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What Is Agentforce by Salesforce?

Agentforce is Salesforce’s AI agent platform that turns your CRM, Data Cloud, and automation into digital workers that plan, reason, and act across sales, service, marketing, and operations. Instead of just surfacing insights, Agentforce agents can take action in your existing Salesforce org.

Connect with Salesforce expert Check AI agent guide

Agentforce by Salesforce is an AI agent platform for building “digital labor” on top of Salesforce. Teams use it to configure autonomous agents that understand your Salesforce data, follow your business rules, and trigger workflows — from updating opportunities and routing leads to resolving cases and orchestrating personalized campaigns. Because Agentforce is embedded in the Salesforce platform, it can leverage Data Cloud, flows, APIs, and Einstein models to automate work while keeping humans in control.

What Does Agentforce Actually Do?

Creates autonomous AI agents — Configure sales, service, marketing, and operations agents that can manage tasks, follow playbooks, and escalate to humans when needed.
Connects to all your Salesforce data — Use CRM and Data Cloud as a trusted source of truth so agents respond with accurate, contextual information instead of generic answers.
Acts across channels and apps — Let agents work in console, Slack, web, and messaging channels, or call flows and APIs behind the scenes to complete jobs end-to-end.
Uses governed playbooks — Encode eligibility, approvals, and compliance checks so your agents execute work safely, the same way, every time.
Augments human teams — Free up reps and agents from repetitive work so they can focus on complex conversations, deal strategy, and relationship building.
Continuously learns and improves — Monitor agent conversations, outcomes, and guardrail triggers so you can refine prompts, workflows, and training data over time.

How Agentforce Fits Into Your Revenue Engine

Think of Agentforce as a new layer in your revenue architecture: AI agents that sit on top of Salesforce and Data Cloud, orchestrating the work your marketing, sales, and service teams already do — but faster, more consistently, and at scale.

Discover → Design → Build → Deploy → Govern → Optimize

  • Discover high-value use cases: Identify repetitive, rules-driven work in sales, service, and marketing — like lead follow-up, case triage, or campaign execution — where AI agents can safely own first drafts or entire tasks.
  • Design guardrails and roles: Define what each agent is allowed to see, decide, and do; when they must hand off to humans; and how to log every action for compliance and analytics.
  • Build with Salesforce tools: Use Agent Builder, flows, prompt templates, and Apex to connect agents to data, workflows, and external systems without recreating your tech stack.
  • Deploy in your existing channels: Embed agents in Salesforce apps, portals, and Slack, or expose them via APIs so they can interact with customers and employees where work already happens.
  • Govern and monitor behavior: Track conversations, actions, exceptions, and override rates; enforce role-based access and approvals to keep agents aligned to policy.
  • Optimize for revenue outcomes: Tie agent performance to pipeline, conversion, CSAT, NPS, and cost-to-serve so you can re-prioritize roadmaps toward the biggest impact.

Agentforce Readiness & Maturity Matrix

Capability From (Ad Hoc) To (Agentic & Operationalized) Owner Primary KPI
Data & Context Fragmented accounts, contacts, and activity data; minimal unification. Unified Salesforce + Data Cloud profiles with governed taxonomies and consent. RevOps / Data Data Completeness, Match Rate
Process Definition Tribal knowledge and disconnected playbooks. Documented sales, service, and marketing workflows mapped into flows. Sales & Service Ops Stage Velocity, Handle Time
Agent Design & Guardrails Experimenting with generic copilots or chatbots. Role-specific agents with clear scopes, prompts, and approval paths. Architecture / CoE Escalation Rate, Error Rate
Channel Coverage Single channel pilots (e.g., web bot only). Agents working across console, Slack, portals, and messaging. Digital / CX Self-Service %, Containment Rate
Measurement & Governance Anecdotal wins; limited instrumentation. Dashboards tying agents to revenue, cost-to-serve, and CX outcomes. Analytics / Finance Pipeline Lift, CSAT, Cost per Interaction
Change Management One-off enablement sessions. Ongoing training, feedback loops, and “human in the loop” practices. Enablement / HR Adoption, Agent Assist Usage, Time Saved

Example Scenario: From Manual Work to Agentic Salesforce

A B2B SaaS company used Agentforce to create a Sales Qualification Agent and a Support Triage Agent. Within weeks, the sales agent pre-qualified inbound leads, enriched records, and scheduled meetings; the support agent categorized cases, gathered missing details, and routed work to the right queues. Reps and agents focused on higher-value conversations while AI handled repetitive tasks — and leadership finally saw AI tied directly to pipeline, win rate, and CSAT.

If you are already investing in Salesforce as your system of record, Agentforce becomes the layer that turns your processes into measurable digital labor instead of isolated AI experiments.

To unlock value, you need more than a demo: you need a clear Agentforce roadmap, prioritized use cases, and a data-first integration plan — all anchored in revenue and customer outcomes, not just “AI projects.”

Frequently Asked Questions About Agentforce by Salesforce

What is Agentforce by Salesforce?
Agentforce is Salesforce’s platform for building autonomous AI agents on top of your CRM. These agents use your Salesforce data, flows, and integrations to understand context, decide what to do next, and take actions — like updating records, sending messages, or triggering workflows — under well-defined guardrails.
How is Agentforce different from a traditional chatbot?
A traditional chatbot usually answers questions in a single channel and can’t reliably act on your systems. Agentforce agents are goal-oriented and action-taking: they can read and write Salesforce data, call flows and APIs, work across channels, and collaborate with humans to complete multi-step jobs, not just provide responses.
What do I need in place before implementing Agentforce?
You’ll get the best results when you have: (1) reasonably clean Salesforce data, (2) documented sales, service, and marketing processes, (3) key workflows automated in flows or Apex, (4) clear policies on data access and approvals, and (5) a cross-functional team (RevOps, IT, Security, and business owners) ready to own AI governance.
What are common Agentforce use cases for revenue teams?
Popular starting points include automated lead follow-up and qualification, pipeline hygiene and enrichment, appointment scheduling, guided selling and proposal prep, NRR plays (renewals and expansions), and support triage or deflection that ties directly back to Salesforce cases and entitlements.
How does Agentforce handle security and governance?
Agentforce respects Salesforce’s existing security model: profiles, permission sets, sharing rules, and field-level security. You can further restrict what each agent can see and do, define approval steps, and keep a full audit trail of actions. A Center of Excellence can review prompts, flows, and outcomes on a recurring cadence.
Where does Pedowitz Group fit into an Agentforce initiative?
Pedowitz Group helps you pick the right first use cases, align Agentforce with your revenue operating model, prepare Salesforce data and integrations, and design agents that tie directly to KPIs like pipeline, conversion, and cost-to-serve — not just AI experimentation.

Turn Agentforce Into Revenue, Not Just a Prototype

Whether you are piloting your first Salesforce AI agents or scaling Agentforce across sales, service, and marketing, we’ll help you design real, governed digital labor tied to business outcomes.

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Revenue Marketing Transformation (RM6™) Revenue Marketing Index Customer Journey Map (The Loop™)

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