Guest: Carlos Escapa – PyTorch Global Business Development Manager, FacebookĬarlos Escapa of Facebook breaks down some of the ways legacy enterprises can learn from AI-first startups.Ĭarlos elaborates on how cultural experimentation and the ability to learn quickly support the best AI companies in converting AI into value. EPISODE 2 – How Culture Separates Top-Performing AI Teams Therefore, finding your most enthusiastic leaders and supporting them in finding the right use cases is a strategy more leaders should deploy. A top-down approach that mandates AI projects, names project leaders, and then presses “play” is, in Seth’s eyes, a very poor approach to fostering AI change.Įncouraging innovation requires channeling enthusiasm. When it comes to fostering AI adoption and building a culture of innovation, leaders need to find internal champions who have the enthusiasm for applying AI and empower them to have their own ideas and discover fruitful AI opportunities. , who explores the “levers” that he’s seen to be effective in improving AI culture.
#LUCIDA SANS UNICODE FONT SERIES#
This series kicks off with IBM ‘s Global Chief AI Officer Seth Dobrin, Ph.D. I’m proud of the amazing guests we lined up, and I hope you’ll enjoy listening to these recordings of each session! AI Culture Change – Advice from the Experts EPISODE 1 – What “Building an AI Culture” Really Involves Be sure to subscribe to the podcast so you receive the latest updates.įor this article and through this series of podcasts, we will highlight salient points and take-home messages from each of these five podcasts, which will help you move the needle on AI culture and achieve AI ROI faster in your enterprise. We’ll be running more series like this in the future and will continue to bring on high-level guests all the way up to global chief AI officers at companies as large as IBM. If you’re not already subscribed to The AI in Business Podcast, be sure to subscribe now on your favorite podcast platforms: We distilled actionable insights from true AI experts.Įvery episode centers on one unifying theme: Culture Change for AI Adoption in the Enterprise.
#LUCIDA SANS UNICODE FONT HOW TO#
In the first week of November for the AI in Business podcast, we met with a series of AI luminaries and discussed how to make AI part of a company’s culture and DNA and how to arrive-faster-at AI ROI. It means setting poor expectations, disappointing leadership, and facing the shut-down of AI projects and initiatives down the road.īut, how-concretely-are AI and IT so different? It comes down to these attributes: To go into AI unprepared means ignoring these differences. Where IT is often predictable, AI sets new predictions. AI means working under a new set of expectations. It’s an entirely new way to work with data, infrastructure, and teams – to open up an entirely new set of capabilities from the ground up. AI is not buying a set of tools for some kind of plug-and-play deployment. More than lack of data science talent, lack of appropriate culture serves as the largest and most consistent barrier to adoption.įor cultures that have spent so long navigating IT deployments, it’s challenging to switch gears and adopt the changes they need to integrate AI.ĪI is not IT. Since then, we have found similar frustrations around enterprise culture in every industry. As far back as 2018 when we surveyed over forty banking industry leaders to discover the biggest issues with AI adoption, enterprise culture was already emerging as top of mind.
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