Overview

This three-and-a-half-day immersive workshop is designed for executives and senior leaders seeking to explore the strategic application of artificial intelligence and machine learning within their departments and across their enterprise. Participants will leave the workshop equipped with actionable plans tailored to both their business unit and broader organizational needs.

Who Should Attend

The Boston campus offers Northeastern’s broadest selection of academic programs—including undergraduate, graduate, and PhD degrees across disciplines. Students engage in cutting-edge research alongside world-class institutions, hospitals, and innovation-driven companies in science, engineering, healthcare, business, and more.

Signature facilities like the Interdisciplinary Science and Engineering Complex foster high-impact collaborations, while research and co-op partnerships support student innovation and real-world problem-solving across global industries.

Workshop Objectives

  • Understand the primary AI/ML methodologies and their best use cases
  • Apply AI/ML thinking to solve critical issues within a business unit and enterprise context
  • Develop a roadmap for implementation, including leadership and change management considerations

Agenda

Day 1

9:00 AM – 12:30 PM

  • Participant Introductions
  • Identification of key challenges to address using AI/ML at both the business unit and enterprise levels

2:00 PM – 5:00 PM

  • Review of core AI/ML methods from both technical and strategic business perspectives

Day 2

9:00 AM – 12:30 PM

  • Development of business unit-level AI/ML implementation plans using provided templates

2:00 PM – 5:00 PM

  • Group feedback and collaborative review of individual plans

Day 3

9:00 AM – 12:30 PM

  • Team-based planning to address enterprise-wide challenges using AI/ML

2:00 PM – 5:00 PM

  • Presentation and review of team strategies for organization-level implementation

Day 4

9:00 AM – 12:30 PM

  • Final discussions on plan implementation, with a focus on execution and change management
  • Summary and closing reflections