Building a foundation for AI success: Technology and data strategy
In this post, we’ll focus on the five data and technology fundamentals required to deliver meaningful, sustainable, and responsible value creation with AI.
AI resources
-
-
Building a foundation for AI success: AI strategy and experience
In this post, we’ll focus on emerging best practices that can help you position your AI projects for success. -
Build, buy, or both? How to choose the right approach for your AI transformation
There are a few common pathways for how to apply AI to reach your goals. -
Transform your business with AI skill building on Microsoft Learn
Learn how skill building with Microsoft Learn is a critical element of your AI transformation strategy. -
Building a foundation for AI success: Organization and culture
Explore a few of the emerging best practices that are helping leaders position their organizations for success in the age of AI. -
Building a foundation for AI success: Governance
We have collected a set of resources that encompass best practices for AI governance, focusing on security, privacy and data governance, and responsible AI. -
The AI Strategy Roadmap: Navigating the stages of value creation
The AI Strategy Roadmap shares what Microsoft has learned about the emerging best practices that organizations are using to create sustainable value with AI. -
Get AI ready: Build skills with Microsoft Learn
A skills-first approach to AI leads to skill building for every role, with Microsoft Learn as a trusted partner. -
Measurement is the key to helping keep AI on track
This new approach to measurement, or defining and assessing risks in AI and ensuring solutions are effective, looks at both social and technical elements of how the generative technology interacts with people. -
3 key features and benefits of small language models
Bigger is not always necessary in the rapidly evolving world of AI, and that is true in the case of small language models (SLMs).