Salesforce AI-201 Agent force Specialist Exam Guide with Topics and Ideal Candid

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The AI-201 Agentforce Specialist exam validates your ability to work with Salesforce’s AI agents, configure them for business workflows, and use prompt engineering and data grounding techniques. It focuses on practical skills for building, managing, and deploying AI-powered agents that automate tasks, support users, and enhance customer experiences inside the Salesforce ecosystem. The exam measures real-world knowledge of Agentforce features, data usage, system behavior, and deployment best practices.

Ideal For

• Professionals who want to build and configure AI agents for business workflows.
• Salesforce admins, consultants, or analysts looking to enhance automation with AI.
• Users familiar with CRM processes who want to integrate intelligent agents into sales, service, or internal operations.
• Teams aiming to streamline tasks, improve support efficiency, or automate repetitive actions using AI.
  
  

Exam Overview

• Exam Code: AI-201
• Exam Name: Agentforce Specialist
• Format: Multiple-choice and multiple-select questions
• Time Allowed: 105 minutes
• Passing Score: 73%
• Difficulty: Intermediate (requires basic Salesforce familiarity)
  
  

Covering Topics1. AI Agents (Largest Section)

• Understanding agent types and capabilities
• Setting up agent topics, instructions, and rules
• Connecting agents to channels like chat, email, or internal systems
• Using actions, tasks, and decision-making tools inside agents
  
  

2. Prompt Engineering

• Creating prompts using templates
• Writing structured and grounded prompts
• Adjusting tone, style, and output behavior
• Improving accuracy through prompt optimization
  
  

3. Data Cloud and AI Data Library

• Setting up data libraries for agent grounding
• Choosing retriever types such as keyword, vector, or hybrid
• Ensuring data relevance, security, and accuracy
• Managing data connections used by AI agents
  
  

4. Deployment Lifecycle

• Testing agent behavior with real scenarios
• Sandboxes vs. production deployment
• Monitoring agent performance
• Handling permissions, security, and system access
  
  

5. Multi-Agent and Integration Concepts

• Configuring agents to work together in workflows
• Connecting agents to APIs and automation tools
• Managing complex, multi-step AI processes