22 AI Agent Terms Every Business Leader Needs To Know
To fully unlock the power of Salesforce Agentforce and Einstein AI, business users and admins alike need a shared language. Here’s your glossary, no jargon, just clarity.
1. Agentic AI
A form of AI that uses autonomous agents to complete multi-step tasks without needing human instruction for every action.
Agentforce is Salesforce’s agentic layer, purpose-built to orchestrate these workflows inside your CRM.
2. AI Agent
An intelligent agent powered by LLMs (like Einstein GPT) that decides what to do and how to do it — across tools, systems, and data.
This is the core of Salesforce Copilot Studio.
3. Agent-to-Human Handoff
A seamless transfer from AI agent to human rep, with full context preserved.
Einstein Bots support this natively — preserving history via Service Cloud’s Omni-Channel routing.
4. Agentic Workflow
A process where agents work collaboratively (or in parallel) to complete business tasks end-to-end.
Flow Orchestrator + Agentforce = true agentic workflows inside Salesforce.
5. Complexity Threshold
The point at which a task becomes too complex for an AI agent — triggering a fallback to a human decision-maker.
Configure thresholds in Copilot Studio with human-in-the-loop logic.
6. Context Awareness
The ability of AI to remember past actions, user preferences, and real-time inputs to personalize responses.
Einstein Copilot uses context memory to tailor user experiences and improve response quality.
7. Deterministic Reasoning
Rule-based logic (like Salesforce Flows) that always outputs the same result.
Useful for predictable workflows, but lacks flexibility of AI agents.
8. Digital Labor
AI-based labor that scales human decision-making.
Salesforce uses this concept in AI-driven case resolution, contract analysis, and lead qualification.
9. Digital Worker
A software “employee” (aka AI agent) that performs structured tasks across departments.
Think: an agent that reconciles finance reports, routes service cases, and drafts responses via Einstein GPT.
10. Dynamic Resource Allocation
The AI agent’s ability to optimize compute and memory usage based on task complexity.
Enables scalable automation in high-load environments like Salesforce Service Cloud or Marketing Cloud.
11. Explainability and Transparency
The AI’s ability to explain why it made a decision and show how it did it.
Einstein Trust Layer and Prompt Studio improve explainability across Salesforce AI.
12. Headless AI Agent
An agent that works invisibly via APIs or triggers, no UI needed.
Useful for Salesforce backend operations, like syncing ERP data or scoring leads silently.
13. Intent Recognition
Detecting what a user really wants based on their message.
Used in Einstein Bots and Copilot to determine action paths — like routing to billing vs. tech support.
14. Long-Term Coherence
The agent’s memory over time, remembering previous chats, issues, or business logic.
Key for subscription renewals, service follow-ups, or complex B2B sales in Salesforce.
15. Multi-Agent System
A network of specialized AI agents that collaborate across departments.
Imagine: a service agent, billing agent, and inventory agent coordinating via Flow Orchestrator.
16. Multimodal AI
AI that interprets text, voice, images, or documents.
Einstein AI can process PDF contracts, customer emails, and voice logs.
17. Ontology
A structured data map the AI uses to understand relationships between terms.
Critical for CRM objects like Accounts, Opportunities, and Products to make sense to AI agents.
18. Polyphonic AI
Multiple agents with unique specializations working simultaneously, managed by a lead orchestrator.
Exactly what Salesforce Agentforce is designed for, one agent pulls the strings of many.
19. Probabilistic Reasoning
The ability to make predictions when data is incomplete or uncertain.
Used by Einstein GPT to draft emails or next-best-actions based on likelihood, not rules.
20. Reasoning Engine
The core logic system that helps agents decide what to do next based on rules, data, and patterns.
Einstein Copilot Studio houses this logic in prompt chains and decision flows.
21. Reinforcement Learning
The agent improves over time through trial, error, and feedback loops.
Salesforce research teams are already exploring this for Copilot feedback training.
22. Sentiment Analysis
AI that reads emotional tone, excitement, frustration, urgency, in a user’s message.
Einstein Sentiment is already available in Salesforce to classify messages in Case or Chat.
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