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The ‘Hybrid PM’: Why You Can’t Be Just Product or Just Program in AI/ML Anymore (and How to Nail…
- In the rapidly evolving field of AI, traditional roles need to adapt quickly to deal with learning models, vast data sets, and emerging ethical considerations.
- The emergence of the 'Hybrid PM' role is driven by the complex, iterative, and data-centric nature of AI development.
- AI projects require a continuous scientific approach, making data management crucial as data essentially shapes AI products.
- Continuous operationalization through MLOps ensures that AI models sustain performance, scale effectively, and remain useful.
- AI projects involve various stakeholders like researchers, engineers, data scientists, business professionals, and customers, necessitating effective communication and translation.
- Ethical and responsible AI development is a core requirement, involving mitigating bias, ensuring explainability, and respecting user privacy.
- The 'Hybrid PM' role is about connecting different aspects in a unique way to navigate the challenges of AI effectively.
- To excel as a 'Hybrid PM,' one needs to master both product strategy and program execution skills.
- The blending of Product and Program Management in AI/ML is an essential evolution for managing complex systems and fostering responsible development.
- Developing both product strategy and program execution skills is crucial for future-proofing one's career in the AI field.
- The demand for 'Hybrid PMs' is expected to increase, offering opportunities for leaders to drive impactful change in the AI domain.
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