{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T11:18:44Z","timestamp":1787915924775,"version":"build-2784847793"},"reference-count":44,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,3,18]],"date-time":"2025-03-18T00:00:00Z","timestamp":1742256000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Agile software project management (ASPM) serves modern industries to conduct iterative development of complicated code bases. The decision-making process in Agile environments regularly depends on individual opinions, creating ineffective results for risk management and resource distribution. Artificial intelligence (AI) is a promising approach for handling these challenges by delivering data-based choices to project management. This research introduces an AI-based decision support system for improving risk reduction and resource distribution in ASPM. The system merges optimization frameworks and predictive analytics to enhance operational decision efficiency. The machine learning solution anchors data evaluation using AI models that simultaneously predict risks and strengthen decision power for resource scheduling. This analysis relied on project records and recent operational data to perform model validation and training procedures. Tests determined how the framework performed against contemporary Agile project management systems by measuring the completion speed of sprints, resource management practices, and risk prediction accuracy. The framework demonstrated better performance by predicting risks and simultaneously maximizing resources utilized during projects. The proposed framework outperformed traditional Agile applications, achieving 94% accuracy in risk identification and enhancing workload management by 25%, leading to an 18% improvement in sprint completion rates and overall project efficiency. These findings confirm that AI-driven decision support systems (DSSs) are crucial in enhancing Agile project management by enabling proactive risk mitigation and optimized resource allocation. By integrating AI-powered decision-making, the framework empowers organizations to improve project outcomes, streamline resource management, and facilitate the adoption of AI-driven methodologies within Agile systems.<\/jats:p>","DOI":"10.3390\/systems13030208","type":"journal-article","created":{"date-parts":[[2025,3,18]],"date-time":"2025-03-18T04:34:43Z","timestamp":1742272483000},"page":"208","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["AI-Driven Decision Support Systems in Agile Software Project Management: Enhancing Risk Mitigation and Resource Allocation"],"prefix":"10.3390","volume":"13","author":[{"given":"Sultan Saaed","family":"Almalki","sequence":"first","affiliation":[{"name":"Department of Digital Transformation and Information, Institute of Public Administration, Jeddah, Makkah Al Mukarramah 23442, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,18]]},"reference":[{"key":"ref_1","unstructured":"Alliance, A. (2024, December 13). Manifesto for Agile Software Development. Agile Alliance. Available online: http:\/\/www.agilealliance.org."},{"key":"ref_2","first-page":"24","article-title":"Utilizing Predictive Analytics and Machine Learning for Enhanced Project Risk Management and Resource Optimization","volume":"2","author":"Jahan","year":"2024","journal-title":"IPHO\u2014J. Adv. Res. Bus. Manag. Account."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Saklamaeva, V., and Pavli\u010d, L. (2023). The Potential of AI-Driven Assistants in Scaled Agile Software Development. Appl. Sci., 14.","DOI":"10.3390\/app14010319"},{"key":"ref_4","unstructured":"Brown, G. (2007). A Critical Evaluation of the Application of Agile Software Development Methods to Distributed Development Efforts, Citeseer. [Master\u2019s Thesis, School of Computing]. Available online: http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Lui, K.M., and Chan, K.C. (2008). Software Development Rhythms: Harmonizing Agile Practices for Synergy, John Wiley & Sons.","DOI":"10.1002\/9780470192672"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Galli, B.J., and Lopez, P.A.H. (2020). Risks management in agile new product development project environments: A review of literature. Sustain. Bus. Concepts Methodol. Tools Appl., 1835\u20131869.","DOI":"10.4018\/978-1-5225-9615-8.ch083"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"106497","DOI":"10.1016\/j.infsof.2020.106497","article-title":"A risk prediction model for software project management based on similarity analysis of context histories","volume":"131","author":"Filippetto","year":"2020","journal-title":"Inf. Softw. Technol."},{"key":"ref_8","first-page":"4751","article-title":"Optimizing Collaboration: Insights into Inter-Team Coordination and Self-Management in Distributed Agile Software Development","volume":"18","author":"Rahman","year":"2021","journal-title":"Webology"},{"key":"ref_9","first-page":"1","article-title":"Challenges of Working from Home in Software Development During Covid-19 Lockdowns","volume":"32","author":"Koch","year":"2023","journal-title":"ACM Trans. Softw. Eng. Methodol."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Betta, J., and Boronina, L. (2018). Transparency in project management\u2013from traditional to agile. Third International Conference on Economic and Business Management (FEBM 2018), Atlantis Press.","DOI":"10.2991\/febm-18.2018.103"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Hadar, E., and Silberman, G.M. (2008, January 19\u201323). Agile architecture methodology: Long-term strategy interleaved with short-term tactics. Proceedings of the Companion to the 23rd ACM SIGPLAN Conference on Object-Oriented Programming Systems Languages and Applications, Nashville, TN, USA.","DOI":"10.1145\/1449814.1449816"},{"key":"ref_12","first-page":"1","article-title":"Integrating AI for agile Project Management: Innovations, challenges, and benefits","volume":"1","author":"Zadeh","year":"2024","journal-title":"Int. J. Ind. Eng. Constr. Manag."},{"key":"ref_13","unstructured":"Bittner, K., and Spence, I. (2006). Managing Iterative Software Development Projects, Addison-Wesley Professional."},{"key":"ref_14","unstructured":"Turban, E. (2011). Decision Support, and Business Intelligence Systems, Pearson Education India."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"140752","DOI":"10.1109\/ACCESS.2020.3010968","article-title":"An Intelligent Recommender and Decision Support System (IRDSS) for Effective Management of Software Projects","volume":"8","author":"Hamid","year":"2020","journal-title":"IEEE Access"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Uysal, M.P. (2022). Machine learning and data science project management from an agile perspective: Methods and challenges. Contemporary Challenges for Agile Project Management, IGI Global.","DOI":"10.4018\/978-1-7998-7872-8.ch005"},{"key":"ref_17","unstructured":"Fatima, T. (2017, January 18\u201319). A Predictive Analytics Approach to Project Management: Reducing Project Failures in Web & Software Development Projects. Proceedings of the International Conference on Data Science (ICDATA), 2017: The Steering Committee of The World Congress in Computer Science, Compute, Meknes, Morocco."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"14749","DOI":"10.1007\/s11042-021-10971-4","article-title":"Augmented reality situated visualization in decision-making","volume":"81","author":"Martins","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"13723","DOI":"10.1007\/s00500-021-06037-0","article-title":"A novel integrated intuitionistic fuzzy decision aid for agile outsourcing provider selection: A COVID-19 pandemic-based scenario analysis","volume":"25","author":"Goker","year":"2021","journal-title":"Soft Comput."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"438","DOI":"10.7763\/IJMLC.2012.V2.162","article-title":"DSS Development and Agile Methods: Towards a new Framework for Software Development Methodology","volume":"2","author":"Garaibeh","year":"2012","journal-title":"Int. J. Mach. Learn. Comput."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1016\/j.jss.2012.01.058","article-title":"Obstacles to decision making in Agile software development teams","volume":"85","author":"Drury","year":"2012","journal-title":"J. Syst. Softw."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1072","DOI":"10.51594\/estj.v5i3.959","article-title":"AI in project management: Exploring theoretical models for decision-making and risk management","volume":"5","author":"Odejide","year":"2024","journal-title":"Eng. Sci. Technol. J."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"32993","DOI":"10.1109\/ACCESS.2025.3539357","article-title":"Enhancing Agile Software Development: A Systematic Literature Review of Requirement Prioritization and Reprioritization Techniques","volume":"13","author":"Tasneem","year":"2025","journal-title":"IEEE Access"},{"key":"ref_24","first-page":"812","article-title":"AI-Driven Prioritization Techniques of Requirements in Agile Methodologies: A Systematic Literature Review","volume":"15","author":"Radwan","year":"2024","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Lin, J. (2013, January 11\u201315). Context-aware task allocation for a distributed agile team. Proceedings of the2013 28th IEEE\/ACM International Conference on Automated Software Engineering (ASE), Silicon Valley, CA, USA.","DOI":"10.1109\/ASE.2013.6693151"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"179","DOI":"10.3390\/computers11120179","article-title":"Agile Development Methodologies and Natural Language Processing: A Mapping Review","volume":"11","author":"Quintana","year":"2022","journal-title":"Computers"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1320","DOI":"10.48175\/IJARSCT-14000T","article-title":"Driving Continuous Improvement in Engineering Projects with AI-Enhanced Agile Testing and Machine Learning","volume":"3","author":"Goyal","year":"2023","journal-title":"Int. J. Adv. Res. Sci. Commun. Technol."},{"key":"ref_28","first-page":"586","article-title":"Agile Risk Mitigation Framework","volume":"21","author":"Naz","year":"2021","journal-title":"Int. J. Comput. Sci. Netw. Secur."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1108\/IJPDLM-12-2021-0532","article-title":"Digitalization and third-party logistics performance: Exploring the roles of customer collaboration and government","volume":"53","author":"Zhou","year":"2023","journal-title":"Int. J. Phys. Distrib. Logist. Manag."},{"key":"ref_30","unstructured":"Singh, M. (2024). Agile Project Management and Testing in the Distributed Development Environment. [Ph.D. Thesis, JC Bose University]."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.infsof.2016.12.005","article-title":"A risk management framework for distributed agile projects","volume":"85","author":"Shrivastava","year":"2017","journal-title":"Inf. Softw. Technol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"104672","DOI":"10.1016\/j.micpro.2022.104672","article-title":"AIDOaRt: AI-augmented Automation for DevOps, a model-based framework for continuous development in Cyber-Physical Systems","volume":"94","author":"Eramo","year":"2022","journal-title":"Microprocess. Microsyst."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Rehman, W., Zainab, H.E., Imran, J., and Bawany, N.Z. (2021, January 21\u201323). NFTs: Applications and challenges. Proceedings of the 2021 22nd International Arab Conference on Information Technology (ACIT), Muscat, Oman.","DOI":"10.1109\/ACIT53391.2021.9677260"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Britto, R., Neto, P.S., Rabelo, R., Ayala, W., and Soares, T. (2012, January 10\u201315). A hybrid approach to solve the agile team allocation problem. Proceedings of the 2012 IEEE Congress on Evolutionary Computation, Brisbane, Australia.","DOI":"10.1109\/CEC.2012.6252999"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"173","DOI":"10.3233\/ICA-150508","article-title":"Evolutionary computation for resource leveling optimization in project management","volume":"23","author":"Kyriklidis","year":"2016","journal-title":"Integr. Comput. Eng."},{"key":"ref_36","unstructured":"Kieling, E.J., Rodrigues, F.C., Filippetto, A., and Barbosa, J. (November, January 29). Smartalloc: A model based on machine learning for human resource allocation in projects. Proceedings of the 25th Brazillian Symposium on Multimedia and the Web, Rio de Janeiro, Brazil."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.future.2021.05.012","article-title":"Research on strong agile response task scheduling optimization enhancement with optimal resource usage in green cloud computing","volume":"124","author":"Shu","year":"2021","journal-title":"Futur. Gener. Comput. Syst."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Chasanidou, D., Elves\u00e6ter, B., and Berre, A.-J. (2016, January 17\u201319). Enabling team collaboration with task management tools. Proceedings of the 12th International Symposium on Open Collaboration, Berlin, Germany.","DOI":"10.1145\/2957792.2957799"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1237","DOI":"10.30574\/wjarr.2025.25.1.0193","article-title":"Optimizing project delivery through agile methodologies: Balancing speed, collaboration and stakeholder engagement","volume":"25","author":"Dugbartey","year":"2025","journal-title":"World J. Adv. Res. Rev."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.jss.2016.03.029","article-title":"Quantitatively measuring a large-scale agile transformation","volume":"117","author":"Olszewska","year":"2016","journal-title":"J. Syst. Softw."},{"key":"ref_41","unstructured":"Speth, S. (2019). Issue Management for Multi-Project, Multi-Team Microservice Architectures. [Master\u2019s Thesis, University of Stuttgart]."},{"key":"ref_42","unstructured":"Zieglmeier, V., and Pretschner, A. (2021). Trustworthy transparency by design. arXiv."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1080\/01930826.2014.903371","article-title":"Improving Strategic Planning by Adapting Agile Methods to the Planning Process","volume":"54","author":"Cervone","year":"2014","journal-title":"J. Libr. Adm."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Nguyen-Duc, A., Cabrero-Daniel, B., Przybylek, A., Arora, C., Khanna, D., Herda, T., Rafiq, U., Melegati, J., Guerra, E., and Kemell, K.-K. (2023). Generative Artificial Intelligence for Software Engineering\u2014A Research Agenda. arXiv.","DOI":"10.2139\/ssrn.4622517"}],"container-title":["Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-8954\/13\/3\/208\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:55:25Z","timestamp":1760028925000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-8954\/13\/3\/208"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,18]]},"references-count":44,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,3]]}},"alternative-id":["systems13030208"],"URL":"https:\/\/doi.org\/10.3390\/systems13030208","relation":{},"ISSN":["2079-8954"],"issn-type":[{"value":"2079-8954","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,18]]}}}