What are some of the key skills and competencies that product leaders need in order to effectively manage AI in their organizations?
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Product leaders should evaluate how to apply AI in their products to create value for the customer. This could mean improving processes, developing innovative products, or enhancing the customer experience. These goals should align with our business objectives and customer needs. Prioritizing these AI use cases is crucial to the success of building the product.
While a product leader doesn't need to be an AI expert, it's beneficial to have a solid understanding of the fundamentals to effectively communicate with their teams. This includes concepts like machine learning, data training, and natural language processing.
I agree with Karen. The first key skill is understanding the business value of AI. We're not just implementing AI for the sake of it, there needs to be a tangible benefit such as cost reduction, revenue generation, or improved customer experience.<br><br>Secondly, understanding the characteristics of the use case is important. AI excels at complex or repetitive tasks, so identifying opportunities for pattern recognition or anomaly detection is crucial.<br><br>Lastly, data is key. High-quality data is needed to train and deploy AI models. As an organization, you need to have access to this data in the right quantities and be able to trust it.<br><br>
The value of understanding user journeys is crucial. AI can deliver value today by sifting through large quantities of data, much more than a human can, and providing plausible outputs.
One common use case we all use, not just in product management but in business, is for AI to transcribe calls. Using AI in this basic manner and then sending that transcript to someone who calls your call center is something we've tried.
The power of connected data is now amplified orders of magnitude. It's reached a point that was unimaginable 10 years ago, leading to issues around data ownership and use for training purposes. Product leaders need to be aware of these issues to avoid potential pitfalls with AI.