Chicago Data Night: Dr. Alan Keahey (Epsilon)

Please join us for our monthly Chicago Data Night, cohosted by Drive Capital, ChiData and the DSI, Practitioners, academics, and aficionados within the Chicago area are all invited to be part of a community at the intersection of industry and academia, brought together by a mutual interest in data. Each month, guest speakers will cover a specific data-related topic.

Hors d’oeuvres and drinks will be provided. Admission is free, and we strongly encourage an RSVP to attend.

Meeting Location
Drive Capital, Fulton East Building
215 N Peoria St
Chicago, IL 60607

AGENDA
5:30pm: Networking Reception
6:00pm: Welcome Remarks
6:05pm: Guest Speaker
6:50pm: Q&A
7:00pm: Networking Reception
7:30pm: Event Concludes

Talk Title: The Intelligence Cube: When Technology Changes Faster Than You Can Hire

Abstract: The data and AI landscape is fragmenting into ever-more specialized disciplines—data engineering, ML ops, prompt engineering, systems architecture, visual analytics—while simultaneously, AI tools are making it possible for individuals to work across more areas than ever before. This creates a paradox: do you organize for deep specialization or broad versatility? The Intelligence Cube framework maps essential capabilities across two layers (platform and experience) and reveals a surprising pattern: organizations that can integrate multiple capabilities consistently outperform pure specialists in rapidly evolving technical domains. Drawing on lessons from building and scaling a multidisciplinary analytics organization, this talk explores how to think about organizational capability as a coordinate system rather than an org chart, why the familiar hub-and-spoke model breaks down for cutting-edge tech, and what structures actually work when technology changes faster than you can hire specialists.

Bio: Dr. Alan Keahey believes the future of data-driven intelligent interfaces belongs to adaptive organizations—not monoliths with rigid specialization. As Vice President of AI & Visual Analytics at Epsilon, he's built a multidisciplinary group that has to reinvent itself constantly to keep up with petabyte-scale marketing data challenges. His unconventional career path—Ph.D. researcher at Los Alamos and Indiana University, multiple startups, IBM Watson architect, Fortune 500 consultant, and holder of patents spanning network visualization to automotive brake engineering—has convinced him that organizations who can bridge technical disciplines move faster than those who hand off between specialists. This advantage, he argues, is about to become decisive.