Remove Experimentation Remove Management Remove Testing
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Practical Skills for The AI Product Manager

O'Reilly on Data

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products. The AI Product Pipeline.

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What you need to know about product management for AI

O'Reilly on Data

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools.

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AI Product Management After Deployment

O'Reilly on Data

The field of AI product management continues to gain momentum. As the AI product management role advances in maturity, more and more information and advice has become available. One area that has received less attention is the role of an AI product manager after the product is deployed. Debugging AI Products.

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88% of AI pilots fail to reach production — but that’s not all on IT

CIO Business Intelligence

The proof of concept (POC) has become a key facet of CIOs AI strategies, providing a low-stakes way to test AI use cases without full commitment. IT managers are leveraging this trend to try to get greenlights for broader technology efforts, Andersen says.

ROI 127
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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

Weve seen this across dozens of companies, and the teams that break out of this trap all adopt some version of Evaluation-Driven Development (EDD), where testing, monitoring, and evaluation drive every decision from the start. What breaks your app in production isnt always what you tested for in dev! The way out?

Testing 174
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Digital transformation 2025: What’s in, what’s out

CIO Business Intelligence

Transformational CIOs continuously invest in their operating model by developing product management, design thinking, agile, DevOps, change management, and data-driven practices. CIOs must also drive knowledge management, training, and change management programs to help employees adapt to AI-enabled workflows.

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10 AI strategy questions every CIO must answer

CIO Business Intelligence

The time for experimentation and seeing what it can do was in 2023 and early 2024. Its typical for organizations to test out an AI use case, launching a proof of concept and pilot to determine whether theyre placing a good bet. These, of course, tend to be in a sandbox environment with curated data and a crackerjack team.

Strategy 141