It’s Monday morning. You have three deals moving through pipeline, and a few approval requests stuck somewhere in Slack. Normally, you’d open five different apps, click through three portals, and maybe give up on things after lunch. But instead, you type a single question into Salesforce Global Search — and an AI teammate answers, takes action, and moves on to the next thing you need.
That’s Agentforce Coworker. It’s the newest addition to the Agentforce platform, and it’s changing how employees interact with CRM and other enterprise applications. But if you’ve been building on Agentforce, you might be asking: “We already have Employee Agents. What’s the difference? Do we need both?”
The short answer: Coworker is a full-blown autonomous agent that can reason, retrieve, take action, and delegate work to other agents when needed. Employee Agents are specialized agents built for specific workflows. Understanding how they complement each other is the key to designing a successful Agentforce architecture.
What Is Agentforce Coworker?
Agentforce Coworker is a full autonomous AI agent — your always-on AI teammate embedded directly into Salesforce Global Search (also known as “Ask Agentforce”), Slack, and soon Microsoft Teams, ChatGPT, Claude, and desktop apps. It’s not just a search bar or a routing layer. It can reason over your data, synthesize insights, take actions, and orchestrate other agents — all from a single conversation.
Built on Agentforce + Data 360, Coworker connects instantly to your CRM data — opportunities, cases, accounts, forecasts, service history, Tableau analytics — without any training or data modeling. It knows your business context from the first prompt.
The critical distinction: Coworker can do much of the work itself — answering questions, pulling reports, summarizing activity. When a task requires deep domain-specific automation, it delegates to the appropriate Employee Agent. It’s an agent that also orchestrates agents.
What Are Agentforce Employee Agents?
Employee Agents are designed to automate specific enterprise workflows. They handle complex, multi-step business processes with deep domain logic.
Examples include:
- Lead Qualification Agent — scoring inbound leads, routing to reps, enriching contact data
- Support Agent — ticket creation, escalations
- Sales Ops Agent — pipeline updates, forecast summaries, opportunity management
Each Employee Agent is built in Agentforce Builder with explicitly defined topics (what it can handle), actions (what it can do), and instructions (how it should behave). They run in the context of the authenticated user, respecting existing permission sets and sharing rules.
The key difference: Employee Agents require intentional design and configuration. They’re purpose-built for depth in a specific domain.
How They Work Together
Coworker automatically discovers all active Employee Agents in your org — no additional configuration required. It reads each agent’s metadata (name, description, topic definitions) and determines when to handle a request itself versus when to delegate to a specialized agent.
For straightforward questions — “What’s my pipeline this quarter?” or “Summarize the last 5 interactions on the Acme account” — Coworker handles it directly using its own reasoning and Data 360 capabilities. For domain-specific workflows that require deeper automation — submitting a deal, provisioning a customer, or executing a multi-step approval — Coworker delegates to the Employee Agent best suited for that task.
Conclusion
The mental model is simple: Coworker is your general-purpose AI teammate. Employee Agents are your domain specialists.
Coworker handles the breadth — reasoning over your entire org’s data, answering questions, synthesizing insights, and taking action across any context.
Employee Agents handle the depth — automating complex, multi-step workflows in specific domains. When the two work together, Coworker serves as both the capable first responder and the intelligent orchestrator that knows when to bring in a specialist.
Start with Coworker for an always-on, multi-skilled AI assistant. Build Employee Agents for complex, multi-step business processes with deep domain logic.