How does the Einstein Trust Layer relate to Agent Action?

The Einstein Trust Layer provides the security, privacy, and responsible AI framework that governs how features like Agent Action access and process data.

What does Agent Action need to work effectively?

AI features like Agent Action rely on quality historical data in your Salesforce org — the more clean, consistent data available, the better the predictions.

What technology powers Agent Action in Salesforce?

Agent Action is powered by artificial intelligence and machine learning, analyzing patterns in your data to make predictions and recommendations.

Agent Action

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Definition

An Agent Action is a specific, discrete task that an Agentforce AI agent can perform when interacting with users or processing requests. Each action is defined with a description, inputs, and outputs, and is mapped to an underlying capability such as a Flow, Apex class, or prompt template. Agent Actions are the building blocks of an AI agent's functionality.

Real-World Example

A developer at CloudServe defines three Agent Actions for their customer-facing Agentforce agent: "Look Up Order Status" (which calls a Flow to query order records), "Process Return Request" (which invokes an Apex class to create a return case), and "Recommend Product" (which uses a prompt template with Einstein). When a customer asks about their order, the agent selects and executes the appropriate action automatically.

Why Agent Action Matters

Agent Action is part of Salesforce's artificial intelligence layer, which brings machine learning and predictive capabilities directly into the CRM workflow. Rather than requiring data science expertise, these features make AI accessible to everyday business users who can benefit from smarter recommendations and automated insights.

The real power of Agent Action lies in its ability to learn from your organization's historical data and surface patterns that humans might miss. Whether it is predicting which deals are most likely to close, recommending the next best action for a service agent, or automatically classifying incoming cases, AI features like this amplify the effectiveness of your entire team.

How Organizations Use Agent Action

•Vandelay Industries — Enabled Agent Action to analyze two years of opportunity data and identify the behavioral patterns that predict deal closure. Sales reps now see AI-generated scores on every opportunity, helping them focus energy on the deals with the highest win probability.
•Cyberdyne Co — Deployed Agent Action in their service center to automatically route incoming cases to the most qualified agent based on case topic, language, and agent expertise. First-contact resolution improved because cases consistently land with someone who can actually help.
•Soylent Group — Used Agent Action to surface proactive recommendations for account managers. When the AI detects a change in a customer's engagement pattern or identifies a cross-sell opportunity based on similar accounts, it pushes a suggestion directly into the rep's workflow.