Artificial intelligence has the potential to make work incredibly efficient, meaning it is the perfect complement to process automation custom business software development . Process automation, and related approaches such as business process management, already aim to improve productivity by automating what can and should be automated. When organizations add AI to 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.

These are just a few of the ways you can use AI and process automation to increase your company's productivity. And what is better?

1. Email classification

Most organizations have a large influx of correspondence to manage, from customer service emails to supplier communications to sales requests. This allows organizations to automate email communications at scale, improving customer satisfaction and removing the drudgery of a repetitive task that simply has to be done.

2. Generating email responses

In addition to classifying emails, an AI model can also generate an initial response. By feeding the original email into the model and asking for a response, using preset tone, length, language, and type requirements, the model can learn what is needed and create a draft response for the user to edit. Imagine how much time a customer service employee spends answering emails and how AI could reallocate their time from repetitive tasks to more complex customer service issues.

3. Download attachments and classify them

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

4. Generation of interfaces from PDF

Instead of a developer doing the tedious work of coding an interface from scratch, a developer can upload a PDF and then have an AI process platform build an interface and generate instructions for the form based on the content of the form. PDF. (Then, using Appian, you can quickly make adjustments to the AI-generated interface using low-code.) This approach radically streamlines the creation of user interfaces, accelerating development work so developers can move on to building other components.

5. Extract key elements from documents

Beyond mere document classification, AI can extract the most relevant data from a document or a fragment of text, categorize it, retrieve related information and connect all this to another system for use or for the preparation of data analysis. When creating an AI model, the developer simply defines the various fields that they want the AI to extract and then automate the extraction process. This reduces manual data entry by employees and increases accuracy.

6. Summarize contents

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 and relevant parameters. The model can extract action items and key facts and achieve better understanding faster than ever.

7. Creation of internal chatbots

The combination of generative AI and enterprise solutions development such as vector databases allows organizations to create their own internal chatbots. For example, a company can create a chatbot that allows users to query an internal knowledge base and get intelligent results based on the semantic meaning of the question. This allows employees to instantly access valuable knowledge and resources, eliminating the need to search for information in FAQs or large knowledge sets. For example, suppose an employee of an insurance company needs to provide support to a client; She could ask the chatbot: “What is the maximum out-of-pocket limit on a gold plan purchased on healthcare exchanges?” and get an answer much faster than searching manually.

These examples are just the beginning – there are many, many more ways to use AI alongside process automation custom development services. So don't miss out on the benefits of adding artificial intelligence to your process automation initiatives. It is a boom that is not going to disappear.

Two tips to make AI and process automation operational

Here are two tips to help you get started with AI operationalization.

1. Take a platform approach

If you have multiple process automation technologies that don't work well together, even if you use AI in each of them, you'll run into significant challenges. Using separate systems for different automation tasks has made it difficult to manage IT teams and slowed the growth of business leaders. Avoid these challenges from the start by using a platform that unifies these technologies, so you can use the most appropriate technology, whether it is AI, robotic process automation (RPA), intelligent document processing, business rules or anything else.

2. Look for platforms that integrate AI into the process

While vendors can and will over-promise about AI, finding an automation platform that truly breaks 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 to streamline your software product development services processes. To find the best option, look for a vendor that is committed to investing in AI and can tangibly show you how it can be used in the product. Most importantly, look for a provider that is serious about protecting your data privacy with Private AI

Combining AI and process automation: 7 ways to use it in your company