# Empowering Business Transformation: The Positive Impact and Ethical Considerations of Generative AI in Software Product Management -- A Systematic Literature Review

arXiv: https://arxiv.org/abs/2306.04605 · HTML: https://mlsanity.com/paper/2306.04605/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 34 references that are in the map.
- First posted on arXiv 5 Jun 2023.

## Builds on (most cited first, 7 of 7)

- [Scaling Laws for Autoregressive Generative Modeling](https://mlsanity.com/paper/2010.14701/) (2020)
- [The Impact of AI on Developer Productivity: Evidence from GitHub Copilot](https://mlsanity.com/paper/2302.06590/) (2023)
- [A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT](https://mlsanity.com/paper/2303.04226/) (2023)
- [Regulating ChatGPT and other Large Generative AI Models](https://mlsanity.com/paper/2302.02337/) (2023)
- [Automatic Code Documentation Generation Using GPT-3](https://mlsanity.com/paper/2209.02235/) (2022)
- [Supervised Semantic Similarity-based Conflict Detection Algorithm: S3CDA](https://mlsanity.com/paper/2206.13690/) (2022)
- [Towards effective AI-powered agile project management](https://mlsanity.com/paper/1812.10578/) (2018)

## Abstract (arXiv)

Generative Artificial Intelligence (GAI) has made outstanding strides in recent years, with a good-sized impact on software product management. Drawing on pertinent articles from 2016 to 2023, this systematic literature evaluation reveals generative AI's potential applications, benefits, and constraints in this area. The study shows that technology can assist in idea generation, market research, customer insights, product requirements engineering, and product development. It can help reduce development time and costs through automatic code generation, customer feedback analysis, and more. However, the technology's accuracy, reliability, and ethical consideration persist. Ultimately, generative AI's practical application can significantly improve software product management activities, leading to more efficient use of resources, better product outcomes, and improved end-user experiences.