Salesforce Relaunches AgentExchange, Marking a New Phase In Its AI Agent Marketplace Strategy

AgentExchange enables enterprises to discover, evaluate, and deploy trusted AI agents with governance, integration, and scalability controls built in

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Salesforce launches AgentExchange, Marking a New Phase In Its AI Agent Marketplace Strategy
AI & Automation in CXCRM & Customer Data ManagementNews

Published: April 15, 2026

Francesca Roche

Francesca Roche

Salesforce has updated AgentExchange, its marketplace for AI agents, as part of its broader shift to agentic customer experience. 

Having previously announced the early version of the marketplace last year, this update has shifted from a builder marketplace of components to a usable catalog of deployable AI agents, acting as a trusted hub for enterprises to discover, evaluate, and deploy solutions 

AgentExchange positions AI agents as an extension of the workforce that can handle routine or complex tasks across the customer lifecycle, from service inquiries to sales engagement. 

Brian Landsman, CEO of AgentExchange and EVP Global Partnerships at Salesforce, explains how the marketplace model extension gives customers a single place to build and deploy agents while helping partners reach more users and scale distribution more efficiently.

“Twenty years ago, we pioneered the concept of an app marketplace with AppExchange, and we’ve been number one ever since,” he said. 

“Now, we are evolving the marketplace for the agentic era, bringing into one place everything that customers need to build and deploy agents, apps, and integrations across the enterprise, with the controls they expect.  

“With the new AgentExchange, partners get better access to Salesforce’s entire install base and tools that help them build, manage, and scale their distribution more efficiently than ever before.”

A Unified Hub for Enterprise AI Solutions

Salesforce AgentExchange is a centralized marketplace for AI agents, designed to help enterprises build, deploy, and scale AI-driven customer and business interactions using a partner ecosystem rather than relying only on in-house development. 

Within the marketplace, customers can browse prebuilt AI agents, components, and integrations designed to perform specific tasks, such as handling service queries, supporting sales outreach, or automating workflows based on their use case. 

These agents are composed of defined actions and topics, which determine what they can do, and they can be customized to fit specific business processes. 

The platform can also streamline procurement and management through unified billing and governance controls, so teams can move from discovery to deployment with minimal friction. 

Bringing together previously separated ecosystems like AppExchange and Slack Marketplace creates a unified destination for discovering, deploying, and managing AI-driven solutions with consistent governance, streamlined procurement, and easier integration across the enterprise. 

By making AI adoption more practical and scalable helps reduce development time and cost while improving consistency and governance by having solutions that are already vetted by Salesforce, lowering risk particularly in customer-facing environments. 

The marketplace is also designed for a wide range of sectors, including customer service, sales, marketing, IT, and operations, as well as developers and partners who build and distribute solutions. 

Shifting AI from a complex, resource-heavy initiative to a modular, repeatable approach enables organizations to deliver better customer experiences more efficiently. 

Accelerating CX Transformation and Modernization

Salesforce’s AgentExchange helps deliver value to CX by simplifying access to ready-made AI agents that can be deployed directly into service, sales, and engagement workflows. 

For customers, this ensures faster and more consistent service experiences, speeding issues resolution more quickly with agents pulling on prebuilt actions, industry knowledge, and integrations to complete tasks such as answering questions, updating records, or routing cases without unnecessary delays. 

As a result, this reduces friction in everyday interactions and improves responsiveness across channels. 

For CX teams, the platform helps reduce operational load and improve efficiency by enabling the use of prebuilt agents that already contain tested workflows and best practices.  

This allows agents to assist with case handling, summarization, and routine service tasks, which enables human agents to focus on more complex or high-value interactions. 

Faster deployment also improves consistency, as the same agent logic can be reused across different teams and regions, reducing variation in service quality. 

For CX leaders, AgentExchange provides a controlled way to scale AI across the organization while maintaining governance, security, and compliance standards, allowing leaders to standardize how AI is deployed across service and engagement functions while still allowing flexibility through partner-built solutions.  

The platform also supports faster transformation, making it easier to modernize customer experience, improve efficiency metrics such as resolution time and cost to serve, and build a more scalable operating model that blends human teams with AI-driven agents. 

The Shift to Agentic CX

Salesforce’s broader shift toward Agentic CX is about moving from AI that assists people to AI that actively performs work across the customer lifecycle. 

Instead of treating AI as a set of tools embedded in individual features, Salesforce is positioning autonomous agents as a core layer of the platform that can understand intent, take actions, and complete end-to-end tasks across sales, service, marketing, and commerce.  

This reflects a transition from static workflows and copilots toward systems that operate continuously in the background, coordinating data, decisions, and actions in real time to resolve customer needs faster and with less manual effort. 

The operating model also changes how teams are structured around CX delivery, as human employees remain central, their focus shifts toward complex problem-solving, judgment, and relationship management, meaning AI agents take on repetitive, high-volume, and data-heavy work, increasing overall capacity and consistency.  

Over time, this creates a more distributed system of work where outcomes are delivered through collaboration between humans and autonomous agents, rather than through linear workflows managed step by step. 

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