As generative AI grows in popularity and enterprises scramble to embrace new technology in a scalable, compliant way, it can be difficult to know the right path forward. Your enterprise has already invested in automating processes to free up resources and improve organizational efficiency, but is it enough? This is where intelligent process automation comes into play.

This year at Appian World, we announced the launch of Process HQ. This next-generation process mining capability combines both process and business data in a single place, automating process analysis and empowering users with intelligent recommendations for where and how to take action. And because it’s part of the Appian Platform, you can immediately apply these improvements to your processes using our AI automation and workflow orchestration capabilities.

For organizations looking to automate processes for better performance, a combination of RPA and process mining can help. Let’s take a step back to understand why. Automation that’s implemented without data-backed decisions often yields poor results. And data without action leads nowhere. To get the most out of any technology investment, you have to be sure you're using the right combination of tools and techniques.

AI injects “intelligence” into automation, enabling systems to execute tasks, comprehend complex data, make informed decisions, and learn from outcomes. Unlike technologies such as robotic process automation (RPA), which follow predetermined rules, AI leverages data to evaluate situations and determine the best course of action. Now that we've explored how AI augments traditional automation tools, let's delve deeper into the realm of intelligent automation.

Intelligent automation removes barriers to scaling automation that have hindered business productivity for years. This powerful fusion of technologies automates complex processes, empowering organizations to adapt to change faster and more effectively than ever before.

Automation and artificial intelligence have been key players in financial services for years. Financial institutions have automated routine tasks across fraud detection and prevention, loan application processing, and customer service, to name just a few. But the pace and breadth of adoption will only increase. In the lending market, automated underwriting can be a game-changer.

Enterprises have complex IT and technology needs. To reach business goals, organizations must often stitch together a patchwork of software and IT systems. So, it’s understandable that the thought of adding yet another technology—low-code—might cause trepidation. But low-code excels at integrating seamlessly with any technology. Low-code tools speed up development work and enable rapid application development.

Learn how to implement end-to-end process automation strategies successfully. Discover which hyperautomation technologies drive immediate and future business impact in the Gartner® Emerging Tech Impact Radar: Hyperautomation Report. Discover which use cases you should focus on for business process automation. Download theGartner® Market Guide for Business Process Automation Tools.

Low-code is here to stay. In fact, Gartner anticipates the adoption of low-code development platforms will grow 20% per year to $44.5 billion by 2026. However, while low-code offers enterprise IT leaders undeniable advantages, its role in shaping the future of process automation is nuanced. This blog delves into the dichotomy of low-code's potential, exploring why it is the future but not the sole solution for process automation.

Intelligent automation is a term for the combination of process automation and artificial intelligence (AI). And it’s creating efficiency gains for enterprises across industries. In this article, discover intelligent automation examples that will illuminate common use cases that enterprises should consider adopting to improve efficiency and make space for innovation.