Salesforce Expands Agentforce With a New Portfolio of AI Agents Built for High-Value Work

SAN FRANCISCO, September 11, 2026 — Every company is racing to turn AI into real business results. But the hardest part is no longer getting AI to answer a question. It’s getting AI to do the work that matters across every business function.

Over the past two years, Salesforce has worked alongside customers across thousands of agentic deployments and delivered 7 billion Agentic Work Units (AWUs) across Agentforce and Slack, including 3.2 billion in Q2 alone. That experience has made one thing clear: putting agents to work requires more than intelligence. Agents need to understand the job, work across the business, and keep moving toward a goal as the work gets more complex.

Today, Salesforce is introducing a new portfolio of job-ready agents built to take on high-value work across sales, service, commerce, employee experience, and the back office. Connected to Customer 360, these agents can work with the customer context and business processes companies already have in Salesforce. These agents come ready for the job and are powered by new Agentforce technology that enables them to pursue goals over time, learn new skills, work with other agents, and continuously improve.

Also see:

Everything from Dreamforce 2026: Claudeforce, Customer Success, and Agents at Scale

A new approach to building agents

Instead of building every agent from scratch, companies can now start with agents designed around the jobs where AI can have an immediate business impact. Each comes with the skills, actions, and data models required for the job, and can be tailored to how each company works.

A LinkedIn post from the company said: Salesforce’s new job-ready agents (Casey, Piper, Hunter, and more) are specifically built to take on high-value work across sales, service, commerce, employee experience, and the back office. Crucially, some of the most valuable work in a business can’t be completed in a single conversation. That’s why Salesforce built a new long-horizon runtime for Agentforce, enabling agents to pursue goals across days and weeks instead of completing only a task or interaction. Hunter is the first agent to run on the long-horizon runtime; soon, more agents across the portfolio will run on it, and customers will be able to build their own long-horizon agents.

Here’s a sampling of what these agents are capable of doing in business environments:

• Casey, your help agent, resolves customer service issues across voice, SMS, WhatsApp, and web chat, with pre-built support for FAQs, returns, account management, human escalation, and more. GA now.
• Paige, your IT & HR service agent, resolves requests across Slack, portals, and the tools employees already use. GA now.
• Carter, your shopper agent, helps shoppers discover and compare products, get questions answered, and convert with in-chat checkout. GA now.
• Hunter, your outbound sales agent, works a sales pipeline from research to outreach, collaborating with sellers over weeks and months. Pilot now; GA November ’26. (Ed: More on Hunter ahead in the story.)
• Marshall, your supply chain agent, orchestrates end-to-end back-office processes, automates manual work with deterministic execution, and provides an audit record of every action. GA now.
• Piper, your inbound pipe gen agent, works across websites and inboxes to engage, qualify, and convert inbound leads into pipeline for B2B sales and marketing teams. GA now.
• Fin, your customer agent, resolves complex customer experience workflows across every channel. Powered by Operator, a customer operations agent, and Fin Apex, a set of custom models trained for customer experience, Fin enables CX teams to deploy quickly and continuously optimize performance. GA now.

Customers can tailor each agent to their business — including giving it their own name — so the agent becomes an extension of their brand and workforce.

Every agent operates within the customer’s business rules, permissions, and security. With Agent Script, Salesforce’s open-source language for agent behavior, customers can also combine AI reasoning with deterministic rules for granular control over how agents make decisions and take action.

Measurable results

These agents are already delivering measurable results:

• 50% of Engine’s chat inquiries are fully resolved by its help agent, Eva.
• 60% of Perk’s sales pipeline is built by its outbound sales agent, Hunter.
• 70% of Autism Queensland’s administrative requests are resolved by its employee service agent, Paige.
• 90% of core shopper journeys are handled by Hibbett AI, which went live in six weeks.
• 4x the conversation volume is now driven by Asana’s website agent, Piper. Customers deploy Piper in 45 days on average.
• 79% of Anthropic’s conversations that Fin sees are resolved autonomously.

Some of the most valuable work in a business can’t be completed in a single conversation. A seller doesn’t just research an account once. Winning an opportunity can require weeks of outreach, new information, changing priorities, and decisions along the way.

That’s why Salesforce built a new long-horizon runtime for Agentforce, enabling agents to pursue goals across days and weeks instead of completing only a task or interaction.

More on Hunter

Hunter is the first agent to run on the long-horizon runtime. Over time, more agents across the portfolio will run on it, and customers will be able to build long-horizon agents of their own with Agentforce.

With the new runtime, a seller might ask Hunter to rescue their at-risk deals before the end of the quarter. Hunter can turn that objective into a measurable goal, build a plan, and begin working toward it — determining the tasks to complete, the tools and context required, and the guardrails that define when it can act autonomously and when seller approval is required.

As the work unfolds, Hunter can incorporate new information and adjust the plan while keeping the seller in control. Underneath, three capabilities make that possible:

• Memory preserves context and progress across sessions, so work doesn’t stop when the interaction ends.
• Durable execution keeps plans running over time and allows an agent to resume or course-correct as circumstances change.
• Dynamic steering adapts an agent’s behavior based on an individual user’s feedback and direction.