TL;DR:

• In January 2025, Salesforce renamed “Einstein Copilot for Salesforce” to “Agentforce” with no functionality changes. If you had Einstein Copilot, your setup still works exactly the same.
• Einstein Copilot (now often called Agent Studio) still exists for assisted productivity tasks like record retrieval and email drafting.
• Agentforce is a separate product tier for autonomous workflows that execute end-to-end without human prompting.
• You only need to migrate if you need autonomous execution across systems. Most organizations aren’t ready: 77% of B2B Agentforce implementations fail due to data quality issues.

In January 2025, Salesforce quietly renamed “Einstein Copilot for Salesforce” to “Agentforce.” The official release notes stated no functionality changes, just updated UI elements and permissions labels. For thousands of Salesforce admins, this created immediate confusion: was their Einstein setup obsolete? Did they need to migrate? Were they falling behind?

The reality: this was a rename, not a forced migration. If you had Einstein Copilot for Salesforce, it’s now called Agentforce in your Setup menu, but nothing about how it works has changed. Your permissions, workflows, and integrations remain intact.

The confusion stems from Salesforce’s broader strategy. Einstein Copilot as a product category still exists for assisted productivity tasks (now often branded as Agent Studio in some contexts). Agentforce represents a different tier: autonomous agents that execute complex workflows end-to-end without waiting for human input. The rename signals where Salesforce is heading, but it doesn’t mean existing Einstein users need to switch immediately. In fact, most shouldn’t.

Quick Comparison: Einstein Copilot vs Agentforce

Here’s the side-by-side breakdown:

The pricing model difference is significant. Einstein Copilot follows a per-user subscription model, while Agentforce charges per conversation or via Flex Credits (roughly $0.60 per use case at 120 credits per interaction). For high-volume autonomous workflows, Agentforce can be cheaper. For human-assisted productivity, Einstein’s per-user pricing is more predictable.

What Was Einstein Copilot?

Einstein Copilot launched as Salesforce’s AI assistant embedded directly into Sales Cloud, Service Cloud, and Marketing Cloud. It was designed to help employees work faster by surfacing insights, drafting communications, and recommending next actions based on CRM data. A service rep could ask, “Show me all open cases from premium accounts this week,” and Copilot would retrieve the data instantly.

The architecture was straightforward: text in, retrieve relevant data, reason about it, text out. It followed the classic predictive AI pattern: interpret information, don’t take action. This made it safe. If Copilot hallucinated or got something wrong, the blast radius was small because it never mutated system state.

Core capabilities included:

• Fetching and summarizing Salesforce records
• Drafting emails and case responses
• Providing next-best-action recommendations for sales and service workflows
• Answering questions about CRM data using natural language

Einstein Copilot still exists. It’s now often called Agent Studio or folded into the broader Einstein platform. The rename to Agentforce only applied to the specific “Einstein Copilot for Salesforce” agent type.

What Is Agentforce?

Agentforce is Salesforce’s autonomous AI platform, built for workflows that need to execute without waiting for human input. Instead of answering questions, Agentforce agents detect events, reason about them, and take action. A renewal agent, for example, can detect an upcoming contract expiration, check compliance rules, validate account health across CRM and ERP systems, and generate a renewal offer autonomously.

The architecture is fundamentally different. Agentforce is built on the Atlas Reasoning Engine, which gives agents the ability to plan multi-step workflows, evaluate business logic, and coordinate with other agents. It’s governed by Salesforce’s Model Context Protocol (MCP), which enforces access controls, logs every action, and ensures agents only operate within authorized boundaries.

Key technical components:

• Autonomous agents that reason, plan, and execute without human prompting
• Cross-system orchestration via MuleSoft APIs (not limited to Salesforce)
• Atlas Reasoning Engine for multi-step workflow planning
• Model Context Protocol (MCP) for governance and auditability

Salesforce reported 330% ARR growth for Agentforce, with over 9,500 paid deals and 3.2 trillion tokens processed. Marc Benioff called it “our fastest-growing product, exceeding expectations.”

The Real Difference: Reactive vs Autonomous

The core distinction isn’t about features. It’s about who initiates the work. Einstein Copilot waits for you to ask. Agentforce detects and acts.

Einstein Copilot operates on data: it retrieves records, summarizes information, and surfaces insights. Agentforce operates on metadata and process logic: it updates objects, fires automations, evaluates validation rules, and mutates system state. This is why Copilot can tolerate ambiguity while Agentforce cannot. Copilot’s output is text. Agentforce’s output is system change.

The risk profile is completely different. Predictive systems like Copilot can hallucinate without breaking anything. If Copilot suggests the wrong account priority, a sales rep catches it. Agentic systems like Agentforce break workflows when they get it wrong. If an Agentforce agent miscalculates contract eligibility and triggers a refund, that’s a real business error.

This is why Salesforce built the Atlas Reasoning Engine specifically for Agentforce. Execution requires context, and context lives in metadata. Agentforce must understand your org’s structure, dependencies, and business logic the way a seasoned architect would. Copilot doesn’t need that level of precision because it never takes action.

What Happened to Your Einstein Setup?

If you had “Einstein Copilot for Salesforce” before January 2025, it’s now labeled “Agentforce” or “Agentforce (Default)” in your Setup menu. That’s it. Salesforce’s release notes confirm: “This change won’t impact your implementations. Your agent is still available to help your Salesforce users with everyday business interactions, embedded right in the flow of work.”

Your permissions, workflows, integrations, and custom actions remain intact. Nothing about how the agent behaves has changed. The rename was a branding decision, not a technical migration.

“As we grow our team of Agentforce agents, we’ve renamed the Einstein Copilot for Salesforce agent type to Agentforce with no changes in functionality.”
— Salesforce Release Notes, January 2025

Einstein Copilot as a broader product category still exists. In some contexts, it’s now called Agent Studio. The rename only applied to the specific default agent type within Salesforce orgs.

Should You Migrate to Agentforce?

The decision comes down to whether you need autonomous execution or assisted productivity.

When to Migrate

Consider Agentforce if you need:

1. Autonomous compliance and governance workflows that run checks across multiple systems without human intervention
2. Cross-system orchestration like renewals that require validating data in CRM, ERP, and contract management tools
3. Proactive risk detection where agents surface issues and take corrective action before a human notices
4. High-volume repetitive workflows where per-conversation pricing beats per-user licensing

One case study showed 60% cost reduction after migration: from $180,000 annually to $72,000 by automating contract renewals and compliance checks.

When to Stay with Einstein

Stick with Einstein Copilot if you need:

1. Assisted productivity for sales reps and service agents (record retrieval, email drafting, recommendations)
2. Human-in-the-loop workflows where employees make the final decision
3. Predictable per-user pricing without usage-based variability

The catch: most organizations aren’t ready. 77% of B2B Agentforce implementations fail, and 69% fail beyond six months. The primary reason? Foundational data quality issues. Agentforce depends on clean metadata, consistent field definitions, and well-governed business logic. If your Salesforce org has duplicate records, conflicting validation rules, or poorly documented custom objects, Agentforce will amplify those problems.

What We’ve Seen in Real Deployments

Agentforce works when three conditions are met: clean metadata, strong governance, and narrow use cases. The organizations that succeed start small. They pick one autonomous workflow, validate it works correctly, then expand. The ones that fail attempt enterprise-wide rollouts before fixing foundational issues.

Metadata quality determines whether agents behave safely. Agentforce must understand field relationships, validation rules, automation dependencies, and business logic. If your org has metadata drift (fields with inconsistent definitions across objects), logic conflicts (overlapping validation rules), or missing lineage documentation, agents will make incorrect decisions.

The true cost is higher than the sticker price. One independent analysis found the real total cost of ownership is $13,600 per user per year when you include Data Cloud licensing, training, and metadata cleanup. Compare that to Einstein Copilot’s $125-550/user/month, which includes everything.

Deployment prerequisites we’ve seen work:

• Metadata audit and cleanup before agent deployment
• Single-workflow pilot (renewals, compliance checks, or case routing)
• Governance framework with clear escalation paths for agent errors
• Drift detection and lineage mapping for all custom objects
• Phased rollout with validation gates between stages

The pattern is consistent: organizations that treat Agentforce as a metadata discipline problem succeed. Those that treat it as a plug-and-play AI tool fail.

Frequently Asked Questions

Do I need to migrate from Einstein to Agentforce?

No. If you had Einstein Copilot for Salesforce, it was renamed to Agentforce in January 2025 with no functionality changes. You only need to migrate if you want to adopt autonomous workflows that execute end-to-end without human input. Most organizations should stay with their current setup until they have a specific autonomous use case and clean metadata.

What happened to Einstein Copilot?

Einstein Copilot still exists as a product category for assisted productivity tasks. The January 2025 rename only applied to the “Einstein Copilot for Salesforce” agent type, which is now called “Agentforce” in the UI. In some contexts, Einstein Copilot is now branded as Agent Studio. The broader Einstein platform continues to power predictive AI across Salesforce clouds.

How much does Agentforce cost?

Agentforce pricing starts at $2 per conversation or $500 per 100,000 Flex Credits (roughly $0.60 per use case at 120 credits per interaction). Einstein Copilot/Agent Studio costs $125-550 per user per month depending on your Salesforce edition and cloud. For high-volume autonomous workflows, Agentforce can be cheaper. For human-assisted productivity, Einstein’s per-user pricing is more predictable.

Why do most Agentforce implementations fail?

77% of B2B implementations fail due to foundational data quality issues. Agentforce depends on clean metadata, consistent field definitions, and well-governed business logic. Organizations that attempt enterprise-wide rollouts without fixing duplicate records, conflicting validation rules, and metadata drift see agents make incorrect decisions that break workflows. Successful deployments start with metadata audits and single-workflow pilots.

Can Einstein and Agentforce coexist?

Yes. Many organizations use Einstein Copilot for assisted productivity (sales reps getting recommendations, service agents drafting responses) while deploying Agentforce for specific autonomous workflows (contract renewals, compliance checks). They serve different use cases and can run in parallel within the same Salesforce org.