Description

Event Overview

Artificial Intelligence (AI) continues to transform how businesses operate. The Manitoba Chambers of
Commerce, in partnership with The Winnipeg Chamber of Commerce and the broader chamber network,
are poised to play a critical role in leading this change.

With funding through the Province of Manitoba, Manitoba AI Pathways has launched to deliver practical,
actionable generative AI training across Manitoba.

To support this initiative, PACE Corporate Training (University of Winnipeg) is pleased to present an
exclusive, one-day seminar designed specifically for key staff and members of the chamber network.
This immersive session will equip participants with the foundational knowledge and language needed to
confidently speak about AI in their regions. Whether facilitating conversations with local businesses,
promoting upcoming AI training opportunities, or supporting digital readiness initiatives, attendees will
leave prepared to act as trusted champions and connectors in Manitoba’s AI evolution.
 

Seminar Objectives

Participants will:

• Develop a clear understanding of AI fundamentals and current business applications.
• Gain confidence in discussing AI trends, tools, and terminology with diverse stakeholders.
• Explore real-world use cases relevant to Manitoba’s economic landscape.
• Understand the ethical and strategic considerations around AI adoption.
• Leave with messaging tools and resources to support regional rollout efforts.
• Receive a verified digital badge to showcase AI readiness and professional development.

Facilitator

Dr. Justin Dallmann, PhD
Data Scientist, Innovation, Transformation & Technology — City of Winnipeg

Before joining the City of Winnipeg, Justin led The Dufresne Group’s advanced analytics initiatives, working on marketing modeling, sales & merchandising forecasts, and data visualization.

He teaches AI in the Workplace and AI Ethics at The University of Winnipeg, and has received multiple cross-disciplinary awards and publications in data science and decision theory. Justin’s doctoral research at the University of Southern California and post-doctoral work at the University of Toronto focused on Bayesian models of bounded rationality, decision theory, and the foundations of statistics.