What’s New in Agentforce 3.0? Salesforce AI Just Got Smarter
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Agentforce 3: Salesforce’s Solution to AI Agent Visibility & Control Challenges

In the past few years, AI has grown rapidly in the tech industry. It can now draft important emails, create MOMs, schedule your meetings, and even automate low-priority tasks to improve productivity significantly. That's why many major technologies have opted to introduce Agentic AI to enhance the workflow and streamline routine tasks through automation. One of the biggest players in this shift is Salesforce, which introduced Agentforce (AI-powered assistant) in 2024.

Since its launch, this platform has helped its customers deliver undeniable value to Salesforce customers. And now, by introducing Agentforce 3, Salesforce has redefined the AI automations by providing real-time command centers, 200+ prebuilt AI actions, and unified agents into one powerful platform.

In this blog, let’s dive further into the world of Agentforce 3.

The Rise of Agentforce

Although the Salesforce AI solution was launched just less than a year ago, this AI-powered assistant has become a great success within Salesforce. With the implementation of autonomous AI embedded into business operations and generative AI capabilities that summarize record details, create customer-centric emails, and even generate knowledge articles, businesses have been able to automate like never before.

Salesforce reports that since the introduction of Agentforce, AI agent usage has grown by 233% in just six months, and over that same period, 8,000 customers have signed up to deploy the Salesforce AI platform for their businesses.

This was the evolution of Agents from mere chatbots to AI agents capable of managing customer relationships, capturing and updating customer details and requirements, and interacting with custom automations to perform respective tasks. 


One powerful example is UChicago Medicine, which has implemented Agentforce to improve patient experience in healthcare. They focused on automating non-clinical support like FAQs, appointment scheduling, and real-time logistical help (ex., parking info), especially after business hours. This addition helped reduce pressure on staff and improve response times.


UChicago Medicine is also exploring Salesforce AI for modern customer support,  to guide patients through care via phone and web chat, allowing them to refill prescriptions, schedule appointments, verify insurance, and receive real-time logistical support like parking updates.


“AI tools in healthcare must be adaptable to the complex and highly individualized needs of both patients and care teams,” said Tyler Bauer, Senior Vice President for System Ambulatory Operations at UChicago Medicine.


What’s New in Agentforce 3?

The new Agentforce release decided to tackle some of the major challenges, such as a lack of real-time visibility, limited control, scalability, and complex integration issues. Let’s look at the important additions to the Salesforce AI solution upgrade:


  1. Agentforce Command Center

    Earlier organisations couldn’t monitor the AI agents in real time, hence the transparency of performance and decision-making was very limited. Salesforce Agentforce 3 changed that by introducing the Command Center, a comprehensive observability solution. Now, users get a full observability solution that lets them:

    This provides the team with a unified view to monitor agent health, measure performance, and optimize outcomes:

    • Analyze interactions: With the help of the command center, users can analyze all the interactions, understand the trend in usage, and get AI-based recommendations to continuously improve their Agents.

    • Track Agent Health: Monitor the agents live for escalation, error rates, and latency. Get real-time updates when something unexpected happens so the team can intervene to keep agents running smoothly.


    • Measure Key Performance Indicators (KPIs): Access dashboards displaying adoption rates, user feedback, success rates, operational costs, and the effectiveness of various topics.


    • Seamlessly Integrate with Existing Systems: Agent activities are meticulously logged in Data Cloud via OpenTelemetry, ensuring compatibility with widely used tools such as Datadog, Splunk, and Wayfound.

    • Utilize Custom Command Centers: Observe agent performance in real-time, integrated with human team insights, initially within Service Cloud and expanding to all departments.

    • Faster Agent Creation: Employ natural language in Agentforce Studio to craft topics and test cases, and simulate agent behavior at scale using the Testing Center.

  2. Model Context Protocol (MCP)


    Agentforce introduces Model Context Protocol (MCP) to solve one of the biggest challenges in AI–interoperability. Seamless communication between AI-powered agents and enterprise systems has been a hurdle, but the platform’s native support for MCP could be a game changer. 


    With MCP, AI platform can connect to enterprise platforms easily, without compromising control or security.

    • Plug-and-Play Integration: Connect with enterprise systems without custom code.

      (MCP provides an open integration layer for tools, apps, and workflows supporting plug-and-play features without coding.)

    • Native-support for MCP into Agentforce: MCP lets agents access enterprise resources with full security controls.

      (Salesforce’s AI solution will have a natively supported MCP client that’ll help it to connect with any MCP-compliant server without any custom code. This helps the platform to access enterprise resources while governing them using your security policies. This can help Agents to expand their functional reach by integrating with platforms like AWS, Google Cloud, etc.)

    • Mulesoft MCP Connector: Turn APIs into agent-ready endpoints with built-in tracking and policies.


    • (The latest version of Agentforce leverages Mulesoft to turn APIs into MCP servers: With the help of Mulesoft’s new MCP Connector feature, we can convert APIs into an Agent-ready resource with security policies and activity tracking. This helps the team to orchestrate multi-agent workflows.)

    • Heroku-Hosted MCP Servers: Easily host and manage your own MCP servers quickly using Heroku.

      (Heroku Managed Inference and AppLink make it fast and easy to deploy, register, maintain, and connect your custom MCP servers.)


“Salesforce’s open ecosystem, especially with MCP support, helps us scale confidently, connecting agents to systems securely and without coding,” said,  Mollie Bodensteiner, SVP of Operations at Engine.



200+ Prebuilt AI Actions & 30+ MCP Servers

With AgentExchange, admins now have access to hundreds of AI actions and MCP integrations. This expands AgentExchange's ready-to-use solutions, such as patient scheduling, to advertising proposal generation, to vehicle servicing, and more. Along with this, we have MCP servers from partners like AWS, Cisco, Notion, IBM, PayPal, Teradata, and many more that are already contributing resources. These prebuilt, ready-to-use features will prove to be very impactful for the Salesforce Agentforce Admins, easy to equip them with the trusted tools they need to drive value fast, as also explained in how Agentforce for Sales Cloud can multiply sales performance.


More Enhancements in Agentforce 3

Some other important improvements that the AI platform brings are:


  • Greater accuracy through Web Search + Inline Citations: Agentforce’s version 3 features trusted, expanded grounding through the addition of web search as a data source, allowing agents to go beyond internal data to answer requests, as well as inline citations that provide references to the grounding sources used in responses.

  • Global Reach: The third-generation AI solution features an expanded global footprint, deploying to Canada, the U.K., India, Japan, and Brazil to serve AI agent traffic within those regions. This release also adds support for 6+ new languages, including French, Italian, German, Spanish, Japanese, and Portuguese. Also, 30+ additional languages are rolling out in the coming months.

  • Enhanced resiliency with automatic model failover: In case of outages or slowdowns, the platform can now switch between AI models automatically to stay online.


Final Thoughts

Salesforce has expanded its AI platform to new heights with the introduction of Agentforce 3. This update focuses on solving real-time visibility and control issues and makes AI-powered agents more impactful and customer-centric. Teams now have the ability to supervise the agents, step in when needed, and smoothly integrate with external systems to enhance the agent capabilities.


With hundreds of prebuilt actions and simplified agent creation, the AI platform’s version 3 introduces groundbreaking possibilities in the field of AI Automation. And it also raises the bar of customer expectations after every interaction they have with AI Agents. 


As Adam Evans, EVP & GM of Salesforce AI, says it best:

“We’ve unified agents, data, apps, and metadata to create a digital labor platform.” 


Want to Bring Agentforce AI into Your Business?

Cloud Science Labs can help you implement and optimize Salesforce’s latest AI-powered solutions, like Agentforce 3, customized to your industry needs.


Talk to our Salesforce experts today.


FAQs:

1. What is the difference between Einstein and Agentforce?

Salesforce Einstein is the broader AI layer that powers insights, predictions, and automation across the Salesforce ecosystem. This AI solution, on the other hand, is built specifically to create and manage AI agents, digital assistants that can interact, decide, and act on tasks autonomously.


2. Is Agentforce worth it for my business?

If your business deals with repetitive customer interactions, internal workflows, or multi-step service requests, this AI platform can definitely add value. It helps automate low-priority, time-consuming tasks like generating emails, updating records, or guiding customers through standard queries. So yes, it's worth it.


3. What’s new in Salesforce Agentforce 3?


  • Command Center: A real-time dashboard to monitor your AI agents.

  • Model Context Protocol (MCP): Makes it easier to connect an AI platform with external tools and systems.

  • 200+ Prebuilt AI Actions: Ready-to-use tasks like scheduling, record updates, proposal generation, and more.

  • 30+ MCP Server Integrations: Including AWS, Cisco, Notion, IBM, and more.

  • Improved Resilience & Language Support: With automatic model failover and GA support for over 6 languages.

 
 
 
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