Salesforce Certified AI Specialist
Harness the power of Einstein AI to deliver intelligent, automated experiences in Salesforce. Master AI implementation, model configuration, predictions analysis, and optimization to drive data-driven decision-making and intelligent automation across your organization.
🆕 Winter '26 Release Updates
Winter '26 delivers groundbreaking AI enhancements:
- AI Decision Elements in Flow: Process complex unstructured data within automation flows using AI-powered decision-making
- Einstein for Developers (Pilot): AI assistance within VS Code and Code Builder to write Apex code, generate test classes, and explain existing code
- Agentforce Builder (Beta): Unified low-code/no-code workspace for designing, testing, and refining AI agents
- One-Click Account Research: AI-driven account research that automatically compiles answers to strategic questions and updates account fields
- Einstein Record Summary: Quickly summarize account, contact, lead, or opportunity records with key details in one click
- Einstein Conversation Insights Search: Filter and search key points from conversations with enhanced analytics
- Service Planner User Permissions: New permission set licenses required for Agentforce Service Assistant access
📋 Exam Objectives by Domain
1. Einstein AI Fundamentals (24%)
- Einstein capabilities and use cases
- AI ethics and responsible AI practices
- Data Cloud integration
- Winter '26: Agentforce Builder capabilities
2. Data for AI (19%)
- Data preparation and quality
- Feature engineering
- Training data requirements
- Data Cloud for AI models
3. Einstein Discovery (17%)
- Story creation and analysis
- Predictions and recommendations
- Model deployment
- Insights interpretation
4. Einstein Prediction Builder (16%)
- Custom prediction models
- Model configuration
- Prediction accuracy evaluation
- Implementation in automation
5. Einstein Bots (12%)
- Bot configuration and deployment
- Dialog design
- Handoff to agents
- Bot performance optimization
6. Einstein Next Best Action (12%)
- Recommendation strategies
- Action deployment
- Winter '26: Enhanced recommendation engine
- Performance tracking
❓ Sample Practice Questions
Question 1 (Winter '26): Which new Winter '26 feature enables flows to use AI for processing unstructured data and making intelligent decisions?
A) Smart Flow AI
B) AI Decision Elements
C) Einstein Flow Processor
D) Predictive Flow Actions
Answer: B) AI Decision Elements - This feature allows flows to leverage AI capabilities for complex decision-making with unstructured data.
Question 2 (Winter '26): What is the primary purpose of Agentforce Builder introduced in Winter '26?
A) Build custom Apex classes
B) Design, test, and refine AI agents using low-code/no-code tools
C) Create marketing campaigns
D) Manage user permissions
Answer: B) Design, test, and refine AI agents using low-code/no-code tools - Agentforce Builder provides a unified workspace for AI agent development.
Question 3: What minimum data quality threshold is recommended for Einstein Prediction Builder models?
A) At least 50 records
B) At least 200 records with both outcomes represented
C) At least 1,000 records
D) At least 10,000 records
Answer: B) At least 200 records with both outcomes represented - Balanced datasets with sufficient records ensure model accuracy.
Question 4: Which Einstein feature provides automated recommendations to users based on predefined business rules and AI predictions?
A) Einstein Discovery
B) Einstein Prediction Builder
C) Einstein Next Best Action
D) Einstein Analytics
Answer: C) Einstein Next Best Action - This feature combines business rules with AI to deliver contextualized recommendations.
Question 5: What is a key ethical consideration when implementing AI in Salesforce?
A) Model training speed
B) Bias detection and mitigation in training data
C) Number of API calls
D) Database storage size
Answer: B) Bias detection and mitigation in training data - Ensuring fair and unbiased AI models is a critical ethical responsibility.
📚 Study Resources
- Official Salesforce Resources:
- Hands-On Practice:
- Complete Einstein Discovery and Prediction Builder superbadges
- Build custom AI models with sample datasets
- Experiment with Winter '26 features: AI Decision Elements and Agentforce Builder
- AI Ethics & Governance:
- Responsible AI principles
- Bias detection methodologies
- Data privacy and security in AI implementations
💡 Pro Tips for Exam Success
- Master Einstein Fundamentals: 24% of the exam covers AI fundamentals - understand Einstein capabilities, use cases, and ethical considerations.
- Practice with Real Data: Hands-on experience building prediction models with Einstein Prediction Builder is crucial for exam success.
- Understand Data Requirements: Know the minimum data quality standards and best practices for training effective AI models.
- Study Winter '26 AI Features: Be familiar with AI Decision Elements, Agentforce Builder, and new Einstein capabilities.
- Focus on Practical Scenarios: Many exam questions test your ability to recommend appropriate AI solutions for business challenges.
- Know Ethical AI: Understand bias mitigation, fairness, transparency, and responsible AI implementation practices.
Last updated: November 2025 | Winter '26 Release