Originally published in Forbes, June 11, 2024. If you’ve ever had a data scientist make a machine learning model for you, you probably first experienced excitement, followed by bewilderment. The potential power is awesome. In its enterprise application, predictive AI is the antidote to information overload. Too many prospective customers? Use a predictive model to prioritize them […]

 Originally published in Forbes, March 4, 2024. Which kind of AI should companies focus on—generative AI, which produces writing, computer code, images, video and other content, or predictive AI, which targets ads, marketing, fraud detection, risk management, healthcare treatment and other established operations? Those posing this question may be missing the point—similar to when someone […]

 Originally published in Forbes, March 25, 2024. To do its job, AI needs your help. It has the potential to drive millions of operational decisions—such as whom to contact, approve, investigate, incarcerate, set up on a date or medicate. But there’s a critical project step that’s often overlooked: Choosing the decision threshold, a single number […]

 Originally published in Forbes, April 10, 2024 When OpenAI’s board momentarily ousted Sam Altman from his post as CEO last November, the media obsession was… intense. Why so much fuss about a corporate drama? The public mania—and perhaps the ousting itself—came in no small part from a widespread belief that the company is well on […]

 Originally published in KDnuggets. Eric Siegel highlights the chronic under-deployment of ML projects, with only 22% of data scientists saying their revolutionary initiatives usually deploy, and a lack of stakeholder visibility and detailed planning as key issues, in his industry survey and book “The AI Playbook.” How often do machine learning projects reach successful deployment? […]

    This article from Morgan Vawter, Global Vice President of Data & Analytics at Unilever, serves as the foreword to The AI Playbook: Mastering the Rare Art of Machine Learning Deployment, by Eric Siegel. Morgan will present a keynote at Machine Learning Week, June 4-7, 2024 in Phoenix, AZ – where registrants will receive […]

 Originally published in Harvard Business Review Machine learning might be the world’s most important general-purpose technology, but it’s notoriously difficult to launch. Outside of Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What’s missing? A specialized business practice suitable for wide adoption. This article […]