Salesforce Certified AI Specialist Guide & Tips

The Salesforce Certified AI Specialist certification equips professionals with the expertise to integrate and leverage AI tools within Salesforce CRM. It focuses on key AI-driven features, such as the Einstein Trust Layer for security, Generative AI for personalized customer interactions, the Prompt Builder for customizing AI queries, Agentforce Tools for enhancing customer support, and the Model Builder for creating custom AI solutions. This certification enables professionals to drive innovation, improve customer engagement, and streamline business operations using AI, positioning them as experts in the evolving field of AI-powered CRM.

About the Salesforce Certified AI Specialist Exam

Number of Questions: The exam consists of 60 questions.
Time Allotted: You have 105 minutes to complete the exam.
Passing Score: In order to pass, a passing score of 73% is required (44 out of 60 questions).
Results: You will receive your results immediately after completing the exam.
Cost: The exam costs $200 (Free till 31 Dec. 2025).
Retake Fee: The retake fee is $100.
Location: The exam can be taken online or at a facility near you.
Restrictions: No hard-copy or online materials can be referenced during the exam.
Prerequisite: You do not need any prerequisites to take the exam.

Salesforce Certified AI Specialist Exam Outline

To earn your Salesforce AI Specialist certification, you’ll need to master various key topics. Specifically, below is an overview of what you can expect to cover in the exam:

Einstein Trust Layer: 15% (9 Questions)

The Einstein Trust Layer is a foundational security feature within Salesforce AI. In particular, it ensures data privacy, security, and grounding features.

Exam Testing Topics

Identify the security, privacy, and grounding features of the Einstein Trust Layer.
Implement and manage the Einstein Trust Layer.

Some of the Key features of the Einstein Trust Layer include:

Masking sensitive data to protect personally identifiable information (PII) before it reaches the AI model.
To ensure secure data retrieval from Salesforce, grounding prompts are based on the user’s permissions.
Screening for toxic output by filtering out bias, inappropriate language, and offensive content.
Preventing data leaks through a strict zero data retention policy.
Ensuring compliance with federal and state regulations regarding data usage.
Generating audit trails to track and review prompt processing, with pre-built reports and dashboards for easy analysis.

Generative AI in CRM Applications: 17% (10 Questions)

Generative AI in CRM Applications leverages artificial intelligence to automate and enhance customer relationship management processes. It enables the creation of personalized content, such as emails, product recommendations, and responses in chatbots, tailored to individual customer needs and preferences. By analyzing customer data, Generative AI helps businesses predict behavior, optimize interactions, and drive meaningful engagement.

Exam Testing Topics

Given a scenario, identify the correct generative AI feature in Agentforce for Sales.
Given a scenario, identify the correct generative AI feature in Agentforce for Service.

Einstein for Sales Features

Prepare with Agentforce: This AI-powered assistant helps you prepare for meetings by researching prospects, summarizing records, and delivering recommendations for planning your day. It provides selling guidance and close plans, auto-updates CRM data, and more.
Create AI-powered generative emails: You can auto-create personalized and impactful emails at scale for prospecting, following up on meetings, and sending proposals.
Leverage AI-powered call summaries and call support: Your reps save time, improve follow-up, and make every interaction count with AI-powered insights, summaries, automated follow-ups, and sales signals. Sellers are provided with key mentions, transcripts, and action items automatically from recorded calls.
Build your data foundation: Use automatic activity capture, opportunity and lead scoring, predictive forecasting, account insights and deal insights to make data-driven decisions.
Coach sellers: Provide instant and actionable feedback through immersive simulations and personalized coaching programs.
Guide selling and grow relationships: Use propensity to buy, next-best opportunity, and product recommendations alongside relationship maps, recommended connections, and email insights to sell the right solution to the right person at the right time.

Einstein for Service Features

Einstein Article Recommendations: Recommends relevant knowledge articles to agents on open cases.
Einstein Bots: Automatically resolves common issues in conversations on chat and messaging channels. Bot conversations can be purchased via the Digital Engagement SKU, or as an add-on.
Einstein Case Classification: Predicts field values like Priority, Reason, or Type for classifying incoming cases based on the text a customer presents in the case Subject and Description.
Einstein Case Routing: Works with Einstein Case Classification to triage and route cases to the right agent or queue.
Einstein Case Wrap-Up: Lets chat agents complete cases fast, with greater accuracy and consistency.
Einstein Conversation Mining: Transforms conversation data into service insights and builds bot intents. This is included in the Service Intelligence SKU, not in the Einstein for Service SKU.
Einstein Knowledge Creation: Grows your knowledge base and captures information in the flow of work with AI-generated article drafts.
Einstein Next Best Action: Uses data insights and business rules to recommend offers and actions for an agent to take.
Einstein Reply Recommendations: Analyzes chat transcripts to recommend relevant replies during chat and messaging sessions.
Einstein Service Replies: Drafts and recommends fluent, courteous, and relevant replies using generative AI for your agents to review, edit, and post.
Einstein Work Summaries: Drafts a summary, issue, and resolution using generative AI, based on a Chat conversation between an agent and customer.
Service Analytics: Provides insights into contact center operations, helping you deliver enhanced customer experiences.

Call Explorer

Users can ask questions directly from voice and video call recordings. The new Call Explorer enables users to quickly retrieve information from calls, such as product mentions or unresolved customer inquiries.

Call Summaries

Users can generate call summaries for voice and video calls. In addition, the new Summary tab in call records lets users create editable summaries that include next steps and customer feedback, making it easier to share and collaborate with teams directly within the workflow.

Einstein Service Replies for Chat

Using natural language processing, as a result, it enables chatbots or service agents to provide quick, relevant, and personalized replies to customer inquiries.

Einstein Service Replies for Email

Utilizing natural language processing, therefore, it helps create quick, relevant, and personalized email replies.

Prompt Builder: 37% (22 Questions)

Prompt Builder is a tool within Salesforce that allows users to create customized prompts for AI applications, enabling more precise and relevant results. It simplifies the process of crafting queries, ensuring that AI-driven insights are tailored to specific business needs and contexts, enhancing overall efficiency and accuracy in customer interactions.

Exam Testing Topics

Given business requirements, identify when it’s appropriate to use Prompt Builder.
Identify the right user roles to manage and execute prompt templates.
Identify the considerations for creating a prompt template.
Given a scenario, identify the appropriate grounding technique.
Explain the process for creating, activating, and executing prompt templates.

Prompt Template Types

Sales Email: Help your team draft truly personalized emails for your customers, products, and events based on record data.
Field Generation: Bring generative AI-assisted workflows to custom fields within a Salesforce record.
Record Summary: Creates a rich-text summary for a Salesforce record based on the record’s data.
Flex: Generate content for business purposes not covered by other prompt template types, allowing you to define your own resources.

– You must enable dynamic forms in order to use the field generation prompt template.

– The process of populating a prompt template with specific data is called prompt resolution.

– The output that the LLM generates is called a response.

Agentforce Tools: 23% (14 Questions)

Agentforce is an assistant designed to support your Salesforce users with business tasks. Moreover, it is accessible across all Salesforce pages, allowing you to effortlessly improve customer interactions and optimize workflows throughout your organization. Additionally, by utilizing your input, like prompts, along with the trusted data within your system, Agentforce provides precise answers and takes the appropriate actions.

Exam Testing Topics

Given business requirements, identify when it’s appropriate to use Agents.
Explain how an Agent works and how the reasoning engine powers Agents.
Leverage standard topics, custom topics, standard Agent actions and custom Agent actions.
Manage and monitor Agent adoption.

How Agentforce Works?

Agentforce has four basic components: namely, the assistant, topics, actions, and the reasoning engine.

Agent

Agents are trusted conversational AI assistants. They increase productivity and reduce your teams’ workload by automating routine tasks and assisting with complex ones.

Actions

Actions are how an assistant gets things done. An assistant includes a library of actions, which is basically a set of tasks the assistant can do, such as summarizing information, getting answers from a knowledge base, or drafting emails. Every action in an assistant is assigned to a topic. There are two types of actions.

Standard Actions: Standard actions are provided by default with Agentforce.
Custom Actions: You can build custom actions through invocable Apex classes, autolaunched flows, and prompt templates.

Topic

Topics are a layer of organization and customization that help your assistant make more accurate decisions and generate more relevant, predictable responses. If you peek inside a topic, you’ll find a collection of related actions and instructions telling Agentforce how to use them.

Reasoning Engine

Agentforce’s reasoning engine orchestrates how topics and actions carry out a user’s request. Behind the scenes, the reasoning engine works with the LLM to carry out the request. Specifically, here’s what it does.

Interprets the user’s request and classifies the utterance into a topic.
Iteratively builds plans for accomplishing the user’s goal.
Finds and launches the right topics and actions to achieve the goal.

Agent Builder

Topics: Opens the Topics panel, which lists all the topics in the assistant. To see or modify a topic’s details, click on the name.
Actions: Opens the Actions panel, which lets you view the actions assigned to the assistant and add or remove actions.
Language Settings: Opens the Language Settings panel, where you can define the conversational style of the assistant.
Event Logs: Helps you monitor and troubleshoot the assistant’s conversation activity.
Conversation Preview Panel: Lets you simulate a user’s conversation with the assistant by entering instructions or requests in the chat window the way a user might, and then evaluate how the assistant performs.

Model Builder: 8% (5 Questions)

Exam Testing Topics

Given business requirements, identify when it’s appropriate to use Model Builder.
Configure standard, custom, and BYO-LLM generative models.

Einstein Studio

The Einstein Studio tab in Data Cloud is the command center for AI models. In Einstein Studio, you can:

Use the model builder to create a new AI model with clicks, not code.
Connect to an existing AI model in an external platform such as AWS SageMaker, Google Vertex AI, or Databricks.
Connect to an existing LLM (Large Language Model) from third parties like OpenAI or Azure.

Einstein Studio Features

Agent Builder: Platform that allows businesses to easily create and customize AI-powered service agents for customer support, sales, and other business needs.
Prompt Builder: Tool used to create detailed, clear, and effective prompts for generating responses from AI models.
Model Builder: Einstein Studio feature used to build or bring your own predictive AI models or LLMs.

Binary Classification Models target business outcomes with only two possible results, which are represented as text data.

Outcome variable is the desired prediction or outcome of a model.

BYO-LLM (Bring Your Own Large Language Model) Integration allows you to build AI models externally and connect them to the Salesforce data using Data Cloud.

Conclusion

In conclusion, the Salesforce Certified AI Specialist certification offers professionals a valuable opportunity to gain in-depth expertise in incorporating AI within Salesforce CRM. Certified specialists can drive innovation in customer engagement and business processes by mastering essential tools like the Einstein Trust Layer, Generative AI, Prompt Builder, Agentforce Tools, and Model Builder. This certification enhances career growth while empowering professionals to help organizations fully leverage AI to strengthen customer relationships, optimize operations, and create personalized experiences. As AI continues to transform CRM, becoming a certified AI specialist places individuals at the leading edge of this evolving field.

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Salesforce Certified AI Specialist Guide & Tips

About the Salesforce Certified AI Specialist Exam