T. Shah, “Cloud-Based Data Warehousing for Marketing Agility: Lessons from FinTech Migrations to Snowflake and AWS,” Int. J. Adv. Res. Sci. Commun. Technol., vol. 4, no. 4, March, pp. 642–652, 2024, doi: 10.48175/IJARSCT-16000B.
A. O. Temitope, “Software Adoption in Project Management and Their Impact on Project Efficiency and Collaboration,” 2020.
S. Kukar, “Explainable AI Models for Transparent and Ethical Customer Relationship Management Decision,” in 2026 IEEE 2nd International Conference on Secure IoT, Assured and Trusted Computing (SATC), Houston, TX, USA: IEEE, Mar. 2026, pp. 1–7. doi: 10.1109/SATC69565.2026.11542554.
P. Nadagoud, “The Role of Open-Source Software in Enterprise Applications: Benefits, Risks, and Adoption Strategies,” Int. J. Comput. Trends Technol., vol. 72, no. 9, pp. 6–13, 2024, doi: 10.14445/22312803/ijctt-v72i9p102.
H. Taherdoost, “A review of technology acceptance and adoption models and theories,” Procedia Manuf., vol. 22, pp. 960–967, 2018, doi: 10.1016/j.promfg.2018.03.137.
S. FakhrHosseini et al., “User Adoption of Intelligent Environments: A Review of Technology Adoption Models, Challenges, and Prospects,” Int. J. Hum. Comput. Interact., 2024, doi: 10.1080/10447318.2022.2118851.
V. Gudur, C. Upadhyay, S. Sudarsan, R. Dandigam, A. Patel, and S. Tiwari, “Trust Deviation Metrics (TDM) for AI-Driven Cloud Orchestration,” in Proceedings of the 2026 9th International Conference on Information and Computer Technologies, ACM, 2026, pp. 539–544. doi: 10.1145/3803291.3803293.
S. Devarakonda, R. Lingam, and V. Challa, “Confidence-Gated RAG for Adaptive Retrieval in Sequential Agents,” in ICLR 2026 Workshop on Logical Reasoning of Large Language Models, 2026, pp. 1–18. doi: 10.1109/TCASAI.2026.3653699.
A. Bandi, P. V. S. R. Adapa, and Y. E. V. P. K. Kuchi, “The Power of Generative AI: A Review of Requirements, Models, Input–Output Formats, Evaluation Metrics, and Challenges,” Futur. Internet, vol. 15, no. 8, p. 260, Jul. 2023, doi: 10.3390/fi15080260.
S. Jain and D. Jain, “Artifact Comparison Analyzer: Evaluating Microservice Build Metrics for Performance and Efficiency Improvements,” in 2026 IEEE International Conference on AI Engineering and Innovations (AIEI), Jamshedpur, India: IEEE, Mar. 2026, pp. 1–6. doi: 10.1109/AIEI69164.2026.11497468.
R. K. Kanneganti, “Security and Compliance Issues in Cloud-Based Deployments of Content and Workflow Management Systems,” Eastasouth J. Inf. Syst. Comput. Sci., vol. 2, no. 01, pp. 131–138, Aug. 2024, doi: 10.58812/esiscs.v2i01.1122.
P. Haindl and R. Plösch, “Value‐oriented quality metrics in software development: Practical relevance from a software engineering perspective,” IET Softw., vol. 16, no. 2, pp. 167–184, Apr. 2022, doi: 10.1049/sfw2.12051.
V. Chaturvedi, “Modern Software Development with Java , Spring Boot , and Python : A Survey of Frameworks and Best Practices,” ESP J. Eng. Technol. Adv., vol. 3, no. 4, pp. 188–197, 2023, doi: 10.56472/25832646/JETA-V3I8P121.
S. Singamsetty, “AI-Enabled Data Stewardship Real-Time Alignment of Privacy and Storage Policies Across Global Systems using Deep CNN-RNN Techniques,” in 2025 5th Asian Conference on Innovation in Technology (ASIANCON), IEEE, Aug. 2025, pp. 1–6. doi: 10.1109/ASIANCON66527.2025.11281010.
J. B. Mehta, “Securing Test Automation in Zero Trust Architectures: A Framework for Continuous Verification,” in 2025 International Conference on Computer and Applications (ICCA), IEEE, Dec. 2025, pp. 1–5. doi: 10.1109/ICCA66035.2025.11430950.
A. A. Soni, M. Parikh, R. N. K. Dhenia, J. A. Soni, A. R. Jha, and S. M. Shah, “Reinforcement Learning for Dynamic Workflow Optimization in CI/CD Pipelines,” in 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN), IEEE, Dec. 2025, pp. 638–644. doi: 10.1109/CICN67655.2025.11367872.
R. Palwe, “The Role of User Experience Design in Advancing Digital Sustainability,” Int. J. Sci. Res., vol. 14, no. 10, pp. 1168–1176, 2025.
V. Kumar, S. K. Madishetty, and G. N. Maddipatla, “Intelligent Surgical Tables: Real-Time Patient Monitoring and Autonomous Adjustment Using IoT, Cloud Computing, and Cybersecurity,” J. Comput. Anal. Appl., vol. 31, no. 02, Feb. 2023, doi: 10.48047/jocaaa.2023.31.02.50.
P. H. Desai, P. Mahalle, and P. Chandre, “Intelligent Access Control Schemes for the Internet of Everything: A Survey of Techniques, Challenges, and Future Directions,” in Information Systems for Intelligent Systems, 2026, pp. 95–105. doi: 10.1007/978-3-032-13196-6_9.
K. Dixit, “Predictive Analytics in Business Intelligence for Sales Forecasting,” Int. J. Adv. Res. Sci. Commun. Technol., vol. 3, no. 1, p. 981, Sep. 2023, doi: 10.48175/IJARSCT-12750G.
S. Martínez-Fernández, P. Jovanovic, X. Franch, and A. Jedlitschka, “Towards Automated Data Integration in Software Analytics,” in Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics, New York, NY, USA, NY, USA: ACM, Aug. 2018, pp. 1–5. doi: 10.1145/3242153.3242159.
E. Bouwers, A. van Deursen, and J. Visser, “Evaluating usefulness of software metrics: An industrial experience report,” in 2013 35th International Conference on Software Engineering (ICSE), IEEE, May 2013, pp. 921–930. doi: 10.1109/ICSE.2013.6606641.
H. Dong and Y. Shen, “The monitoring effect of CSI 300 inclusion: Evidence from enterprise risk management adoption,” Financ. Res. Lett., vol. 93, p. 109634, Mar. 2026, doi: 10.1016/j.frl.2026.109634.
M. Alenezi and M. Akour, “AI-Driven Innovations in Software Engineering: A Review of Current Practices and Future Directions,” Appl. Sci., vol. 15, no. 3, p. 1344, Jan. 2025, doi: 10.3390/app15031344.
T. R. Merlo, F. Fard, and S. Hawamdeh, “Cloud Computing’s Impact on the Digital Transformation of the Enterprise: A Mixed-Methods Approach,” Sustainability, vol. 17, no. 13, p. 5755, Jun. 2025, doi: 10.3390/su17135755.
M. Z. Fathoni, A. M. Sri Asih, and M. A. Wibisono, “Adoption of Open-Source Enterprise Resource Planning in Small and Medium Industries: A Literature Review,” in IEEE International Conference on Industrial Engineering and Engineering Management, 2024. doi: 10.1109/IEEM62345.2024.10857088.
M. Bilal, M. Iftikhar Ali, K. Rasheed, and S. Saad, “Exploring Adoption Trends of Knowledge Management Systems in the Software Industry’s SMEs: A Comprehensive Investigation of Enablers and Barriers,” in 2023 4th International Conference on Data Analytics for Business and Industry, ICDABI 2023, 2023. doi: 10.1109/ICDABI60145.2023.10629373.
O. N. Patino-Toro, A. Valencia-Arias, S. Gomez-Molina, and M. C. Bermeo-Giraldo, “Open-Source Software Adoption Among University Students in Emerging Countries,” IEEE Rev. Iberoam. Tecnol. del Aprendiz., vol. 17, no. 2, pp. 185–196, May 2022, doi: 10.1109/RITA.2022.3166950.

Similar Articles

1-10 of 34

You may also start an advanced similarity search for this article.