AI is evolving quickly, and many organizations are still trying to separate practical business value from hype. That’s why we created AI in 30, a recurring monthly webinar series focused on practical, approachable AI education for business leaders. Held every third Wednesday at 1PM ET, these concise 30-minute sessions explore everything from real-world AI applications to workflow automation and even governance and risk considerations. Whether you’re exploring AI for the first time or looking to better structure your organization’s AI strategy, AI in 30 is designed to deliver actionable insights without unnecessary technical complexity.
Each month, AI in 30 explores a different aspect of artificial intelligence and what it means for today’s businesses. Sessions are designed to make AI easier to understand and help business leaders identify where it can realistically fit within their organization.
Topics throughout the series include:
Whether you’re just beginning to explore AI or already using it within your organization, each 30-minute session is focused on practical takeaways you can use to make more informed decisions.
Download two practical tools designed to help you apply what you learn:
AI Summary Guide
A clear, executive-level breakdown of:
AI Go-To Prompts Sheet
A ready-to-use set of prompts for:
👉 Fill out the form to download now
AI is already embedded in the tools your team uses every day. The real risk isn’t using AI- it’s using it without structure, governance, or leadership oversight.
Organizations today are facing:
Before you invest further, you need clarity.
No- everything is designed in plain business language.
AI can be secure but it is not secure by default. Public tools, unmanaged usage, and lack of governance can introduce data leakage and compliance risks. That’s why leadership oversight and structured implementation are critical.
Most organziations start by identifying practical use cases and defining guardrails or areas for data governance.
Pinpoint where AI can drive measurable impact across your organization.
Evaluate tools, align investments to business goals, and build a realistic roadmap.
Reduce risk by defining data usage standards, policies, and oversight.