What is intelligent process automation?
This article was written by Ma-Keba Frye, SEO Content Writer at MuleSoft.
Organizations are reaching new levels of productivity and efficiency as they automate their business processes. By 2026, the business process automation (BPA) market is expected to grow to $19.6 billion as organizations, small and large, deploy advanced tools to streamline end-to-end business processes, reduce errors, and more.
Automation has become a business imperative with the accelerated pace of innovation and the need for increased agility and resiliency. Intelligent process automation (IPA) offers several benefits to business operations, scalability, and digital experiences
What is intelligent process automation?
Traditional robotic process automation (RPA) automates repetitive, rule-based tasks and is driven by structured data. However, RPA bots cannot learn, improve, or incorporate unstructured data like emails and documents. This requires more advanced technology — that's where intelligent process automation (IPA) comes in.
IPA, sometimes called intelligent automation (IA), is the convergence of several components such as RPA, artificial intelligence (AI), natural language processing (NLP), and more. Together these technologies accelerate innovation and automate more extensive decision-based processes that typically require human intervention. It incorporates cognitive technologies, analytics, learning, and reasoning to enable rapid end-to-end business process automation and enhance business values across the entire enterprise. Organizations can then make complex mission-critical decisions with minimal human intervention.
What technologies does intelligent process automation utilize?
In addition to RPA, IPA relies on intelligent technologies such as:
- Natural language processing (NLP) software is a tool that enables a computer to understand, interpret, and manipulate spoken and written language.
- Artificial intelligence (AI) is technology that simulates human intelligence, analyzes data faster than people, and learns from past decisions.
- Machine learning (ML) is AI software that uses algorithms to identify patterns in structured data to make predictions and forecast outcomes.
- Computer vision is a field of AI that includes optical character recognition (OCR) tools that convert scanned documents and images into text.
- Process mining is an analytical approach that diagnoses business processes, then uses data analysis to capture and improve them.
What are the benefits of intelligent process automation?
Due to intelligent process automation's cognitive capabilities and ability to mimic human actions, IPA tools can be instrumental in increasing operational and business efficiency. IPA can improve:
- Customer experience: IPA can improve internal processes that enable faster and more accurate customer data results, such as onboarding, underwriting, and customer service times.
- Workforce productivity: Automating labor-intensive tasks that previously required human intervention enables employees to reallocate their time to other tasks that yield greater ROI.
- Accuracy: Manual data entry is often prone to error. IPA improves data accuracy and ensures consistency across data sets.
- Time and cost savings: Streamlined processes and increased employee productivity enable organizations to complete tasks faster, which saves organizational time and money.
- Compliance: A consistent and automated approach helps organizations adhere to security requirements and regulatory compliance.
What are some intelligent process automation use cases?
Leveraging IPA across various industries gives organizations a competitive advantage while contributing to increased growth and efficiency. Some common use cases include:
- Financial services: IPA contributes to faster customer response times, adherence to compliance requirements related to loan applications and credit decisioning, fraud detection, and ensuring accurate and streamlined underwriting.
- Healthcare: IPA creates faster, more accurate, and more secure processes for transferring patient records and billing. This improves employee productivity and the patient experience.
- Insurance: IPA tools can supplement many insurance processes like document handling for underwriting, claims processing and handling, fraud detection, and customer-facing tasks
What's the difference between intelligent process automation and hyperautomation?
IPA and hyperautomation are often used as interchangeable terms; however, they are different concepts. Both utilize automation tools to streamline processes, but IPA relies on automation technologies such as RPA and AI to optimize and streamline business processes. Hyperautomation, on the other hand, is an approach that aims to automate as many processes as possible across the organization. Therefore, it encompasses AI, IPA, RPA, and other technologies like OCR and NLP.
Overall, it's not enough to digitize processes in this digital age — it's also critical to automate them for greater efficiency and resilience. IPA improves end-to-end business processes, enables business continuity, and supports data-driven decision-making. To learn more about implementing a successful automation strategy, download our CIO guide to enabling business automation.