Companies have been using automation tools of all kinds—like robotic process automation (RPA)—in their organizations for years. RPA is a great tool on its own to save time by handling repetitive tasks like moving files, copying data, and even advanced logic-based use cases. But as your business grows and data volumes increase, you might need to boost your intelligence to deal with more complex scenarios.
Artificial intelligence (AI) is already being used in all kinds of creative ways to further simplify and streamline tasks. So much so that 92 percent of businesses plan to invest in AI, per Gartner. But before you combine the power of AI with RPA, it’s important to understand how they can work together, and the best practices to use to see optimal results.
Enhancing RPA with AI
RPA software bots act as digital assistants, taking over your most repetitive tasks. And AI, especially large language models (LLM), can add another skillset to your digital workforce. Trained on a vast amount of data, this intelligence enables AI tools to do things like generate text, solve real problems, and in some cases, even write code.
Imagine you’re setting up a new automation task, and you’re not sure the best way to do it—whether it’s the proper syntax, how to structure the logic, or even assembling the workflow itself. Instead of spending time digging through pages of documentation, or spending hours experimenting, tap into AI. An AI tool trained on LLMs can speed up the learning process with RPA tools by suggesting the next steps, providing quick answers, and even giving you the right code snippet when you hit a roadblock.
Want to see RPA and AI in action? Watch our on-demand webinar to see more use cases for using AI to assist RPA with building and troubleshooting tasks. WATCH NOW >
Best Practice: Choose the Right AI Tool
There are already a number of AI LLMs available, and different AI engines are better suited for certain tasks than others. When integrating AI into an RPA tool, it’s especially important to understand that all tools are not created equally. Do your research and try out different tools to find which fits your needs best.
There are general purpose AI models available, like ChatGPT-4, and others specialized for specific tasks or industries. And while there are free LMMs available, AI tools can vary significantly in cost depending on the model and provider. Their pricing models also vary from a one-time purchase to subscription-based plans.
Generally, paid AI services tend to provide better results, with more accurate and advanced outputs compared to free tools. And free tools usually lack features and functionality, performance, and can even limit the number of prompts you can make. No matter what your use case is, it’s crucial to weigh the cost against your needs and budget to ensure any AI solution you choose aligns with your larger business goals.
Best Practice: Use Clear, Descriptive Prompts
The biggest part of ensuring you get proper results from your AI tool is understanding how to properly write prompts. Most errors come from poorly written prompts. Clear, specific, and well-structured prompts are more likely to yield accurate and relevant outputs. As you craft your prompts, take a moment to think about how you’re framing your requests.
Try to break down your prompts to the basics and then build on those results as needed. And don’t be afraid to ask the engine if what you’re looking to do is even possible or if it’s capable of outputting the type of data you’re looking for. In some cases, you can even prompt your AI tool to do more research before providing the response.
Watch this clip from our recent webinar to see an example of a bad prompt vs. a good prompt:
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Best Practice: Keep Security and Privacy in Mind
One of the most important topics when it comes to AI is security and privacy. When you’re querying external AI services, always be mindful of the data you’re sharing with the engine. Avoid feeding any AI tool—free or paid—with sensitive information like passwords, private customer data, or proprietary code. If you’re unsure of what information you should and shouldn’t share, consult your company’s AI or privacy policies.
Always make sure the information you provide is safe to share, especially if you’re using AI to assist with generating scripts or solving specific problems. It’s all about balancing the convenience of AI with the responsibility of keeping your data secure.
Best Practice: Understand the Limits of AI and Test Your Results
While AI can be incredibly helpful, it is important to set realistic expectations as you get started—AI tools are powerful, but they’re not perfect. Sometimes they may not generate a working script on the first try or even subsequent tries, and the script they do create might need some tweaking to fit your exact needs. And when it comes to brand new features or very specific use cases with your RPA tool, the AI engine might not fully understand the ins and outs yet.
Always review and test your output to ensure it meets your specific needs, and most importantly, that your AI-assisted automation workflow works. Preferably, use a testing environment instead of your production environment, especially in more complex or niche scenarios, to avoid potential downtime or letting errors spin out of control.
AI tools can significantly speed up your work with RPA tools, but don’t forget that at the end of the day, you’re still responsible for building automation that works. Don’t forget to apply our own expertise to fine tune and, more importantly, verify what your AI tool is producing—never blindly trust the output.
Best Practice: Experiment On!
The best way to use AI and RPA together is to keep learning and experimenting. The more you use AI with an RPA tool, the more you’ll discover what works best for you. Don’t hesitate to try out different approaches or ask your AI tool for help in ways you hadn’t considered before. Embracing AI is a learning process, but the more you engage with it, the more you’ll get out of it.
Don’t forget that AI models and tools are constantly changing and evolving. New updates can bring more accuracy, updated features, and stronger integrations. Keeping an eye out for the latest developments will help you get the most out of the AI engine you choose to use with an automation tool.
As you start integrating AI into your RPA workflows and tasks, remember these best practices and takeaways to help you get the most out of the technology while avoiding potential pitfalls. By doing so, you’ll make your automation work smarter and more efficiently, all without compromising on quality or security. And always keep in mind that like automation, AI is a tool meant to complement your expertise—not replace it.
Source: https://www.fortra.com/blog/5-best-practices-using-ai-rpa
