My question is more to understand if a PM needs to understand the AI concepts to be a successful AI PM?
3 answers
All related (6)
Suhas Manangi
Group Product Manager, AirbnbJune 6

PMs are generally categorised into B2C (Consumer), B2B (Enterprise), Platform, and Product. PMs role is generally 2 of these 4 things. Within this one can also be generalist PM vs domain PM vs growth PM vs scale PM etc. AI PM is the same. One additional categorey can be about building ML Ops platform but I am not convinced one needs a PM for it, or can't be fit into one of the 4 categories described above.

PMs working on Alexa can be AI PMs, but not necessarily TPMs.

Savita Kini
Director of Product Management, Speech and Video AI, CiscoMarch 3

AI/ML by definition requires a decent foundational understanding for AI/ML/Deep Learning Concepts, trends in industry, tools and methodologies to be able to work with engineering in defining solutions to customer /user problems. For the forseeable future, I would say that most AI/ML product managers would likely function as both technical as well as regular product managers to blend user journeys into concrete AL/ML solutions. 

Deepak Mukunthu
Senior Director of Product, AI/ML Platform, DocuSignJune 26

I have seen 4 different types of AI Product Managers:

1. Product focused: Infuse intelligence into products (e.g., search, personalization)

2. Platform focused: Infrastructure & tooling for data scientists and ML engineers to manager ML lifecycle

3. Business/Operations focused: ML to improve product adoption/operations (e.g., customer churn prediction) or business outcomes (e.g., revenue forecasting). This role typically works with data science teams that work on internal optimizations leveraging ML.

4. Research focused: Bringing AI research breakthroughs to market

If you are interested in learning more, watch my session on AI/ML Product Management: