Use innovation tools with AI to predict and influence
AI means artificial intelligence, in which a computer detects patterns of data to produce insights that can help businesses understand the behavior of their customers. AI predictions can predict customer needs and automate business processes. Using AI applications and digital innovation tools, companies can discover information lying latent in unstructured data and deliver new ways to engage with customers to deliver better experiences.
You can accelerate this type of digital innovation through each of the following solution areas. Best practices and technical guidance to accelerate digital invention are listed in the table of contents on the left side of this page. Those articles are grouped by solution area:
- Machine learning
- AI applications and AI agents
- Knowledge mining
Considerations when starting your digital innovation journey with AI applications
AI strategy, AI culture, responsible and scalable AI, and AI for each of the different business personas are crucial elements for any business to consider when planning your AI prediction and innovation journey with AI.
AI strategy: Industry leaders follow a framework for creating an AI vision that can be applied strategically across an organization. Questions around the value creation perspective, organization and execution perspective, and industry environment perspective define the AI environment.
AI culture: To successfully develop an AI culture, key changes might be required to become AI-ready. This includes the ability to explore AI potential across the business, recognition and fostering of the skills and roles required to make AI success, providing examples of successful implementations of AI with relevant scenarios in finance, marketing, sales, and customer service and AI application evangelism.
Responsible AI: Responsible AI is a commitment to the advancement of AI, driven by principles that put people first. Microsoft AI principles and resources support trusted AI within infrastructure and business frameworks. To successfully build an AI practice, responsible AI should be incorporated into your digital innovation approach.
Scalable AI: Scalable AI enables fueling innovation tools at all levels, evaluating AI investments, and establishing technical processes for AI throughout your organization. AI patterns and best practices allow scaling AI horizontal and vertical through the enterprise.
AI for business users: AI can empower everyone within an organization to achieve more, not just developers and data scientists. Over time, all users should understand the AI applications, concepts, tools, and technologies that make it possible.
AI for business leaders: Understanding state-of-the-art AI technology by holistically exploring machine learning concepts and how they can be used to optimize business across industries, and develop an understanding on how these innovative tools and technologies can benefit your business.
The articles shown in the table of contents will help you get started with each of the solution areas.
Some links might leave the Cloud Adoption Framework to help you go beyond the scope of this framework.