Survival Guide to AI Product Management

Abstract: 

Today’s digital enterprise architecture aims to efficiently scale business through technology and AI products are taking the center stage in that transformation.

However managing AI products become extremely challenging for many organizations as it sits at the intersection of cross-functional efforts such as infrastructure, data architecture and governance, application distribution and delivery while baking automation, observability, and SRE capabilities into it.

Even if you get the technicals right, delivering business value through AI is still difficult as you need to integrate these technologies into decision-making processes and work your way through internal resistance and gain stakeholder buy-in early in complex operational environments.

Moreover, a lack of skills for managing the product life cycle prevents most of AI initiatives from making it into the production.

To thrive in this new world, you need to understand the depth and breadth of technology stack, underlying supporting architectures, design choices,organizational structure and processes.

In this talk, Umit will explain how AI product development differs from software development and how should you embrace the produc management within the context of AI products.

By the end of this talk, you will feel comfortable with the probabilistic nature of such initiatives rather than staying in the comfort zone of the deterministic environment of traditional software development.

In the last section, Umit will also present several case studies to share practical tips and guidance.

Bio: 

Umit excels at shipping ML products to production in complex IT and business environments.Before joining EPAM, he held roles as a researcher, software engineer, data scientist, ML engineer, manager, and technical leader. He worked at massive engineering companies as well as ambitious start-ups, consulted for Fortune 500 companies, and taught graduate courses in computer science and engineering.

Umit’s research spans multiple disciplines, and he enjoys sharing his insights at conferences, universities, and meet-ups. He's also regularly coaching and mentoring newcomers and university students to make their career dreams come true while having a fulfilling life.

Open Data Science

 

 

 

Open Data Science
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Cambridge, MA 02142
info@odsc.com

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