"For an economist, you're not so dumb," I was once told by an engineer. I don't think it's possible to receive a better compliment than that.I have a total of 10 years of hands-on experience building data and AI solutions within various sectors, and 8 of those have been spent spearheading data science initiatives in the retail industry. I have 3 years of experience managing data scientists (up to 8), and 1 year of experience managing other data science managers (up to 2). I have been responsible for hiring 24 data scientists throughout my career, and I’ve also built two MLOps platforms from the ground up.While I love to challenge myself to be deep in the code on one day and thinking, leading, managing or recruiting on the next, for the better part of the last 3 years I have found the most satisfaction in doing AI strategy and business development work in order to make the ground fertile for building and launching true AI-first products.I believe the best is yet to come in the world of AI. The technology required to build significantly more transformative AI solutions than we see today already exists; solutions that have the potential to improve our lives by making us better at things we want to be good at, and automating the things we don't really want to do.What's missing are products, services, organizations, and processes built in an AI-first way. What does AI really do? It makes predictions. And there are way more prediction problems out there than you think. Organizations that are adept at recognizing these problems in their core business and value proposition, and rig themselves to systematically solve them in a way that continuously creates useful and value-generating intelligent products and services, will attain powerful competitive advantages. Many AI projects have failed with the realization that AI was not the answer, but that is only because nobody was asking the right question.Succeeding with AI has just as much to do with strategy, product, and design thinking as it has to do with algorithms. AI is not inherently an "analytics/insights thing," or even a "data thing." It is first and foremost a product thing and a business thing. But it is still only by thinking about data and algorithms first - before we even begin - that we can efficiently build intelligent, self-learning products. My passion lies in paving the way for building these products, which requires me to walk the lines between visionary and pragmatic, thinking and doing, and humble and bold.