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How Intelligent Business Automation Combines AI and Automation

Elizabeth Bell, Appian
March 18, 2024

Enterprises looking to increase productivity and optimize business processes are increasingly turning to artificial intelligence (AI). AI can meet these expectations—but only with the right enabling technology. Intelligent automation at scale across the organization can offer a strategic approach to incorporating AI into complex business processes. 

Intelligent automation defined.

Intelligent automation refers to the usage of advanced technologies like AI and machine learning (ML) to automate complex business processes beyond what conventional automation tools like robotic process automation (RPA) or intelligent document processing (IDP) can achieve on their own. 

AI brings the “intelligence” to intelligent automation, enabling traditional automation methods to interpret complex data, make decisions, and learn from outcomes.

Which emerging automation trends deserve your attention now? Get the Gartner® Hyperautomation Trends Report.

How does intelligent automation technology work?

Intelligent automation technology enhances traditional process automation techniques to create more streamlined business processes. AI harnesses data to enable systems to learn, adapt, and make decisions, so that automation can do even more to save employees time. 

For example, see how these two tasks related to IDP and RPA below change when AI is added into the mix:

  • Document classification. IDP was revolutionary when it was introduced, saving employees hours on manual content processing. But AI has enhanced this technology even more. For example, Appian’s AI Skills allows customers to securely train private AI models with their own data. These models can tackle things like email and document classification and document extraction. 
  • Workflow generation. Some robotic process automation providers already enable developers to use a recorder to track their tasks so RPA can follow along and create its own workflow design, but AI will likely make it even more seamless. In the future, expect to see RPA bots enhanced with the ability to auto-generate workflows. In fact, RPA trends indicate AI is already influencing both software robot development and the way bots carry out task automation to equip them to handle more complex tasks, rather than just repetitive, simple tasks.

3 ways enterprises can use intelligent automation technology.

What becomes possible when you pair AI and automation via intelligent automation? We suggest three ideas below, but as intelligent process automation platforms adopt more and more AI, this list will grow.

1. Create AI models specific to you.

Creating an AI model is simple in a process automation platform like Appian. It’s designed for ease-of-use, eliminating the need for a large team of data scientists or substantial investment in new infrastructure. 

Imagine you want to create a model for classifying and extracting data from documents. Upload your sample documents, and the platform handles the model training. You can then review and adjust the outcomes as necessary. This straightforward approach allows you to create an AI model that’s customized on your own data, which not only enhances accuracy but also reduces hours spent working on manual processes.

2. Automate process design.

Low-code AI tools that combine AI and automation make it easier and quicker for developers to create digital solutions. These tools allow you to go from a basic document to a complete application interface with just a few clicks. This means less time spent on writing front-end code, tweaking data for databases, and designing interfaces with CSS. AI handles most of the heavy lifting, so developers can focus on making small, necessary adjustments in a straightforward, low-code environment. This approach speeds up development and simplifies the process, making the creation of digital solutions more efficient and less complex.

3. Embed AI into large business processes.

To get a real return on your AI investment, you need to be able to put AI into action in your core business processes. AI process platforms that take a low-code approach are purpose-built to operationalize intelligent automation in end-to-end processes. Finding intelligent automation technology that actually breaks down or significantly reduces the barriers of AI adoption and addresses real-world use cases can serve you well. 

How to integrate intelligent automation technology into your business.

The easiest way to incorporate intelligent automation into your business processes is to adopt a process automation platform that already enables this. Here are three reasons why:

  1. Easy access to data. An AI process automation platform with data fabric, API, and RPA capabilities acts as an enterprise architecture layer that can connect to anything in your tech stack. Data is the fuel of artificial intelligence. The more data AI gets, and the better that data is, the more effectively AI can help you. 
  2. Speed. You can design digital solutions to automate processes with all the AI capabilities available to you in the platform, rather than building AI products from scratch. Although not every process automation platform has comparable AI capabilities, plenty of new features will be developed in the next few years. See this strategic planning assumption from Gartner® in their Market Guide for Business Process Automation Tools: “By 2025, 60% of business process automation (BPA) vendors will offer generative AI—driven process modeling to reduce process development times.”
  3. Do more with less. Integrated IT platforms that can handle many business challenges eliminates siloed IT systems, enabling an end-to-end approach to intelligent automation across your business operations. The versatility of process automation platforms allows you to pivot without having to reinvest in niche technologies or custom AI development.

Get more information on what low-code process automation and AI together can do. 

8 experts weighed in on how enterprises need to be moving in AI. Download their insights in the 2024 AI Outlook