AI Product Management Articles You Might Have Missed So Far
A Selection of My Past Insights and Essential Reads
#beyondAI
I regularly review my articles to find inspiration for new topics and critically assess their continued relevance. As my views and knowledge evolve, it's important for me to understand how aspects of AI Product Management (AIPM) have changed over time. For example, with the maturation of AI technologies like GenAI, the role of an AIPM must also evolve. This is worth an article on its own!
Today, I've prepared some of my past articles for you. You might have missed them if you recently joined my newsletter or simply because life happened.
Happy reading 🛋️
Why We Need a Curated Learning Repository for AI Product Managers
In my career as an AI Product Manager, I've found navigating the vast and constantly evolving landscape of AI resources challenging. Many professionals struggle to find reliable, comprehensive learning materials. To address this, I proposed creating a curated learning repository for AI Product Managers, which received enthusiastic support from my LinkedIn community. This initiative aims to provide a well-rounded educational resource to help AI Product Managers develop their skills effectively. Read the full article to learn more about this exciting project and how you can contribute.
Why AI Projects Fail and How to Fix Them (Based on Research)
Despite significant investments, many AI projects fail to deliver expected results. Based on extensive research, this article explores the key reasons behind these failures, such as unrealistic expectations, lack of understanding of business needs, and inadequate resources. It also highlights the crucial role of AI Product Managers in addressing these challenges and ensuring project success. For aspiring AI Product Managers, practical steps to enter and excel in this field are outlined. Click to read the full analysis and discover how AI Product Management can make a difference.
AI Products are Incomplete without Data Products
AI products are part of a larger value chain that requires robust data products to succeed. As the industry increasingly focuses on AI Product Managers (AIPMs), it's crucial to also recognize the importance of Data Product Managers (DPMs). While AIPMs manage AI solutions, DPMs ensure data quality, strategy, accessibility, and alignment with business goals. The collaboration between these roles is essential for the success of AI initiatives. But which should come first? The answer depends on the context and the company's strategy. Read the full article to explore this dynamic and find out why DPMs are AIPMs' best allies.
The Double Trio Framework for AI Product Management
Aspiring AI Product Managers often struggle with where to start and how to manage the complexities of AI product development. To address this, I developed the Double Trio Framework, which balances technical and operational elements essential for successful AI products. The framework includes the Technical Trio (Data, IT, AI) and the Operational Trio (Governance, Business, People). This approach ensures comprehensive coverage of all critical aspects, from data quality and infrastructure to ethical governance and user experience. Click to explore how this framework can guide your AI initiatives and learning path.
The Declining Era of Data Science Teams as Mere Service Providers
Many in-house Data Science teams operate as service providers, focusing on delivering outputs rather than outcomes. This model often leads to underutilized AI solutions and highlights the need for AI Product Managers (AIPMs). Without an AIPM, AI teams risk delivering technically sound but practically irrelevant products. An example from a fintech firm illustrates how introducing an AIPM can bridge the gap between technical teams and business needs, leading to more impactful and user-friendly AI solutions. The era of treating Data Science teams as mere service providers is ending. Click to learn why delivering true AI products is crucial for business value.
I hope you find these articles insightful and helpful on your journey in AI Product Management. Life gets busy, and it’s easy to miss some content. I think I will make this a new habit to regularly post past articles. I hope that helps you as much as it does for me.
JBK 🕊️
P.S. If you’ve found my posts valuable, consider supporting my work. While I’m not accepting payments right now, you can help by sharing, liking, and commenting here or on my LinkedIn posts. This helps me reach more people on this journey, and your feedback is invaluable for improving the content. Thank you for being part of this community ❤️.