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How to select the right use cases for enterprise AI agents

Selecting the right use cases for enterprise AI agents is crucial for successful implementation and achieving desired business outcomes. Unlike traditional RPA bots, AI agents can reason, make decisions, collaborate, and take actions to pursue goals, enabling them to automate a wide range of business processes. Choosing the right use cases maximizes the impact of AI agents and secures organizational buy-in.

Here are a few ideas on where to start identifying potential use cases for AI agents within your business:

Evaluate your existing RPA pipeline to identify processes which may be more suitable for AI agents than RPA bots.
Review your existing RPA processes, in particular the upstream and downstream activities, to identify opportunities to increase the automation scope with AI agents.
Business processes that are well-documented and have available Standard Operating Procedures (SOPs) are ideal use cases to train the AI agents on.
Adopt an inside-out approach: focus on internal back-office processes first before looking at the client-facing, front-office tasks. This will enable you to achieve a good balance between risks and rewards.
Start with the proven, popular use cases such as Invoice Processing Agent, Employee Onboarding/Offboarding Agent, Customer Success Agent, Digital Marketing Agent, etc