Driving More Success from your Agentforce Investments

The Shift Happening Inside Salesforce and Agentforce

If you caught the Q3 Salesforce earnings call, the numbers tell an undeniable story: Agentforce and Data 360 generated nearly $1.4B in ARR in 14 months. Agentforce alone surpassed $500M ARR, growing 330% year over year.

We’re watching Agentforce reshape how work gets done in real time. By operating directly in the flow of work, inside the systems where customer and company data already live, Agentforce moves beyond traditional AI tools. And Data 360 provides the foundation. It unifies structured CRM data with unstructured signals from emails, call transcripts, PDFs, knowledge articles, and Slack conversations. Slack acts as the operating system for daily work, enabling digital workers to collaborate alongside humans where business actually happens.

As a trusted Salesforce Summit partner, Asymbl helps customers translate the Agentforce ecosystem into measurable operational improvements. You don’t need a complex program or a full rearchitecture to compete. You simply need the right starting point. For agile businesses, this moment changes the equation: competing with enterprise giants no longer requires enterprise budgets. It requires clarity about where to begin. 

That perspective comes from experience. Prior to joining Asymbl, I was a Salesforce MVP and a CEO at a Salesforce consulting company that I eventually sold. Those experiences shaped how governance, technical implementation, and workforce orchestration were embedded directly into business operations, and Asymbl benefits from those foundations today. But, we recognize that not every organization can hire a Chief Digital Labor & Technology Officer with deep, hands-on Salesforce experience to accelerate their digital workers or connect Agentforce agents into a coordinated team capable of delivering sustained operational impact. What organizations can do today is adopt a more intentional operating model with proven methodologies. 

Next, we want to show you how teams make that shift by deploying their first digital worker or by building toward a coordinated workforce orchestration program with Agentforce as the foundation.

‍What Actually Changes When Agentforce Is Orchestrated

Throughout this blog, we reference AI agents and tools, and digital workers. Here’s what we mean by those terms.

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AI Agents: highly specialized AI capabilities designed to perform a narrow set of tasks with speed and predictability. They are typically deployed and owned by IT as standalone tools, require minimal coaching, and depend on humans to initiate, guide, and complete work. As a result, agents often operate in isolation, with both the agents and their data remaining disconnected from core business workflows.

Digital Worker: AI agents & AI tools orchestrated together and embedded within business workflows to deliver specific outcomes with clear roles, KPI’s, and coaching to accelerate output, improve consistency, and expand capacity. (e.g. Asymbl’s internal digital workers include: Casey (Marketing), Teddy (Sales), Polly (People Operations), etc…)

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The distinction between these definitions didn’t emerge in theory. It emerged through practice. 

Today, most businesses capture only a fraction of the value available in Agentforce. When sales, service, or IT AI agents run in isolation, workflows stall, and humans have to step in to trigger, guide, or finish tasks. As a result, measurable outcomes become restricted, and organizations struggle to see the return they initially expected. 

Customers often tell us they have unused Agentforce credits or that their agents struggle to perform consistently. In many cases, we find that each agent is simply waiting for the right knowledge, access, and coaching to contribute in a reliable way as digital workers. For our customers using Agentforce, this gap between isolated agents and digital workers is where workforce orchestration starts to matter, because it changes how work actually flows across the organization.

From Owning AI Agents to Managing Digital Workers

IT teams often carry the initial ownership of AI because they’re responsible for infrastructure, integration, and security, even though they don’t own workflow adoption or business outcomes. As Agentforce becomes more embedded in day-to-day operations, governance needs to extend beyond IT, with ownership of usage and outcomes clearly established within the business, where roles, accountability, and collaboration are better defined and managed.

For customers looking to increase the capacity of their SDR, Service, or IT agents, we often see that spinning up generic AI agents with generic data leads to generic outcomes, even when Agentforce is owned by IT. Real capacity comes from collaboration.

For Agentforce SDR agents, that collaboration must include sales leadership. Only sales leaders understand how leads should be qualified, when outreach should occur, which signals indicate buying intent, and how opportunities move through the pipeline. When IT and sales work together, SDR agents can move beyond isolated tasks and ad hoc AI tools to support end-to-end sales motion inside Salesforce.

The same is true for Agentforce Service agents. IT must partner with customer service leaders who understand demand patterns, ticket drivers, and where customers experience friction. Service leaders know when volumes spike, how workflows change, and which steps require escalation. That context allows Service agents to move beyond simple responses and meaningfully increase service capacity across channels.

For Agentforce IT Service agents, success requires collaboration between IT, People Operations, and line-of-business leaders. Business leaders define what content is accurate, which workflows matter, and how exceptions should be handled. They also help ensure agents operate fairly, consistently, and in line with organizational norms, especially when prioritizing requests or handling sensitive scenarios.

If your AI agent isn’t delivering these results you want right out of the gate, don’t give up. AI agents can get things wrong. When Agentforce agents are managed as part of the workforce rather than deployed as isolated tools, organizations expand their capacity in the ways they initially intended.

Where Agentforce Operates: Inside the Flow of Work

Digital workers built on Agentforce create value when they operate inside the systems and workflows where work actually happens. With Agentforce, this means more than deploying agents inside Salesforce alone. Sales, service, recruiting, and operations teams work across multiple systems. They collaborate in Slack, rely on third-party data, and move work through defined stages. Digital workers need to be embedded across that reality in order to move work forward.

Agentforce becomes powerful when agents do more than complete isolated tasks. A well-orchestrated Agentforce agent can interpret intent, apply context, and progress work through multiple workflow stages without requiring humans to manage each step. This is where the distinction between deterministic automation and probabilistic reasoning matters. Salesforce provides a powerful deterministic foundation, such as workflows, routing, approvals, and consistency, while Agentforce layers probabilistic reasoning on top, which allows AI agents to adapt to variation from human input.

We see this most clearly in practice when Agentforce agents respond flexibly while still advancing structured workflows. For example, in a recruiting workflow, a recruiter might send a simple request to the agent like, “Schedule an interview with Bobby,” or they might provide a more detailed instruction with a specific time and date, list of participants, and any other constraints. We’ve helped our Asymbl customers unlock productivity with Agentforce by interpreting both inputs, understanding the job context, and dynamically adapting the workflow, automatically completing required steps and surfacing the appropriate interface until the interview was confirmed. 

In this model, AI-powered workflow automations are not digital workers themselves. They are a part of the building blocks digital workers rely on. A digital worker coordinates multiple workflows, applies context and memory, and operates under management and governance to deliver consistent outcomes. 

This model is supported by a reusable Action library and integration architecture. With MuleSoft assembling Agentforce to ERPs, HRIS systems, and third-party platforms, IT can create a plug-and-play foundation where a single integration enables multiple digital workers. Rather than relying on brittle point-to-point connections, organizations establish a flexible layer that makes enterprise data accessible wherever it lives, allowing digital workers to operate reliably across the business.

Agentforce agents also require time, coaching, and iteration. They do not perform perfectly on day one. Teams that start with a clearly defined job to be done, manage agents as part of the workforce, and refine behavior over time see far better results than those who deploy broadly and expect immediate impact. When early outcomes fall short, it’s rarely because the investment was wrong. It’s because orchestration and management weren’t truly applied. This workforce approach is how teams unlock sustained productivity from Agentforce.

‍Why This Evolution Matters for Sales, Service, and IT

For sales, service, and IT leaders, digital workers reframe Agentforce from a set of agents into an orchestrated workforce that can reliably move work forward. Orchestration is what allows Agentforce to operate beyond task completion and contribute to real business outcomes. Without it, agents remain limited by shallow workflows and fragmented execution.

Here’s what that shift means in practice for sales, service, and IT.

Sales 

When an Agentforce Sales Agent is deployed, it functions as a digital teammate that manages the logic of the sale so humans can manage the emotion of the sale.

• Scale Revenue Output: Shift sales from a purely linear labor model to a more scalable one by using Agentforce to handle 24/7 lead qualification and meeting scheduling, increasing capacity without requiring proportional increases in operating expense.
• Compress the Sales Cycle: Automate handoffs across systems. The agent evaluates prospect fit, pulls relevant case studies from the CMS, and delivers personalized content to prospects without requiring manual rep involvement.
• Enable the “Zero-Admin” Rep: Move reps out of data entry and coordination work. The agent manages CRM updates, calendar logistics, and follow-up sequences so reps can focus on live conversations and deal progression.
• Improve Forecast Accuracy in Real Time: Replace gut-based forecasting with continuously enriched data. The agent identifies gaps in opportunity records and either prompts the rep for missing context or retrieves it from Data Cloud to keep forecasts current.

Services

Agentforce transforms service from a queue into a flow by connecting Data Cloud to your SOPs. The agent acts as a digital worker that:

• Owns the Intake: Instantly identifies customer intent and sentiment, applying your specific brand voice across channels such as SMS, WhatsApp, or Web.
• Executes the Workflow: Moves beyond suggesting answers to perform multi-step actions, such as processing a return or updating shipment status directly within backend systems.
• Manages the Gap: Resolves repetitive backlog autonomously while escalating complex or emotionally sensitive cases to human experts, that are complete with full context and a briefing.

IT

Agentforce shifts IT from ticket execution to workforce enablement where IT manages the security, connectivity, and performance of Digital Workers across the enterprise.

• Strategic Workforce Orchestration: Move from “fixing laptops” to “designing labor.” IT partners with LoB leaders to onboard Agentforce agents, mapping access to Data Cloud and ensuring agent Actions align with departmental goals.
• Centralized Governance (The Trust Layer): Maximize the value of Salesforce and Slack by consolidating AI work into a secure, governed environment. This eliminates shadow AI and ensures every interaction is grounded in company data and compliant with privacy standards.
• Deflection via Self-Healing Workflows: Target high-volume, low-complexity work. Deploy agents to autonomously handle identity management, software provisioning, and system status updates, reducing Tier-1 human intervention.‍
• Agile Integration Architecture: Replace brittle, hard-coded automations with a reusable Action library. By using MuleSoft and emerging protocols like Model Context Protocol (MCP), IT creates a plug-and-play integration layer. A single connection to an ERP or HRIS can power multiple digital workers across Agentforce, Slack, and even third-party AI platforms, ensuring enterprise data flows securely into the systems where work actually happens.

‍How We Got Here 

Digital workers are not the beginning of AI adoption. They’re the point where AI finally fits into how work actually gets done. At Asymbl, we help organizations reach this point using our three-step playbook: Define the Roles and Motivation, Onboard into the Flow of Work, Coach and Scale.

Before we even began offering workforce orchestration technology to customers, we began with the same Salesforce and Agentforce tools that everyone else adopted. We experimented.  We internally deployed digital workers to automate workflows. We learned what didn’t work. And what emerged is a workforce orchestration model born from practice, not theory. 

There’s a reason why Asymbl is the winner of the 2025 Salesforce Customer Success Award for Agentforce Innovation. It’s because we’re helping our customers move beyond silos and limitations. We're here to help you define your first use case and drive buying in a strategic plan in under 60 days.

Workforce orchestration has become a defining advantage for organizations seeking sustainable efficiency and scalable growth, and Asymbl supports teams in applying it with clarity and measurable results.

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