Salesforce has launched Agentforce 3, a significant update to its AI agent platform, aimed at solving key barriers to enterprise-scale adoption: visibility and control. The update introduces the Agentforce Command Centre, a complete observability solution that enables organisations to monitor, measure, and optimise AI agent performance across workflows.

“With Agentforce, we’ve unified agents, data, apps, and metadata to create a digital labour platform, helping thousands of companies realise the promise of agentic AI today,” said Adam Evans, EVP and GM of Salesforce AI. “The result is Agentforce 3, a major leap forward for our platform that brings greater intelligence, higher performance, and more trust and accountability to every Agentforce deployment.”

Agentforce 3 builds on deployments from over 8,000 customers since its October 2024 launch. According to Salesforce, companies like Engine, Grupo Globo, PepsiCo, UChicago Medicine, and 1-800Accountant have already seen measurable outcomes. 

Grupo Globo reported a 22% increase in subscriber retention, Engine reduced average customer case handle time by 15%, and 1-800Accountant saw autonomous resolution of 70% of administrative chat engagements during the 2025 tax season.

Ryan Teeples, CTO at 1-800Accountant, said, “We’ve established a strong deployment foundation and are focused on launching new agentic experiences and AI automations through Agentforce’s newest capabilities. With a high level of observability, we can see what’s working, optimise in real time, and scale support with confidence.”

The new Command Centre provides detailed analytics on latency, escalation frequency, and error rates, while offering real-time alerts and dashboards. It integrates with existing tools like Datadog, Splunk, and Wayfound via OpenTelemetry. 

It also supports AI-assisted development through Agentforce Studio, allowing teams to simulate agent behaviour at scale and generate topics and test cases using natural language.

Agentforce 3 also introduces native support for Model Context Protocol (MCP), enabling seamless interoperability with external systems. MuleSoft connectors allow existing APIs to be converted into MCP-compliant servers, while Heroku offers infrastructure for managing custom MCP servers. This integration supports secure, plug-and-play agent workflows.

“Salesforce’s open ecosystem approach, especially through its native support for open standards like MCP, will be instrumental in helping us scale our use of AI agents with full confidence,” said Mollie Bodensteiner, SVP of operations at Engine. “That level of interoperability has given us the flexibility to accelerate adoption while staying in complete control.”

The AgentExchange platform has also been expanded to include over 30 partners, including AWS, Google Cloud, Box, Cisco, IBM, PayPal, Stripe, Notion, WRITER, and Teradata. Customers can access a growing catalogue of MCP servers that allow agents to connect with external services.

Healthcare institutions are also finding use cases. “AI tools in healthcare must be adaptable to the complex and highly individualised needs of both patients and care teams,” Tyler Bauer, SVP for system ambulatory operations at UChicago Medicine, said. “We need to support that goal by automating routine interactions in our patient access centre…which would free up the team’s time to focus on sensitive, more involved, or complex needs.”

According to a forthcoming Slack Workflow Index, AI agent usage has surged 233% over the last six months. Salesforce’s updates are positioned as a response to this spike, addressing long-standing gaps in observability, governance, and enterprise readiness.

The company stated it will continue rolling out department-specific Command Centre configurations, starting with Service Cloud. These configurations allow supervisors to track agent performance in real time and escalate issues when needed.

Agentforce 3 is available now, with expanded global availability and flexible pricing designed to accelerate time-to-value for enterprise customers.

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