What if your business data could tell you exactly what’s working, what’s broken, and what to do next—without dashboards, analysts, or endless spreadsheets?

Most leaders know data-driven decisions matter.
 Very few have the time, tools, or teams to analyze data consistently, deeply, and at scale.

In this episode of the Leveraging AI Podcast, Isar Meitis is joined by Keith Moehring, CEO of L2 Digital, to break down how business leaders can use AI + automation to turn raw data into clear insights—and actionable recommendationsautomatically.

Instead of chasing reports, building pivot tables, or relying on expensive BI platforms, you’ll learn how to build an AI-powered analytics assistant that pulls data from multiple sources, identifies what actually changed, explains why it happened, and emails you the insights on a schedule you choose.

This isn’t theory. It’s a practical, repeatable system that replaces hours of manual analysis with intelligent automation—while keeping humans focused on decisions, not data prep.

In this session, you’ll discover:

• Why “more data” isn’t the answer and how AI helps surface the right insights
• How to automate multi-source data analysis without advanced technical skills
• The 4-step framework for building reliable AI analytics automations
• How AI identifies deviations, root causes, and meaningful trends
• When to use rigid automation vs. flexible AI reasoning
• How leaders receive clean, actionable insight reports directly via email
• Why separating “analysis” and “strategy” agents improves AI output quality
• How this approach applies across marketing, finance, sales, HR, and operations

About Leveraging AI

• The Ultimate AI Course for Business People: https://multiplai.ai/ai-course/
• YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/
• Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/
• Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!