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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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| Paper Title: | AI-Enabled Sentiment Analysis for Agile Retrospectives: Enhancing Continuous Improvement through Predictive Insights |
| Authors Name: | Ullas Das |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_205067
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| Published Paper Id: | IJRTI2506211 |
| Published In: | Volume 10 Issue 6, June-2025 |
| DOI: | https://doi.org/10.56975/ijrti.v10i6.205067 |
| Abstract: | The following paper provides an in-depth study of integration of Artificial Intelligence (AI) into Agile retrospectives with the view towards sentiment analysis to enable continuous improvement. Agile retrospectives remain one of the vital practices in the Agile methodology and allows groups to examine their practices and pinpoint areas that need refinements. Nonetheless, the traditional retrospectives have weaknesses which include biases, small amounts of data and subjectivity of it. In this review, I suggest an AI-based sentiment analysis solution that would combine various information sources such as communication channels, project management systems, and code controls in order to provide more precise and context-sensitive information. Not only does the model analyze the sentiments in a historical light but also uses predictive analytics to determine how the issues may play out in the future, and teams use this as an opportunity to solve problems ahead of time. The model also proves to be more accurate, precise, and predictive than the baseline methods since it shows similar outcomes to a comparative study of the model performance. Implications to practitioners and policymakers are put across in their ability to leverage decision-making and make it more effective as well as through team work and effective risk management with this model. Possible areas of further research are described, and it is proposed to conduct longitudinal research, address the considerations related to ethics, and expand the application of the model to incorporate cross-industry opportunities to enhance the capabilities of the model further and regulate its appropriate application in Agile. |
| Keywords: | AI in Agile, Sentiment Analysis, Agile Retrospectives, Continuous Improvement, Predictive Analytics, Data Integration, Agile Tools, Team Collaboration, Risk Management, Machine Learning, AI Ethics, Agile Methodology, Feedback Analysis |
| Cite Article: | "AI-Enabled Sentiment Analysis for Agile Retrospectives: Enhancing Continuous Improvement through Predictive Insights", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.c79-c89, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506211.pdf |
| Downloads: | 000524 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2506211
Registration ID:205067
Published In: Volume 10 Issue 6, June-2025
DOI (Digital Object Identifier): https://doi.org/10.56975/ijrti.v10i6.205067
Page No: c79-c89 Country: Chennai, Tamil Nadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2506211 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2506211 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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