AI and Process Automation: 7 Ways to Use It in Your Business

Artificial intelligence has the potential to make work incredibly efficient—which means it’s the perfect complement to process automation technology. Process automation, and related approaches like business process management, already aim to improve productivity by automating what can and should be automated. When organizations add AI into the mix, employees can delegate even more responsibility to technology, giving them time back to innovate, focus on the customer experience, and work on high-value projects. 

Here are just a few of the ways you can use AI and process automation to supercharge productivity in your business. Even better? You can do everything on this list in the Appian AI Process Platform. 

Most organizations have a huge influx of correspondence to manage, from customer service emails to vendor communications to sales requests. AI can use machine learning to understand different types of emails and then determine how to classify them. This enables organizations to automate email communications on a large scale, improving customer satisfaction and taking the drudgery out of a repetitive task that just has to get done.

In addition to classifying emails, an AI model can also generate an initial email response. By feeding the original email into the model and prompting it with a response, using preset requirements for tone, length, language, and type, the model can learn what’s required and create a draft response for the user to edit. Imagine how much of just one customer service employee’s day is spent responding to emails—and how AI could reallocate their time from repetitive tasks to more challenging customer service problems. 

When an organization receives documents, whether via mail, email, or web upload, AI can assist with classification. The model learns by seeing different types of documents and how they’re typically categorized then applies that knowledge to new documents coming in. This means an employee can simply review exceptions and respond to the documentation, rather than downloading each document, reading it, and manually classifying it. 

Generative AI and process automation can work together to quickly convert PDF and other structured forms into digital interfaces. Rather than have a developer do the tedious work of coding an interface from scratch, a developer can upload a PDF then have an AI process platform build an interface and generate instructions for the form based on the PDF’s contents. (Then, when using Appian, they can quickly make tweaks to the AI-generated interface using low-code.) This approach makes it radically faster to create user interfaces, speeding up development work so developers can move on to building other components.

Beyond just classifying documents, AI can extract the most relevant data from a document or a piece of text, categorize it, retrieve related information, and plug all of this into another system for usage or data analysis prep. When building an AI model, the developer simply has to define different fields that they want AI to extract, then automate the extraction process. This reduces manual data entry for employees and increases accuracy. 

AI can also summarize content for employees. AI can save end users time and improve decision-making by automatically generating summaries of incoming documents based on predefined, relevant settings. The model can pull out action items and key facts and achieve better understanding faster than ever. This ability can be widely applied to research, marketing work, etc. 

Pairing generative AI and technologies like vector databases enables organizations to create their own internal chatbots. For example, an organization could build a chatbot that allows users to query an internal knowledge base and retrieve intelligent results based on the semantic meaning of the question. This allows employees to instantly access valuable insights and resources, eliminating the need to hunt through FAQs or large knowledge sets for information. For example, let’s say an employee at an insurance company needs to support a customer; they could ask the chatbot, “What's the maximum out of pocket limit on a gold plan bought on the healthcare exchanges?” and retrieve an answer much faster than they could by searching manually. 

These examples are just the beginning—there are many, many more ways to use AI in tandem with process automation technology. So don’t sleep on the benefits of adding artificial intelligence into your process automation initiatives. This is a boom that’s not going away.

If you have multiple process automation technologies that don’t work well together, even if you’re using AI in each of them, you’ll run into substantial challenges. Using standalone systems for different automation tasks has led to difficult management for IT teams and stunted growth for business leaders. Avoid these challenges from the start by using a platform that unifies these technologies, so that you can use the best-fit technology, whether it’s AI, robotic process automation, intelligent document processing, business rules, or something else. 

While vendors can and will over-promise on AI, finding an automation platform that actually breaks down or significantly reduces the barriers to AI adoption and addresses real-world use cases will serve you well. These intelligent process automation tools deliver real results for streamlining your business processes. To find the best fit, look for a vendor that is both committed to AI investment and can show you tangibly how it can be used in the product. Most importantly, look for a vendor who is serious about protecting your data privacy with private AI.