LEARN. PRACTICE. GROW.Concept and mechanism
An AI capability improves a process only when its output supports a suitable decision. Einstein Lead Scoring helps rank leads using historical conversion patterns. Displayed factors help interpret the score but do not establish that changing an attribute causes a sale. The score should not be treated as a calibrated individual probability without evidence. Einstein Case Classification uses closed-case history to recommend field values for new cases. The service process, categories, and routing rules still need definition. Benefits should be measured through useful time saved, required corrections, and service quality, including effects on different request groups.
Guided application
In an eligible pilot, distinguish displaying alternatives, preselecting a value, and saving automatically. These actions have different consequences. Confidence thresholds constrain some actions, but high confidence can coexist with error. Confirm capabilities available in the edition and contract before designing automation; this course does not promise universal feature availability. Start with observable scope, record operator interventions, and compare with the previous process. If routing deteriorates, restore human confirmation in the affected scope while investigating labels, data, and thresholds. Increasing populated-field rates without assessing correctness may merely accelerate work that later needs correction.
Example: lowering a threshold raises field completion from 60% to 88% but doubles transfers between teams. The benefit must include the cost of those transfers.
Common pitfalls
Score treated as guarantee; recommendation treated as saving; automation without confirmed entitlement; measuring volume without errors.
Related topics: Choose the AI task and quality evidence · Trust principles and real consequences · Human oversight and response to AI failures
Choose capability by process and accept automation based on operational effects.
Reference: Learn About Einstein Classification Apps · AI Associate historical Spring 24; retired 2026-02-02