10 Reducing complexity with generative AI
This chapter covers
- Designing and improving process flows with generative AI
- Replacing disambiguation dialogue flows with LLM judgments
- Testing static dialogue flows with generative AI as the “user”
It’s difficult to design a process-oriented bot that meets all the needs and desires of all stakeholders. Competing priorities may lead to a “design by committee” that introduces complexity. And well-meaning people can design edge cases that hamper the main dialogue flow. These complexities burden your users and make them more likely to quit or fail when using the bot. Generative AI can help you detect and improve these scenarios, helping you remove complexity and increase the successfulness of your bot.
Process flow builders often ask for too much information from the user. (More information is better, right? Not if it causes the chatbot to fail!) There are several ways to improve process flows with generative AI:
- Use generative AI to make suggestions about how to build a process flow.
- If your process flow is built, use generative AI to suggest improvements. It can also test the flow by acting as the user.
- Replace some static process flows with a large language mode (LLM)–driven process.
We’ll start by exploring a claim status process flow for a medical insurance provider. Then we’ll see how generative AI can help us design and improve this process flow and others.