Generative AI Augmented Product Management from a Systematic Literature Review (V5)
Hello Vitor,
Thank you for your email. Apologies for taking a few days to respond. Monday and yesterday I was swamped and didn’t have the time to look at your paper. Today wasn’t much better, but I saw your ping on WhatsApp.
Overall, well done on pulling the paper together. It’s not an easy topic as PM is quite broad and touches many different industries. I thought I’d share a few thoughts for you to noodle on until we have a chance to meet online:
- Research questions: I think the RQs are in the right direction, but I think we need to discuss these to sharpen them a bit further. For instance, I would invert RQ1 along the lines of “Which product management activities have the highest potential to be addressed by GenAI.
- I leave it to Helena to comment on the research method, but it seems quite long in its description.
- Results: the descriptive part is a bit “straightforward” and doesn’t really offer much news beyond some numbers. Is there more we can say about it?
- Can we draw conclusions based on a single study or should we aim to have it confirmed by multiple?
- Can we bring structure in thematic analysis? For instance, the topics on “personas” are quite related in my view and largely cover the customer part.
- Also, the topics are quite high level, e.g. “GenAI for Continuous Improvement” and “LLM-Driven Feature Competitor Analysis” seem quite generic in my view. Can we go one or two levels deeper?
- Unexplored areas: There is a concept called MECE: Mutually Exclusive; Collectively Exhaustive. How do we create a sense of MECE for these topics? It reads a bit as a laundry list.
These are my current comments that I was hoping you could work on a bit until Monday. If you’re able to join the meetings then, we can discuss in more detail.
Finally, please don’t feel bad about the feedback. Overall it’s a really good job. I am trying to get the paper to an even higher level.
Thanks,
1
Research questions: I think the RQs are in the right direction, but I think we need to discuss these to sharpen them a bit further. For instance, I would invert RQ1 along the lines of “Which product management activities have the highest potential to be addressed by GenAI.
RQ1 - What are the existing GenAI use cases that augment product management?
RQ2 - How does the future of AI-augmented product management look?
RQ3 - From the evaluated use cases, what crucial challenges and considerations emerged for maximizing their potential and potentially improving preparation for future use cases?
2
leave it to Helena to comment on the research method, but it seems quite long in its description.
3
Results: the descriptive part is a bit “straightforward” and doesn’t really offer much news beyond some numbers. Is there more we can say about it?
4
Can we draw conclusions based on a single study or should we aim to have it confirmed by multiple?
5
Can we bring structure in thematic analysis? For instance, the topics on “personas” are quite related in my view and largely cover the customer part.
5
Also, the topics are quite high level, e.g. “GenAI for Continuous Improvement” and “LLM-Driven Feature Competitor Analysis” seem quite generic in my view. Can we go one or two levels deeper?
6
Unexplored areas: There is a concept called MECE: Mutually Exclusive; Collectively Exhaustive. How do we create a sense of MECE for these topics? It reads a bit as a laundry list.