Last month, we focused on advancing your career in the age of AI, and this month we have a new theme: building your corporate AI strategy. At Emerj, much of our work in the public and private sector is in building an AI strategy and giving organizations data on where the ROI is in the AI world. This week, we speak with Ian Wilson, former Head of AI at HSBC and a research advisor for our banking work. He has rare experience applying AI strategically at one of the largest banks in the world, and I think he is just the person to start off this month's theme. Ian talks about beginning to plan your AI strategy.

This is our final episode in our series on advancing your career in the era of AI this month. We had more Linkedin messages on this theme than any we've done before, and it got me excited to think about what we could do with this kind of series in the future. In this episode, we distill the insights from this month's series with insights from our broad catalog of interviews with AI-minded executives throughout the many years doing this podcast. We also cover three AI-related career roles that do not involve coding.      

We continue our theme on advancing your career in the era of AI. This week, we speak with another AI lead from a gigantic IT services firm: Cognizant. Bret Greenstein is Head of AI at Cognizant, and he talks about what folks who think about AI in terms of strategic direction, project management, etc., have in common. Brett also discusses how non-technical folks can think about AI in order to take on leadership roles in AI projects, including having a firm understanding of what is possible with AI in their industry.

This week, we speak with Sriram Ramanathan, CTO at Genpact, about what the important non-technical roles exist for making AI work in the enterprise. Everything from project management to quality control and beyond, Sriram lists out areas where nontechnical experts play a critical role in bringing AI to life. 

If you're listening to this podcast, you at least have an interest in leveraging AI in the enterprise. But how do you take that interest and use it to move up in your company and advance your career? In this week's episode, we speak with Muriël Serrurier Schepper, who worked with AI at Rabobank and Shell managing advanced analytics projects. She now has her own AI consulting firm. Muriël speaks with us about her experience using her prior skillset to enter the world of AI, take the reigns of exciting AI projects, and open up more career opportunities for herself.

In October, we're focusing on how non-technical employees can still gain an edge in the era of AI even if they've never learned any code. I can't think of a better guest off the bat than our quest this week: Wijay Wijayakumaran, Chief Architect of Machine Learning and AI at IBM Australia. Wijay emphasizes how much stock he places in the critical importance of subject-matter experts and business leaders with domain knowledge. He also runs through possible career opportunities that non-technical employees can look for in the era of AI and questions they can ask to get more involved with AI projects at their organization.

This is the final episode of our series on the ROI of AI. This week is the monthly analyst call, in which Emerj CEO Daniel Faggella breaks down some of the key themes from this month's interviews. In particular, Daniel puts a large emphasis on connecting the dots between near-term and long-term ROI. A lot of these themes and core questions are discussed and answered for clients of our AI Product Development Roadmap services. 

This week, we spoke with David Carmona, the GM of Artificial Intelligence at Microsoft, about his approach to AI ROI with the enterprise clients of Microsoft. The biggest takeaway from this episode comes right at the beginning. David talks about how to think about artificial intelligence ROI in the long-term and the near-term. That is to say, how are we going to see a relatively near-term return with AI that might be able to improve our condition while keeping in mind the longer-term disruption in our industry?

It's clear that there's a revolution in how artificial intelligence is done with neural networks as opposed to the old school systems of the '80s and the '90s. It's clear that hardware is beginning to evolve, and it's also quite clear that the way that we power these hardware systems is going to have to change. GPUs and AI hardware are tremendously power-intensive, and this week we speak with Robert Gendron of Vicor Corporation, a company focused on powering AI systems. Vicor is in partnership with Kisaco Research, which is putting on the 2019 AI Hardware Summit September 17 and 18 in Mountain View, California. Robert speaks about why the way that they are powered needs to be different than traditional manufacturing equipment. He also discusses how the powering of these systems need to work if businesses want to reduce energy costs and be as efficient as they can when it comes to AI.

This week, we have a bonus episode.  We spoke with Jonathan Ross, CEO and Founder of Groq, an AI hardware company, about software-defined computing. Groq is in partnership with the AI Hardware Summit happening in Mountain View, California on September 17 and 18.  Software-defined computing is a way of thinking about how computing can be optimized for machine learning functions. Ross talks about some of the pros and cons of GPUs and where software-defined computing might make its way into future machine learning applications.