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- Learn how to use AI tools and resources for your business.
After completing this module, you'll be able to:
- Prioritize AI use cases by value, feasibility, and time to value, and track results with clear Key Performance Indicators (KPIs).
- Unify data, modernize infrastructure, and adopt Azure services to run secure, compliant AI at scale.
- Put governance, security, and regulatory controls in place to manage risk and maintain trust.
- Enable people to use AI in daily work with Copilot, agents, and low code tools to boost productivity and streamline processes.
- Learn how to align AI to business strategy and ensure readiness using essential drivers for scalable, impactful, secure adoption.
After completing this module, you will be able to:
- Align AI strategies with business priorities to focus on high-impact areas.
- Design a scalable and secure foundation for AI deployment.
- Accelerate AI adoption through effective tools and methods.
- Develop governance strategies to manage risk responsibly.
- Integrate organization and culture changes for efficient AI implementation.
- Explore six principles to guide AI development and use - fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.
In this module, you will:
Explain why responsible AI matters and identify its societal implications.
Apply Microsoft’s six guiding principles for responsible AI in your organization.
Design a governance system that turns principles into actionable policies and controls.
Take practical steps to implement responsible AI across teams and processes.
- Learn enterprise AI management with our free open online course, including scaling AI.
By the end of this module, you're able to:
- Explain the foundational concepts and business value of generative AI for organizations.
- Identify and evaluate Microsoft generative AI solutions—including Copilot, Azure AI, and agents—for common business scenarios.
- Assess key considerations for adopting generative AI, including model selection, cost drivers, and responsible use.
- Recognize challenges and opportunities in generative AI, such as reliability, bias, and strategic alignment.
