After identifying your use case ideas for Agentforce, flesh out each of the use cases so your organization can assess and prioritize them. Remember, this stage of the planning process is about the project goals, not the technical solution.
Required Editions
| Available in: Lightning Experience |
| Available in: Enterprise, Performance, Unlimited, and Developer Editions. Required add-on licenses vary by agent type. |
Identify the Jobs To Be Done
First, describe the work the AI agent will do. Many organizations use the Jobs to Be Done framework to outline the role of the agent and the tasks it will perform. Be sure to think deeply about the work and its expected outcomes. It’s an essential step in understanding how the agent can impact your organization, customers, and employees.
Determine the Scope
After identifying the work you want the AI agent to do, the next step is figuring out the right amount of work. What’s the appropriate scope? Your minimum viable product (MVP) should be the smallest unit of work that it makes sense to deliver. An iterative approach allows you to validate your assumptions, demonstrate value, manage the level of risk, and develop a plan for scaling the AI solution. The scope can be gradually expanded as your organization's AI maturity grows.
Define the Business Value
When you fully understand the scope of the work the AI agent will perform, you can establish the business value of the use case. Be sure to set specific, measurable goals and focus on outcomes. For more information about defining the business value of AI use cases, see AI Strategy.
Evaluate Data Readiness
Next, evaluate your data readiness for the use case. For AI agents to perform optimally, they must be powered by trustworthy, high-quality data that’s relevant to the business context. To learn more about data readiness, see AI + Data: Project Planning.
Assess and Prioritize the Use Cases
After defining your Agentforce use cases, your organization can assess the feasibility and impact of the projects and then incorporate them into their prioritized AI roadmap. See AI Strategy for more information about the factors to consider when refining your AI backlog and which prioritization frameworks you can use.