[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-250363-105":53,"doc-detail-250363-en":127},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":120,"head_meta":122,"extra_data":124,"updated_unix":126},105,"en","using-gpt-to-build-a-project-management-assistant-for-jira-environments-read-online","Using GPT to build a Project Management assistant for Jira environments - read online","","Project management teams face sustained difficulty due to the high volume and diversity of project data, spanning timelines, budgets, and task dependencies. Efficient control from initiation to completion depends on tools that streamline communication, optimize resource allocation, and support real-time, evidence-based decisions. Existing approaches often require steep learning curves and complex programming to extract the needed information. This work introduces JiraGPT Next, a Jira add-on that uses GPT Large Language Models with a natural-language interface to retrieve project information via APIs and OpenAI models. It presents design decisions and evaluates GPT accuracy under different prompts.",{"@graph":63,"@context":119},[64,80,102],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":11,"@type":70,"position":76},"https://docshare.wps.com/template/presentations/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/using-gpt-to-build-a-project-management-assistant-for-jira-environments-read-online/250363/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/using-gpt-to-build-a-project-management-assistant-for-jira-environments-read-online/250363.png","ImageObject",442,249,{"name":88,"@type":89},"Connor ","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-19","2026-09-12",true,{"@type":98,"interactionType":99,"userInteractionCount":101},"InteractionCounter",{"@type":100},"ViewAction",9,{"@type":103,"mainEntity":104},"FAQPage",[105,111,115],{"name":106,"@type":107,"acceptedAnswer":108},"What problem does the paper address in project management?","Question",{"text":109,"@type":110},"Project managers must handle large volumes of diverse data such as timelines, budgets, and task dependencies. 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SE] 30 Sep 2025  \nUsing GPT to build a Project Management assistant for Jira  \nenvironments  \nJoel Garcia-Escribano 1 , Arkaitz Carbajo2a , Mikel Ega˜na Aranguren3b , and Unai Lopez-Novoa3c  \n1Accenture, Bilbao, Spain  \n2 LKS Next GobTech, Bilbao, Spain  \n3 University of the Basque Country UPV/EHU, Bilbao, Spain  \n[joel.b.garcia@accenture.com](joel.b.garcia@accenture.com), [arkaitz.carbajo@gobtech.lksnext.com](arkaitz.carbajo@gobtech.lksnext.com), {mikel.egana, [unai.lopez](unai.lopez}@ehu.eus)[}](unai.lopez}@ehu.eus)[@ehu.eus](unai.lopez}@ehu.eus)  \nKeywords: Intelligent Decision Making, LLM, Jira, GPT, Prompt Engineering, Project Management.  \nAbstract: In the domain of Project Management, the sheer volume of data is a challenge that project managers continually have to deal with. Effectively steering projects from inception to completion requires handling of diverse information streams, including timelines, budgetary considerations, and task dependencies. To navigate this data-driven landscape with precision and agility, project managers must rely on efficient and sophisticated tools. These tools have become essential, as they enable project managers to streamline communication, optimize resource allocation, and make informed decisions in real-time. However, many of these tools have steep learning curves and require using complex programming languages to retrieve the exact data that project managers need. In this work we present JiraGPT Next, a software that uses the GPT Large Language Model to ease the process by which project managers deal with large amounts of data. It is conceived as an add-on for Jira, one of the most popular Project Management tools, and provides a natural language interface to retrieve information. This work presents the design decisions behind JiraGPT Next and an evaluation of the accuracy of GPT in this context, including the effects of providing different prompts to complete a particular task.  \n1 Introduction  \nIn the evolving landscape of Project Management, the confluence of artificial intelligence and task management platforms has become a focal point for driving efficiency and enhancing decision-making processes (Auth et al., 2021; Taboada et al., 2023) . Jira 1 , developed by Atlassian, stands out as an industry-standard tool that enables teams to plan, track, and manage agile software development projects. However, despite its comprehensive feature set, Jira users often encounter challenges in navigating complex workflows, managing growing backlogs, and maintaining clear communication across tasks and team members.  \nAs the velocity of software development accelerates and the volume of tasks within projects proliferates, the need for intelligent automation within Project Management tools becomes increasingly paramount. The deployment of AI in this domain  \na [https://orcid.org/0000-0003-0904-4627](https://orcid.org/0000-0003-0904-4627)  \nb [https://orcid.org/0000-0001-8081-1839](https://orcid.org/0000-0001-8081-1839)  \nc [https://orcid.org/0000-0002-2707-8946](https://orcid.org/0000-0002-2707-8946)  \n1 [https://www.atlassian.com/software/jira](https://www.atlassian.com/software/jira)  \nhas predominantly focused on predictive analytics for project outcomes or robotic process automation for task completion. However, these applications have not fully leveraged the potential of AI to interact with users in a natural and contextually relevant manner. The advent of sophisticated language models such as GPT (Brown et al., 2020) offers an untapped opportunity to address this gap (Nuhn et al., 2022) .  \nThis paper presents JiraGPT Next, a prototype of a GPT-based intelligent assistant for Jira environments. The aim is to provide a natural language interface by which managers can retrieve precise information about their projects in a seamless manner, hiding the complexities of Jira. Our software retrieves information from Jira database through its API and uses OpenAI’s pub","cbCaia7S03OYKlWr","https://ap.wps.com/l/cbCaia7S03OYKlWr","pdf",390316,"English","# Introduction\n## Background\n### LLMs\n### Project Management","[{\"question\":\"What problem does the paper address in project management?\",\"answer\":\"Project managers must handle large volumes of diverse data such as timelines, budgets, and task dependencies. The paper highlights that steering projects effectively requires precise and agile information handling.\"},{\"question\":\"What is JiraGPT Next?\",\"answer\":\"JiraGPT Next is a Jira add-on that uses a GPT Large Language Model to provide a natural-language interface for retrieving project information from Jira through its API.\"},{\"question\":\"How does the paper evaluate the system?\",\"answer\":\"The evaluation focuses on measuring GPT accuracy in this context and analyzing the effects of using different prompts for completing a specific task.\"}]","Using GPT to build a Project Management assistant for Jira environments - read online | PDF",1789254723]