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AI integration

AI integration is the incorporation of artificial-intelligence capabilities into a software system, digital product, workflow, or decision-making process.

How 2 Manning books explain it

The Art of AI Product Development

AI integration is the incorporation of artificial intelligence capabilities into an existing or newly developed digital product.

How it is used
Guides product builders in identifying opportunities, managing risks, and allocating resources across AI initiatives.
How deep it goes
Distinguishes three starting scenarios and details brownfield data, governance, and infrastructure challenges.
Examples
Uses financial analytics, corporate reporting, sustainability reporting, and data analytics platforms as integration cases.
What you can do after
Evaluate AI opportunities and guide initiatives while accounting for integration risks and organizational context.

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AI for Everyday IT

AI adoption is the organizational process of accepting, implementing, and integrating artificial-intelligence capabilities into work and decision-making.

How it is used
Applies AI to workplace problems, process improvement, organizational adoption, and professional skill development.
How deep it goes
Explains practical use-case selection, experimentation, advocacy, and planning, but stops short of implementation details for complete production systems.
Examples
Uses HR data structuring, SharePoint metadata assignment, code documentation, and a six-month DevOps learning-plan prompt.
What you can do after
Apply it via AI tools to identify useful opportunities, improve work, demonstrate measurable value, and plan further skill development.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.