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Wiz Learning Report
AI Powered Futures
CILAR · Cohort 2 · Summary Report
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Wiz Learning Report
CILAR · Toronto Metropolitan University Chang School of Continuing Education
AI Powered Futures: Cohort 2 Summary Report
Prepared by Wiz Learning
Cohort 2 Complete
April 8 – May 27, 2026
8 modules · 8 weeks
Virtual delivery
Program overview
AI Powered Futures is an 8-week applied AI upskilling program developed by Wiz Learning for the Centre for Innovation and Leadership in Retail (CILAR), in partnership with Toronto Metropolitan University's G. Raymond Chang School of Continuing Education. The program builds practical AI literacy for retail and customer-facing professionals, with a focus on responsible use, applied decision-making, and human oversight of AI tools. Completion of the program supports eligibility for the CURV 701-DA0: Leading Responsible AI Use in the Workplace microcredential from TMU.
- All 8 sessions delivered online
- Each session ran 90 minutes with an optional 30-minute office hour
- Cohort 2 was designed specifically for managers and team leads in the retail industry
- Lead facilitation by Merveille M., with supporting facilitation by Ryan P. across all modules
Cohort profile
16 learners registered for the program. Two withdrew after Week 2, bringing active enrollment to 14 for the remainder of the program. Cohort 2 was the most experienced cohort to date, with 92% of learners already using AI tools in their day-to-day work before the program began.
What set Cohort 2 apart was the shared thread running through the group. While the cohort included learners from retail, banking, financial services, tech, and government, the majority came from management and leadership roles: store managers, team leads, and operational supervisors. Several others had backgrounds in IT or early-stage startups. This professional similarity gave the group an unusually strong foundation for peer learning. Facilitation deliberately placed learners in breakout groups with career similarities, which produced richer discussion, more relevant scenario work, and a stronger sense of shared context throughout the program.
- 75% of learners came from supervisory, team lead, or corporate office roles
- 67% arrived with a positive outlook on AI at work; the remaining 33% saw it as useful but were unsure how to apply it
- Most common AI uses at program start: writing messages or emails (12/12), brainstorming (12/12), organizing information and research (9/12 each)
Attendance and engagement
Two learners withdrew after Week 2, bringing active enrollment to 14. All attendance figures from Week 3 onward are calculated against that revised total. Cohort 2 maintained strong and consistent attendance across the full program, with no week falling below 71%.
Avg attendance
84%
Across all 8 weeks
Peak attendance
100%
Week 2 (14/14)
Avg engagement composite
4.48/5
Across all 8 weeks
Usefulness rated 4 or 5
88%
Of 74 total responses
Weekly attendance
Peak
Standard
Below avg
Weekly engagement composite (out of 5)
Composite score
The engagement trajectory across Cohort 2 was one of the clearest positive trends of the program. After a dip in Week 2 to 3.90, engagement climbed steadily through Weeks 3 to 6, peaking at 4.83 in Week 6. Every session from Week 3 onward scored 4.29 or higher. The program never dipped below 4.0 in its final four weeks, a pattern that reflects both the quality of facilitation and the strength of the cohort's shared professional foundation.
Assessment and knowledge growth
TMU CURV 701-DA0 microcredential results
Leading Responsible AI Use in the Workplace
5
Enrolled in pathway
3
Submitted
2
Confirmed passes
1
Result pending
Among the 4 learners who completed the post-program growth survey, AI confidence increased from 5.6 to 8.25 out of 10, a gain of 2.65 points. The mid-program knowledge check, completed by 9 learners at the halfway point, averaged 89%. The end-of-program knowledge check, completed by 7 learners, averaged 84%. These two assessments measure different content and are not directly comparable, but both indicate strong knowledge retention across the program.
AI confidence before and after (out of 10)
Before (baseline avg)
After (growth survey avg)
Post-program concept familiarity (out of 4)
Post-program avg (4 respondents)
Self-paced completion (Disco)
Self-paced completion was stronger in Cohort 2 than in Cohort 1 across the first half of the program. Modules 1 and 2 both closed at 86%, and Modules 3 and 4 held at 71% — compared to 62% and 58% in the same modules for Cohort 1. The second half followed a similar declining pattern across both cohorts, with Modules 7 and 8 closing at 43% and 29% respectively.
Module completion rate
Strong (70%+)
Moderate
Declining
Low
Program highlights
Cohort 2 was the highest-performing cohort to date by engagement, with an average composite of 4.48 out of 5 across all 8 weeks. The cohort's leadership background consistently elevated discussion quality. By Week 6, student-led conversation had become the defining feature of the program, with learners building on each other's ideas and connecting AI concepts to their real workplaces without being prompted. One standout exchange moved from restaurant customer service to the idea of curating experiences, landing on emotional intelligence as a core human skill that AI cannot replace.
Module 3, focused on prompt engineering, was independently named by multiple learners as the most practically useful part of the program, including in end-of-program reflections. Module 4, covering responsible and ethical AI use, produced the highest student-rated understanding score of any session at 4.25, alongside 75 to 90% active participation. The deliberate practice of grouping learners by career similarity in breakout rooms contributed meaningfully to the depth of those sessions.
AI Decision-Making Matrix
DECIDE Check
AI Responsibility Gate
Prompt engineering framework
"I was unconfident and struggled to use my curiosity. Now I am much more confident and structured — and I have made a lot of headway in the space."
Cameron J. — Retail
"Once you understand how to communicate with AI properly, it becomes a very practical and useful tool that can really support your work and help you grow."
Neslihan M. — Customer Service
"I had thought AI would replace humans and take their jobs. For now, it seems like humans are still needed — context, critical thinking, reasoning, and judgment are still required."
Samantha K. — Retail
Areas for improvement
- Self-paced completion declined steadily from Module 5 onward, closing at 43% for Module 7 and 29% for Module 8. This pattern has appeared across both cohorts and points to a structural challenge in sustaining asynchronous engagement through the back half of the program.
- Weeks 7 and 8 saw the lowest attendance of the program at 71% and 79% respectively, despite both sessions carrying significant microcredential and wrap-up content. How these final sessions are framed and communicated in advance is worth revisiting for future cohorts.
About Wiz Learning
Wiz Learning is an AI-powered education technology company that helps schools, nonprofits, workforce agencies, and organizations design engaging, scalable, and personalized learning experiences. Supporting more than 9,000 learners across 30 countries, Wiz Learning partners with institutions to build future-ready programs rooted in equity, accessibility, and real-world outcomes. The company has been featured in Forbes, recognized as a Columbia University EdTech Fellow, spotlighted by Stanford University's Graduate School of Business, and backed by funders including Google, the Cartier Women's Initiative, and ECMC. AI Powered Futures was developed and delivered by Wiz Learning on behalf of CILAR in partnership with Toronto Metropolitan University's G. Raymond Chang School of Continuing Education.
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