Sales, service, marketing, commerce, analytics, and industry AI use cases
Business goals, user journeys, value, feasibility, risk, data readiness, and adoption
Einstein 1 Platform concepts, Data Cloud grounding, CRM context, and metadata
AI project roles, governance, lifecycle, success metrics, and operating model
Use-case assessment and solution blueprint
Practical Activity
Configure or analyze a scenario involving predictive ai, generative ai, copilots, agents, machine learning, and salesforce product landscape.
Build and validate an exercise covering sales, service, marketing, commerce, analytics, and industry ai use cases and business goals, user journeys, value, feasibility, risk, data readiness, and adoption.
Use tests, logs, reports, or documentation to verify use-case assessment and solution blueprint.
Key Takeaways
Explain predictive ai, generative ai, copilots, agents, machine learning, and salesforce product landscape in the context of Salesforce AI Solutions (SAI201).
Apply practical methods for sales, service, marketing, commerce, analytics, and industry ai use cases and business goals, user journeys, value, feasibility, risk, data readiness, and adoption.
Test, document, and troubleshoot use-case assessment and solution blueprint.
