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What are the different types of AI Product Managers. Are we going to see a role that's similar to a Technical Product Manager focused towards the data science team?
My question is more to understand if a PM needs to understand the AI concepts to be a successful AI PM?
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 p......Read More
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 plat......Read More
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 manag......Read More
I think at an even higher level we will actually see at least 3 different approaches to AI product management even in the organization structure itself (not necessarily mutually exclusive): * Dedicated AI PMs: Absolutely, more and more companies with dedicated AI product managers * Po......Read More
Related Ask Me Anything Sessions
Gong Director of Product, Rapha Danilo on AI Product Management
April 27 @ 11:00AM PST
DocuSign Senior Director of Product, AI/ML Platform, Deepak Mukunthu on AI Product Management
June 28 @ 10:00AM PST
Airbnb Group Product Manager, Suhas Manangion AI Product Management
June 7 @ 10:00AM PST
Metrics are an interesting question. This really depends on the type of product we are building that leverages ML. Since ML can be use for example in electronic records, sales workflows, computer vision type use cases or speech / audio use cases some of which I am familiar with -- we can break it......Read More
Trust & Risk is a specific domain, so generalist PM would need to pivot to become a domain PM. This will require launching solutions across multiple years. Fraud evolves every year, but over 90% still remains the same decade long type. Payment Risk is a good stepping stone. Balacing security with......Read More
Assuming you are specifically interested in AI product management, I would suggest these approaches to get started with ML. While I was new to ML/AI, these approaches helped me. 1. Online courses 2. Part-time certifications 3. Conferences 4. Kaggle 5. Publish your work 6. Internship/Volunte......Read More
The first challenge is actually self-imposed by product teams. Ask yourself: are we implementing an ML feature mostly because of FOMO / not wanting to "fall behind", or because of a first-principled, customer-first assessment of need/opportunity? Assuming we've identified a real need/opportunity......Read More
What metrics do ML product teams look at to define success? Which do you find to be the most important?What are the key skills one should target to learn to grow in Trust & Risk , as a Product Manager ?Hard to notice that Product Management interviews require a ton of practice! Any resources for budding/ aspiring Product Managers ? Alternatively, any platforms that you are aware of, where folks can get Prod Mgmt experience by enrolling in projects?What are the challenges in implementing an ML feature in a product? who takes the decision to determine what type of ML feature would help the product and how to solve the problem related to it? How closely AI PM works with Data scientists?