Learn the Microsoft AI approach
AI is disrupting every industry and every business. For the last decade, AI has enabled companies of all sizes to achieve better business results. There's already a mainstream business use of AI thanks to these three trends:
- Access to massive amounts of data.
- Access to massive computing power through cloud.
- Access to AI algorithms.
However, AI is now experiencing major breakthroughs. A new generation of LLMs enables new use cases that weren't possible a few years ago, such as those based on high-quality generative AI. Based on these technologies, organizations will experience a second wave of AI-powered transformation. However, businesses need an easy way to access the latest AI if they want to take full advantage of it.
Microsoft is working to democratize AI use. For this, it has designed a wide range of solutions and services to bring AI to everyone, irrespective of their level of AI expertise. There are four approaches, ranged from the level of AI and coding expertise required.
- AI as copilot for business users: Microsoft has embedded AI in everyday applications, so business users can benefit from it, even if they don't know anything about coding or data science. In this approach, AI is delivered as a Software as a Service (SaaS) and becomes transparent, that is, it's fully integrated within the provided service without users having to worry about it. For example, Microsoft 365 Copilot incorporates the latest generative AI in the shape of a virtual assistant that performs tasks for you in Microsoft 365 apps.
- Microsoft Power Platform: It covers several low-code products that help you build different pieces of applications. These products have a layer of AI, but it's transparent as well and you can benefit from it without handling it directly.
- Azure AI Services: These are the solutions for users who want to deliver an AI project but have little data science expertise. They offer premade AI models for you to reuse or customize.
- Azure Machine Learning: All machine learning tasks can be handled from this platform. It helps data science teams in setting, automating, and enabling machine learning best practices.
Keep in mind that Microsoft has designed all these products and services following strict responsible AI principles. Any AI implementation should be equally respectful.
The rest of this module covers each of these options. Next, we'll discuss the one with the lowest entry barrier, AI as copilot, embedded in everyday applications.