Becoming an AI Product Manager: The Essential Guide
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Understanding AI in Product Management
The role of a product manager (PM) has evolved with the emergence of Artificial Intelligence (AI). Today, those managing products that incorporate AI technologies often refer to themselves as “AI PMs.” As AI continues to dominate discussions across industries and platforms like LinkedIn, it’s crucial to understand how the responsibilities of an AI PM differ from those of a traditional PM.
While many PM positions may not explicitly include “AI” in their titles, AI-related responsibilities are frequently outlined in their job descriptions. However, this does not necessarily elevate the status of PMs working in AI. The distinction primarily rests on the specific software techniques and tools they utilize.
The Role of Product Managers
PMs are responsible for defining the mission and vision of their products by collaborating with various teams and crafting strategies for success, all while navigating risks and challenges. Products can take many forms, including:
- Web technologies (browsers, extensions, etc.)
- Desktop applications (GUIs)
- Mobile applications
- Web applications (platforms with user-engaging features)
- APIs
- Web3 technologies
- Robotics
AI can enhance any of these categories. For instance, machine learning (ML) models can be integrated into various products, while robotics fundamentally depend on AI for their decision-making processes. Even platforms like ChatGPT, which utilize complex large language models (LLMs), are hosted on straightforward web applications.
An AI PM, therefore, is someone who manages any product that leverages AI technologies to optimize success. During collaboration with engineering teams, they can apply their expertise in AI to discussions about:
- Capacity: What is the GPU usage per input query?
- Priority: How long will it take to complete our model, and what are the success metrics?
- Brainstorming: Which new features can be enhanced with AI for improved user experience and profitability?
However, it’s important to note that any PM—regardless of AI use—should engage in these discussions. Not incorporating AI into a product doesn’t automatically diminish its value or the PM's career prospects.
Evaluating Product Needs
The necessity of AI in a product depends on its specific context. The Viability, Feasibility, and Desirability framework, popular among PMs and UX designers, emphasizes essential pillars for product success, where AI is merely a tool and not the focal point. Ultimately, the product's value is paramount; without it, AI integration may be futile.
For instance, if you aim to create an AI tool for generating digital pixel art, you may face significant competition, with numerous existing products offering similar features. Targeting a niche market with high-value problems can increase the chances of success.
As AI becomes increasingly integrated into various technologies, its prominence in product discussions is understandable. This trend will persist as AI drives innovation in features such as recommendation systems, targeted advertising, chatbots, and personalized customer support.
The Future of AI and Product Management
Looking ahead, the impact of AI on product management will likely grow. Nonetheless, the role of the PM will remain vital, with or without AI involvement.
The first video titled "The ONLY 4 Ways to Become an AI Product Manager with No Experience" offers insights into how to enter the field of AI product management without prior experience.
The second video, "How to Break into AI Product Management without Experience," provides valuable tips for aspiring AI PMs.
About the Author
My name is Kasey, also known as J.X. Fu (my pen name). I am passionate about writing and often find myself creating novels during my evenings while working full-time as a tech PM.
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