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AI-powered Scrum: A systematic literature review of the current trends and the state-of-the-art of Artificial Intelligence capabilities in agile project management
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2024 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The establishment of agile methodologies revolutionised project management with flexibility and teamwork. Alongside technological advancements, organisations have increased their investments in Artificial Intelligence for project management. Currently, there is a lack of knowledge about AI capabilities in agile project management which are presented in the context of a framework to guide practitioners. At present the most popular agile framework is Scrum. This research addresses the problem with comprehensive documentation about the insights from existing literature regarding the current trends and state-of-the-art of AI capabilities in agile project management and presenting them in the context of Scrum. Thus, the following research question was developed: “What insight can be derived from the existing literature about AI and agile project management in relation to the Scrum framework?”. To ensure a comprehensive and contemporary research due to the technological advancements in the field of AI, the research was delimited to articles published between the years 2018 to 2024. This research used a systematic literature review as a research strategy and directed content analysis for the analysis of the collected secondary data. The PRISMA framework with inclusion and exclusion criteria, categories and keywords was applied to systematically assess the eligibility of the collected data and to ensure transparency. The results reveal various trends with AI capabilities of identification, classification, automation, estimations and recommendations throughout the different phases of the Scrum framework. The research concluded the importance of having a repository of detailed historical project data for accurate estimations and forecasts to ensure a competitive advantage.

Place, publisher, year, edition, pages
2024.
Keywords [en]
Agile methodology, Agile project management, Artificial Intelligence, Scrum
National Category
Information Systems
Identifiers
URN: urn:nbn:se:su:diva-242641OAI: oai:DiVA.org:su-242641DiVA, id: diva2:1955532
Available from: 2025-04-30 Created: 2025-04-30

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Campoverde Morales, Melina
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf