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AI Product Management
19 Answers
Tamar Hadar
The Knot Worldwide Senior Director of Product • February 2
As a first PM, you will need to be very judicious with how you allocate your time and resources. In fact, I think that’s true for larger companies as well. There are always going to be more ideas than resources available. As a product manager, you are responsible for translating the company’s vi......Read More
9667 Views
1 Answer
Dalit Heldenberg
January 23
Balancing current customer needs with the ever-evolving landscape of AI and technology is a critical facet of effective product management. To achieve this delicate balance, consider the following key strategies: 1. Define Business Goals: * Begin by setting clear business goals for the upcomin......Read More
397 Views
5 Answers
Savita Kini
Cisco Director of Product Management, Speech and Video AI • March 3
Key traits for AI PM is no different from other PM roles -- empathy for customer issues, ability craft / create / articulate problems and how we might approach the solution, industry and domain experience, and collaborative leadership to work with engineering. Willingness to learn or prior experi......Read More
611 Views
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?
5 Answers
Savita Kini
Cisco Director of Product Management, Speech and Video AI • March 2
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
561 Views
3 Answers
Savita Kini
Cisco Director of Product Management, Speech and Video AI • March 3
This is not a simple question. There is no such thing as a "traditional PM" because PM roles and responsibilities differ by industry segment. There are substantial differences in PM roles from consumer app to enterprise app to hardware and enterprise infrastructure. Fundamentally the role of th......Read More
719 Views
1 Answer
Mike Flouton
GitLab VP, Product • January 9
This will be anti-climactic, but my advice is "don't forget you're a PM." Stay laser focused on the customer, their pain and problems and solve the problem. AI is an incredibly powerful tool to solve customer problems, but that's all it is. A tool to solve problems. And it's not always the best t......Read More
570 Views
6 Answers
Savita Kini
Cisco Director of Product Management, Speech and Video AI • March 3
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
367 Views
1 Answer
Mike Flouton
GitLab VP, Product • January 9
For sure. There are certain things AI does really well, and others that humans or traditional deterministic algorithms do better. That sounds obvious, but there's some nuance here that users often miss. At Barracuda, we were the first major email security vendor to market with an AI based appr......Read More
565 Views
5 Answers
Savita Kini
Cisco Director of Product Management, Speech and Video AI • March 3
Seek to understand and clarify first before assuming you have learnt everything that is to know and propose solutions. I see there are lot of online courses, documentation, articles -- you can do a lot of reading online to educate yourself about the complexities of model development, data gathe......Read More
824 Views
3 Answers
Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • June 28
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 it right. It all starts with defining and prioritizing the right scenario/problem to focus on, working with data science and ML ......Read More
830 Views