
Your playbook for making AI real, practical, and valuable.
Jie Tao, DSc, an associate professor of business analytics and the director of the AI and Technology Institute at Fairfield University’s Charles F. Dolan School of Business, provides listeners with a practical guide to mastering AI for real results.
Each episode delivers actionable tools, proven frameworks, and real-world case studies to help leaders and innovators leverage AI for business growth and career success. Explore topics from the Practical AI Playbook to insights from Fairfield Dolan's AI and Tech Institute and discover powerful AI applications shaping the future.
Your playbook for making AI real, practical, and valuable.
Jie Tao, DSc, an associate professor of business analytics and the director of the AI and Technology Institute at Fairfield University’s Charles F. Dolan School of Business, provides listeners with a practical guide to mastering AI for real results.
Each episode delivers actionable tools, proven frameworks, and real-world case studies to help leaders and innovators leverage AI for business growth and career success. Explore topics from the Practical AI Playbook to insights from Fairfield Dolan's AI and Tech Institute and discover powerful AI applications shaping the future.
Episodes
Jul 29, 2026
The Syllabus Broke, the Students Didn't - Ep. 14
Jul 29, 2026
Jul 29, 2026
41 min
Dr. Philip Maymin and Dr. Jie Tao — analytics professors at Fairfield Dolan, where Tao directs the AI and Tech Institute — host the first graduates of the MS in Business Analytics and AI to appear on the show: Margarida Sacouto and Sheila Green. Tao's course ran on one stubborn premise: you shouldn't have to change how you work because of AI. AI is here to help, not the other way around.
Then Tao rewrote the course mid-semester — the first time in his career — because a real client materialized. Synchrony Financial's regulated core business was off-limits by design, so students who signed up to automate their own cover letters were suddenly consulting for a Fortune 100 analytics function. Green's group, the youngest in the room and the most AI-native, decided they were the least technical and shipped anyway.
Cleaning data eats 50 to 80% of any analytics project, so Sacouto's team deliberately corrupted a credit-card dataset and built an agentic skill that cleaned it while logging every decision with a confidence score. Green's team piped it into compliance documentation. The two projects chained end to end by accident — vindicating Tao's insistence that spec-driven development was never spec-driven coding.
"Hallucination is a feature, not a bug." Results and the spec-driven deep dive land in the next episode.
