Explore the business value of generative AI solutions
Microsoft Learn
Last updated March 17, 2026
A two-module path aimed at business leaders who need to understand generative AI well enough to make decisions about it — no hands-on tools, no prerequisites. It covers the foundations (what generative AI is, the kinds of models, and the cost drivers behind them), how to spot high-value opportunities and assess whether an organization is ready, and what responsible adoption looks like in practice. The second module turns to making AI work reliably: grounding it in trusted data, ensuring data quality and security, and knowing when traditional machine learning is the better fit. About one hour, self-paced.
What you'll learn
- The foundations of generative AI: concepts, models, and cost drivers
- Identifying high-value opportunities and assessing organizational readiness
- Principles of responsible AI adoption
- Grounding AI in trusted data and ensuring data quality and security
- Recognizing when machine learning, rather than generative AI, is the right tool
Frequently asked questions about Explore the business value of generative AI solutions
Who is Explore the business value of generative AI solutions for?
Business leaders and decision-makers who want to understand generative AI's value, costs, and risks without any technical prerequisites.
Is Explore the business value of generative AI solutions free?
Yes — Explore the business value of generative AI solutions is completely free to take.
What are the prerequisites for Explore the business value of generative AI solutions?
None. No coding required.
Why we suggest this course
For executives and decision-makers who keep being asked about AI strategy, this path delivers understanding rather than a tool walkthrough: where generative AI creates measurable value, what it costs, how to gauge organizational readiness, and how to adopt it responsibly. It is pitched squarely at leadership, and the page lists no prerequisites, so it assumes no technical background. Useful framing of grounding and data quality means it does not oversell AI as a drop-in fix.