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.
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.
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