Chicago eLearning & Technology Showcase 2026

Learning and development teams have more data than ever before, from completion rates and satisfaction scores to engagement dashboards and learning analytics. Yet many organizations still struggle to answer one critical question: Did learning actually improve performance?

In this interactive session, Vanessa Milara Alzate explores how to move beyond vanity metrics such as attendance, satisfaction, and course completion toward meaningful performance intelligence. Using the modernized Kirkpatrick Four Levels®, you will learn how to design elearning programs with evaluation built into the process from the start.

Through real-world examples, the session demonstrates how LMS analytics, digital learning platforms, and data dashboards can be used to measure behavior change and business outcomes rather than simple activity tracking. Participants will also explore how instructional design decisions, learning technology data, and organizational goals can work together within a unified evaluation strategy.

By the end of the session, participants will be able to

• Differentiate between vanity learning metrics and performance-based evaluation indicators.
• Design elearning programs that integrate the Kirkpatrick Four Levels® evaluation framework from the start.
• Apply learning technology data (LMS analytics, digital learning tools, and performance metrics) to demonstrate measurable business impact.

Most AI training programs are built the wrong way. They teach people about AI through static elearning and then expect them to use AI effectively in dynamic workflows. The result is low adoption, surface-level usage, and learning investments that fail to improve performance.

Using Golin’s global AI transformation as a live case study, this session explores how a 1,700-person communications agency increased AI adoption from 15% to more than 90% in 18 months by rethinking its instructional design approach. You will examine the learning architecture behind those results, including role-specific pathways, expert-led microlearning, a globally scaled AI mentoring program, and adoption metrics tied to business outcomes.

Drawing on additional lessons from AI upskilling efforts across 115,000 employees at Publicis Groupe, Joe Leslie will share the strategic frameworks and instructional models that supported these initiatives, including a problem-first methodology centered on real workplace challenges.

By the end of this session, you will be able to

• Apply a problem-first framework to AI training design.
• Build role-specific AI learning pathways.
• Evaluate AI training using adoption and performance metrics.

AI isn’t a one-and-done transformation. It’s a series of evolving projects layered across teams, systems, and strategies. In this session, you will explore the AI Implementation Canvas: a practical tool for navigating the complexity of AI adoption with clarity, care, and confidence.

The Canvas helps you ask the right questions, include the right people, and plan for both business value and ethical impact across a variety of AI initiative types. Megan Torrance will lead you in discussion of the role that L&D can play in leading the initiative. Then, you will walk away with a clear model to bring back to your organization and use immediately.

By the end of this session, you will be able to

• Lead AI implementation conversations across 14 planning dimensions.

• Apply L&D’s unique skillset to support the organization’s collaboration around AI implementations.

• Support your organization with the AI literacy and business change frameworks needed for success.

It’s Monday morning, and you check your email to see, “There’s something wrong with the onboarding process. People don’t know what they need to know after it’s done. The training needs to be revised.” But here’s the issue: you’re working with one person’s assumptions and no time to figure out what’s actually broken.

This session shows you how to stop guessing. Using a real-world example, Shannon Tipton will show you how to work with AI to pinpoint the root cause of the perceived issue and then simplify the development process. You will leave with practical workflows that you can use right away to build training that actually solves the problem.

By the end of this session, you will be able to

• Diagnose training requests using AI tools to find the real cause of business problems, so you can build solutions that fix actual issues instead of incorrectly perceived ones.

• Apply AI-powered content audits to evaluate existing training materials, helping you keep what works and cut what doesn't, save time, and improve quality.

• Implement AI workflows that link training to business problems, so you can build solutions faster and show stakeholders the real impact.