The Agentforce Operations Process Evolution Playbook: 8 Steps to Scale AI Process Automation
A practical execution guide for the leaders turning a subset of processes into measurable value, using each win to fund the next.
A practical execution guide for the leaders turning a subset of processes into measurable value, using each win to fund the next.
Diane Roberts, Senior Director, Agentic Solutions Leader
Husein Tambawala, VP & CCO, Agentic Process Automation and Intelligence
Most enterprises face a familiar choice: Spend years auditing and re-engineering before deploying AI, or rush to push models across the business and hope value follows. Both stall before they pay off. The faster path — and the one teams using Agentforce Operations are proving in production — is to work process by process. Identify a single high-impact business process, digitize it, orchestrate it with agents, and let the result fund the next one.
That is what we mean by an AI process: a single business workflow, end-to-end, redesigned so agents and humans share the work. The agent handles the high-volume, repeatable steps. The human owns judgment, relationship, and final accountability. The process is the unit of value, not the model or the platform. Every process moves on its own journey, and value builds inside that process in three orders. First, efficiency as workflows get digitized; second, better decision-making as agents take on orchestration; and third, value chain transformation as AI-first design takes hold.
Consider what wasn't possible before:
AI processes are where agents prove measurable business value.
Salesforce customers running this 8-step play with Agentforce Operations are seeing concrete returns at each stage of the Agentforce Operations maturity journey: 15–20% efficiency gains in the first 60 to 90 days as workflows get digitized, 40–60% gains as agents take on orchestration over 60 to 180 days, and 70–95% gains as AI-first design takes hold over one to two years.
One energy company added roughly 40 agent-executed steps to a single invoice validation process and cut tens of millions in annual cost. An electronics manufacturer pulled a full day out of inventory hold time. Both wins came from picking the right process and shipping it, not a multi-year transformation program.
This playbook picks up where that thinking leaves off. It's the practical, step-by-step companion: how to stand up your first AI processes with Agentforce , how to govern them, and how to scale from a first production deployment to enterprise-wide adoption.
Each step assumes the strategic case has been made. The focus here is execution — what to do, in what order, with which owners, and against which measures of success.
Three market pressures make process-by-process AI execution urgent.
The cost imperative. The overhead of running a globally competitive, compliant organization keeps climbing. Hiring more people can't keep pace with regulatory and operational complexity. The early returns are real: McKinsey's 2025 State of AI report finds a majority of respondents reporting cost reductions from generative AI across most business functions — 61% in supply chain, 58% in service operations, 56% in strategy and finance.¹ But the same report finds 80%+ of organizations haven't yet translated those wins into enterprise-level EBIT impact. The function-level case is proven; the next step is scaling AI across whole processes — which is what agentic systems are built for.
The efficiency ceiling. Legacy automation plateaus at incremental gains, optimizing isolated steps. Agentic systems handle complex, multi-step reasoning across entire processes. McKinsey finds that only 21% of organizations using generative AI have fundamentally redesigned even some of their workflows — and only 1% of executives describe their rollouts as "mature."² The ceiling isn't the technology. It's the redesign work most companies haven't done yet.
The time-to-market imperative. Speed is now a structural advantage. Gartner predicts that by 2028, at least 70% of customers will start their service journeys through a conversational AI interface³ — collapsing handoffs that used to take days into seconds, and pulling that compression upstream into every adjacent process.
The shift that matters most. Shift from measuring task-level efficiency to measuring P&L impact. Steps 1 through 3 set the strategic frame; Steps 4 through 8 turn it into execution. Find your innovation champions early. They're how the organization gets ready.
| Step | Name | Key Outcome |
|---|---|---|
| 1 | Strategic Alignment | Blueprint Portfolio defined with scope, success criteria, roadmap |
| 2 | Organizational Readiness & Communication | Internal brand, comms plan, and innovation champions engaged |
| 3 | Process Selection for Scale & Value Baselining | 3–5 approved processes with scorecards, flows, and a defined no-go list |
| 4 | Demonstrate Quick Value (Agentic Day 1) | Live deployment with ROI dashboards, accuracy targets, published win stories, and Center of Excellence (CoE) established |
| 5 | Refine the Roadmap & Reimagine the Operating Model | Executive-approved roadmap with future-state operating model and CoE evolved from live production learnings |
| 6 | Implement the Roadmap, Scale and Measure | CoE maturation, scaled blueprints, and live executive ROI dashboards |
| 7 | Recognize and Reinforce Value | CFO-ready value scorecard, success stories, and refined roadmap for next phase |
| 8 | Scaling Agentic Processes & Operating Model Evolution | AI-First culture with self-sustaining CoE and enterprise-wide agentic patterns |
Agentforce Operations (AFO, formerly Regrello) — Salesforce's AI-first platform for automating and orchestrating complex middle and back-office processes.
Agentic Day 1 — Your first live production deployment, 1-2 use cases.
Blueprint — Agentforce Operations' term for a structured, reusable process template with a defined start and end. Once published, it becomes the master pattern that workflow instances run from.
Center of Excellence (CoE) — The internal team that sets standards, governance, and best practices for building and scaling AI processes.
Goal: Anchor your AI process portfolio to the organization's top-tier business objectives.
Before you select a blueprint or build anything, you need a clear answer to one question: Which business outcomes will AI processes change in the next 12 months? The decisions you make here define scope, success criteria, and the narrative that carries the work forward.
This is what your first 90 days with Agentforce Operations look like. Step 1 starts before any technology decision — you align on which business outcomes will move.
Execution approach:
Goal: Prepare the organization to move. Build the internal narrative, identify your champions, align leadership, and update incentives before execution begins.
Transformation stalls when the organization isn't ready to move with it. Step 2 builds the human infrastructure: the narrative, the champions, and the leadership alignment. By the time execution begins in Steps 3 and 4, the organization is already pointed in the right direction.
Execution approach:
Goal: Identify the processes where AI agents can deliver real, measurable value, and build the foundation for everything that follows.
You are not selecting every possible process. You are finding the ones that are thorny enough to matter, feasible enough to win, and backed strongly enough to scale. The goal is a real production deployment with measurable business value, not a POC (proof of concept). Some candidates that enter this step won't make it through — that is exactly how it should work.
Execution approach:
Goal: Deliver immediate, measurable impact and build organizational confidence through your first live production deployment.
Agentic Day 1 is the foundation of your roadmap. The processes you deploy, the wins you document, and the confidence you build are what unlock investment and momentum for everything that follows. The 30 to 60-day window assumes specific conditions are met: a pre-built AFO or partner blueprint that fits the process, low-integration scope, and native connectors to your source systems. Most enterprises won't have all three on every candidate — that's expected. Use the portfolio approach in Step 3 to find the candidate where they line up. Where they don't, plan for a longer first window and capture the gap in Step 5.
Execution approach:
Goal: Establish a clear picture of what your platform can actually do, define ownership across every layer, and build a roadmap that reflects reality.
Step 4 proved the concept. Step 5 is where you confront the full picture: the platform's real capabilities and limits, the support model, and the operating-model shift to scale. The common failure here is building a roadmap on unresolved ownership, integration, and support questions. Resolve those first.
Execution approach:
Goal: Scale proven workflows with discipline. Anchor every decision to one question: is this generating more value than it costs?
Step 6 is where the program either compounds or stalls. Teams that scale successfully stay anchored to value, build their builder community with real support, and treat governance and compliance as structural inputs rather than afterthoughts.
Execution approach:
Goal: Turn proven results into continued investment.
Step 7 is where the work you have done becomes the mandate for what comes next. The wins from earlier steps are only as powerful as your ability to communicate them clearly, connect them to the business case, and use them to unlock the next phase of the roadmap.
Execution approach:
Goal: Earn the right to scale by closing governance and security gaps first, then expand from centralized execution to decentralized innovation.
The foundation must be enterprise-ready before any phase begins. Gaps exposed at scale are far harder to close than gaps resolved before it. Step 8 plays out in three phases.
Successful adoption of Agentforce Operations does not happen all at once; it is built through a disciplined, targeted strategy. By systematically focusing on individual processes, proving incremental value, and driving each process toward its optimal value potential, organizations chart a sustainable path forward.
Ultimately, an AI-first operating model is forged through the repeatable execution of these eight steps until the core business model has fundamentally evolved.
Ready to identify your first AI process? Spend a day with us. Salesforce's free one-day Agentforce Operations Proof of Concept workshop helps your team scope, build, and walk away with a working prototype.
Learn more about Agentforce Operations at salesforce.com/agentforce/operations/ .