After this lesson you will be able to
- Anchor every Agentforce conversation in one measurable business problem instead of a demo.
- Assess readiness across data, process, permissions and ownership before proposing a pilot.
- Design a pilot with a baseline, a success metric and a decision date.
- Explain Agentforce pricing models accurately, including Flex Credits, per-user add-ons and editions.
Start from a problem, not from the agent
The weakest Agentforce pitch begins with what agents can do. The customer nods, watches a demo, and files it under "interesting." The strongest pitch begins with a task the customer already wants to get rid of.
Look for work that is high volume, repetitive, rule-based and already partly documented. For example, a regional insurance agency might field hundreds of policy status questions each week that an agent could answer from records already in Service Cloud. A wholesale distributor's inside sales team might spend hours qualifying inbound leads that follow the same pattern. These are concrete, countable and owned by someone.
Ask the customer to name the task, the volume, the people doing it today and what they would do with the time back. If they cannot name a task, the conversation is not ready for Agentforce yet, and pushing will cost you credibility. Our Agentforce opportunity finder at /salesforce-account-executives/agentforce-opportunity-finder/ helps you spot candidate use cases from what the customer already owns.
Check readiness before you propose anything
An agent is only as good as the data, process and permissions behind it. A customer with poor case categorization, missing knowledge articles or inconsistent record ownership will get poor results, and that will be remembered as an Agentforce failure.
Run a short readiness check with the customer before you scope a pilot. Be honest about gaps. A readiness gap is not a lost deal. It is often a services opportunity and a reason to build trust. Our readiness checklist at /resources/agentforce-readiness-checklist/ gives the customer a structured way to assess themselves.
- Data: are the records the agent needs complete, current and in Salesforce or Data 360?
- Knowledge: is there documented content the agent can draw on, and who maintains it?
- Process: is the task defined well enough that a new employee could follow written steps?
- Permissions: what should the agent be allowed to see and do, and who approves that?
- Ownership: who owns the agent's performance after launch?
- Escalation: what happens when the agent cannot help, and who receives the handoff?
Design a pilot that produces a decision
A pilot without a success metric becomes an extended free trial. Design it to end in a yes or no.
Keep the scope narrow: one use case, one team or channel, and a small number of subagents. Salesforce began renaming agent topics to subagents in April 2026, so use that term with customers who follow the product closely. Agree on a baseline before launch, measured from current data: volume, handle time, resolution rate, response time or whatever the business problem is about.
Set a review date and decide in advance what result justifies expansion. Measure both outcome and quality. Resolution rate means little if customers are escalating in frustration. Review real conversations with the business owner during the pilot, not only dashboards.
Delivery matters here. Agent design, subagent instructions, testing and guardrails take experience. Bringing a delivery partner in at the pilot design stage keeps the scope honest; Abstrakt can help through the deal desk at /salesforce-account-executives/deal-desk/.
Explain the pricing models accurately
Agentforce pricing has several parts, and customers get confused when AEs blur them. As published on salesforce.com/agentforce/pricing on October 27, 2026, at list price in US dollars, the main options are below. The page notes it is for information only and subject to change, so check it again before you quote, and use your own price book for actual deals.
Two details customers often miss: unused Flex Credits do not roll over into later terms, and Flex Credits and Conversations cannot be used in the same org. Salesforce also notes that its example cost estimates exclude Data 360 credits and other consumption services, so remind customers that data costs may be separate.
- Flex Credits: $500 per 100,000 credits. A standard Agentforce action uses 20 credits; an Agentforce Voice action uses 30. Credits can be used across actions, prompts, translations and voice actions.
- Conversations: $2 per conversation, an alternative consumption model.
- Agentforce add-ons for Sales, Service, and Field Service and Operations: $125 per user per month, with unmetered employee usage. Industries add-ons are $150 per user per month.
- Agentforce User License: $5 per user per month, which requires Flex Credits.
- Max Edition: from $550 per user per month, including the Agentforce add-on and 2.75 million Flex Credits per org per year.
- Salesforce Foundations: listed at $0, including Agentforce Builder, Prompt Builder and Agent Script among other tools.
- Buying models: Pre-Purchase, Pre-Commit (listed as widely available later this year) and PayGo. Usage beyond entitlement is billed at the contracted rate monthly in arrears, with no overage penalty.
Model consumption from the customer's volumes
Consumption pricing makes customers nervous because the bill depends on usage they have not seen yet. Reduce that by modeling it from their own numbers during the pilot design.
Take the expected monthly volume of the task and estimate how many agent actions each one needs. For example, if a customer expects 5,000 conversations a month and each averages two standard actions, that is 10,000 actions, or 200,000 Flex Credits at 20 credits per action, which is $1,000 a month at the published list price. Your assumptions about actions per conversation will be wrong at first. Say so, and use the pilot to replace them with real data.
Compare that cost to the current cost of the task, not to zero. Then fold it into the business case using the method in the business case lesson and the Agentforce-specific inputs at /resources/agentforce-roi-business-case/.
Know when to slow down
Credibility with AI comes from saying no sometimes. If the customer has no defined task, no clean data, no owner, or expects the agent to replace a process nobody understands, recommend fixing those first. You can still sell the groundwork: data cleanup, Data 360, knowledge management or a Service Cloud or Sales Cloud improvement that makes an agent viable later.
Customers remember the AE who told them they were not ready yet and showed them how to get ready. That AE is usually the one they call when they are.
Talk tracks
When the customer asks "what can Agentforce do for us?"
“Quite a lot, but I'd rather start with you. What's one task your team does hundreds of times a month that you'd happily never do by hand again?”
It moves from capability to a specific, countable problem.
When the customer is excited but has no use case
“I love the interest. Before we talk about agents, let's find one problem with a clear owner and a number attached. Otherwise we'll build something impressive that nobody measures.”
It channels enthusiasm into a pilot that can succeed.
When readiness gaps show up
“Honestly, the agent will only be as good as the records behind it. I'd suggest we fix this piece first, or scope it into the pilot, so the results reflect what the agent can actually do.”
Naming the gap protects the customer and your credibility.
When proposing a pilot
“Let's pick one use case, measure where you are today, and agree now on what result would justify going further. Then we review it together on a set date.”
It turns the pilot into a decision rather than an open-ended trial.
When the customer worries about unpredictable consumption costs
“That's a fair worry. Let's model it from your actual volumes, and use the pilot to replace our guesses with real numbers before you commit to anything larger.”
It treats cost uncertainty as something to measure, not dismiss.
When the customer asks which pricing model is right
“It depends on who uses the agent. If your employees use it all day, a per-user add-on may be simpler. If it serves customers at variable volume, consumption usually fits better. Let's look at your numbers.”
It ties the pricing model to the use case instead of defaulting to one.
Agentforce opportunity qualifier
Use it on a live deal. Tick items off as you go; nothing you tick leaves this page.
Common mistakes
Leading with the demo
A demo without a problem gets polite interest and no budget. Find the task first, then show how an agent handles it.
Skipping readiness
Launching on weak data or undefined process produces poor results that get blamed on the product.
Running a pilot with no baseline
Without a before measurement, nobody can say whether the pilot worked, and expansion stalls.
Quoting pricing from memory
Agentforce packaging has changed often. Check the current pricing page and your price book before you put numbers in front of a customer.
Ignoring consumption and data costs
A case that shows only license cost will surprise the customer when usage and data costs arrive. Model them up front.
How you will know it is working
- Customers bring you specific tasks instead of asking what AI can do.
- Pilots end with a clear expand or stop decision on the agreed date.
- Consumption estimates are close to actual pilot usage after one revision.
- Readiness gaps turn into scoped work rather than stalled conversations.
Questions
Is Agentforce included in any edition?
As published on salesforce.com/agentforce/pricing on October 27, 2026, Max Edition includes the Agentforce add-on and 2.75 million Flex Credits per org per year. Salesforce Foundations is listed at $0 with builder tools included. Confirm current packaging and your customer's contract before you rely on either.
Should I recommend Flex Credits or Conversations?
It depends on how the agent will be used and what the customer finds easier to forecast. Note that the pricing page says the two cannot be used in the same org, so the choice matters. Model both from the customer's volumes if they are unsure.
How long should an Agentforce pilot run?
Long enough to collect meaningful volume against the baseline, and short enough that the decision does not drift. Set the length from the task's volume, and fix the review date before launch.
What if the customer is not ready?
Say so, and sell the groundwork. Data cleanup, knowledge management, Data 360 or a core Sales Cloud or Service Cloud improvement can make an agent viable later, and the customer will trust your recommendation when they are ready.