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AB-731 Course Notes

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Section 1Business ValuePreview
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Summary

Generative AI creates or transforms content from prompts and context, while predictive AI usually scores, forecasts, classifies, or detects patterns from structured data. AB-731 questions often ask leaders to choose the right AI approach for a business need: generative AI fits drafting, summarizing, search, ideation, and natural-language assistance; predictive AI fits repeatable decisions such as demand forecasts, churn scoring, anomaly detection, and risk prediction. The business value test is not whether AI sounds impressive, but whether the capability improves a measurable outcome.

Key Points

  • Generative AI: Generative AI produces new or transformed content such as text, summaries, images, code, or recommendations from prompts and context. It is valuable when work involves unstructured information and judgment, but its output must be reviewed because it can fabricate details.
Section 2Capabilities & OpportunitiesPreview
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Summary

Microsoft 365 Copilot and Microsoft Copilot solve different levels of work. Microsoft 365 Copilot is grounded in Microsoft 365 work data and appears across apps such as Word, Excel, PowerPoint, Outlook, Teams, and chat experiences; Microsoft Copilot and Microsoft 365 Copilot Chat provide broader chat assistance with web grounding and enterprise controls depending on the experience. AB-731 questions usually ask leaders to map a business process to the right Copilot surface, not to assume every Copilot has the same data access or app integration.

Key Points

  • Microsoft 365 Copilot: Microsoft 365 Copilot is the work-focused Copilot experience integrated with Microsoft 365 apps and grounded in Microsoft Graph data the user can access. It is the right fit when the value comes from documents, email, meetings, chats, spreadsheets, and presentations.
Section 3Implementation StrategyPreview
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Summary

An AI implementation strategy starts with responsible AI principles and ownership. Fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability should be translated into decision gates, not left as slogans. An AI council or steering committee gives legal, security, IT, risk, data, business, and operations leaders a place to approve use cases, resolve conflicts, and stop teams from creating shadow AI with unmanaged data exposure.

Key Points

  • AI Council: An AI council is a cross-functional governance group that guides AI strategy, approves policies, reviews risk, and aligns AI investments with business priorities. It reduces fragmented decisions and gives the organization a consistent path for responsible AI adoption.