Leveraging ChatGPT in Automation Development and Design

In a matter of weeks, generative artificial intelligence (AI) has moved from the bleeding edge of technology to the mainstream.

Right now, you, me, and just about anyone can use AI to create amazing artwork, narrate a book, write a blog, even create a new programming language from scratch. Imagine going back just a couple of years ago and telling your colleagues you’d be able to do all of that today from your smartphone!

The launch of OpenAI’s ChatGPT—a Large Language Model (LLM) is able to generate human-like text, has been a catalyst. It has revealed to millions of people around the world the recent advances in AI and focused minds on what’s possible with these models. It’s a big step forward in the democratization of AI, providing powerful foundational models that can be used to create even more valuable tools.

Note: ChatGPT is the most accessible generative AI tool available today, but similar results could be obtained from other emerging tools as well

On some of the ways expert robotic process automation (RPA) developers find ChatGPT to be useful.

  1. Use ChatGPT to understand other developers’ code
  2. Quickly create documentation for your code
  3. Create code from natural language requests
  4. Generate test data
  5. Generate test code for a code sequence

Business applications for ChatGPT when combined with a UiPath automation

  1. Analyze customer feedback
  2. Create a customer response email
  3. Prescreening resumes
  4. Create job interview questions
  5. Evaluate customer service conversation

What's next?

Generative AI, like the kind found in ChatGPT, is going to be a valuable tool for developers of all levels. Its main use today will be when you need to generate something new (and non-critical!) based on certain specifications – or ‘prompts’ as they’re called in the new lingo. When you pair these results with action enabled by automation, you can tackle a broad set of interesting new use cases. What many organizations still need to work out is how to operationalize these generative AI tools in a business environment with consistency and governance.