
ABOUT OUR MARCH SPEAKER:
Logan Monday is a Senior Analyst and AI Consultant who helps organizations turn AI from a confusing concept into practical, trusted workflows that solve real business problems. His work bridges AI enablement, project management, and plain-language communication — guiding teams from experimentation to measurable implementation through clear governance, structured training, and defined KPI’s tied to ROI.
With a background in education, international service, and technology, Logan specializes in translating complex technical ideas into usable systems employees can confidently apply in their daily work. Based in Chicago, he continues refining practical AI adoption frameworks that keep human judgment at the center of innovation while helping organizations close the growing AI training gap. You can learn more about Logan's work at his website.
The Mox.E Speaker Series is a curated experience designed for Black and Brown entrepreneurs in the Entrenuity Accelerator Cohort and Mox.E community. We connect founders with action leaders who share real strategies, decisions, and lessons behind measurable business growth. Each session delivers practical tools and honest insight you can apply immediately to your business.
WORKSHOP TITLE: AI FRAMEWORK: DEFINE YOUR KPI'S TO SET YOUR ROI'S
AI tools have become more accessible and experimentation is commonplace, but fewer than 5% of businesses achieve measurable impact. In this next session of the Mox.E Speaker Series, Logan Monday breaks down how to transform your current AI use out of the experimental phase and into a tool with KPIs that deliver real ROI.
This workshop is designed for founders, operators, and leaders who are ready to have AI work as a tool, not a magic wand, with clear metrics and outcomes.
Key takeaways include:
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Determining the KPI for each attendee’s preferred AI tool.
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A repeatable feedback cycle for confidently measuring AI regardless of the AI tool.
- A seven-step framework for transforming AI KPIs into measurable ROIs.
If you or your team has been asking, “How do we actually measure if AI is working for us?” then this session answers that question.
