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

Nishant A. Parikh|arXiv (Cornell University)|Jun 5, 2023

Big Data and Business Intelligence20 citations

TL;DR

This paper conducts a systematic literature review (2016–2023) on generative AI in software product management, detailing its applications, benefits, and ethical constraints.

ABSTRACT

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.

Motivation & Objective

• Assess how generative AI can support idea generation, market research, and customer insights in software product management.
• Identify how GAI aids requirements engineering and product development to reduce time and cost.
• Evaluate the reliability, accuracy, and ethical issues associated with applying GAI in product management.
• Synthesize literature from 2016 to 2023 to map practical capabilities and limitations for practitioners.

Proposed method

• Conduct a systematic literature review of relevant articles from 2016–2023.
• Map generative AI applications to software product management activities such as idea generation, market research, and customer insights.
• Analyze benefits including potential time and cost reductions through automatic code generation and feedback analysis.
• Assess constraints related to accuracy, reliability, and ethical considerations.
• Provide a synthesized view of practical implications for software product management.

Experimental results

Research questions

• RQ1 What are the potential applications of generative AI in software product management across the product lifecycle?
• RQ2 What benefits and efficiencies does generative AI offer to software product management activities like development, market research, and customer analysis?
• RQ3 What are the ethical and reliability concerns that arise from deploying generative AI in software product management?

Key findings

• Generative AI can assist in idea generation, market research, customer insights, requirements engineering, and product development.
• GAI has the potential to reduce development time and costs through automatic code generation and customer feedback analysis.
• Despite benefits, issues of accuracy, reliability, and ethics persist in applying GAI to product management.
• Practical application of GAI can improve resource efficiency, product outcomes, and end-user experiences.
• The study provides a comprehensive view of positive impacts and ethical considerations for practitioners.