A consultant is helping sellers at a professional services firm quickly decide which of their assigned leads to work on first each morning. The sellers want a natural-language explanation, generated from the record's recent activity and field data, that appears directly on the lead form rather than a raw list of numbers. Which capability should the consultant recommend to meet this specific need?

The correct answer is the Copilot-generated lead summary in the Sales Copilot pane that synthesizes record and activity data into conversational text. The sellers specifically want a natural-language explanation of a lead, generated from recent activity and record data, surfaced right on the form; that is the role of the Copilot-generated lead summary, which turns underlying signals into readable prose a seller can scan in seconds rather than a set of raw metrics to interpret. The predictive lead scoring numeric score and grade alone is incorrect because it produces numeric and categorical outputs, not conversational summaries; it informs prioritization but does not narrate the reasoning in plain language. The relationship health score shown on the account timeline is incorrect because it reflects the strength and trend of an ongoing account relationship over time, which is a different signal aimed at account-level engagement rather than a fresh narrative summary of an individual lead. The sales sequence assigned to the lead's record type is incorrect because it is a scheduled series of outreach steps and activities assigned to guide follow-up, not a natural-language summary tool; sequences automate cadence, they do not explain a lead's current state in conversational terms. The Copilot summary is purpose-built for exactly the scanning-and-deciding workflow described in the scenario.