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?
3 Answers
Salesforce Senior Director of Product, Agentforce AI Platform • 3y
While infusing ML into a product can be extremely powerful to light-up new scenarios for customers and to optimize current scenarios, it can take a lot of effort to get i...
1413 Views
Gong GM / Sr Director of Product • 3y
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 b...
1159 Views
Cisco Director of Product Management, Speech and Video AI • 3y
Implementing an ML feature vs a non ML feature is no different. The complexity is how the ML model is integrated into the existing product, business or user workflows, an...
252 Views
Related Questions
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?Who is better suited for an AI product management role compared to a traditional pm role?How is it possible that in this age of AI,wherein AI is far more capable enough to present different solutions to a problem,the role of PM in the Solutioning stage of Product Development cycle remains relevant?What level of hard/technical skills should someone aim to develop to thrive as an AI product manager?How do you see AI changing the way product teams collect and interpret user feedback in real time?What are the key traits you look for in hiring AI Product Managers?