Intelligent automation tools and software use of technology such as artificial intelligence (AI) and robotic process automation (RPA) to automate mundane, repetitive tasks. The goal of intelligent automation tools is to streamline processes, reduce costs, and improves the efficiency of business operations.
The term "intelligent automation" was first coined by Forrester Research to describe tools that support enterprise automation in business process management. IA is sometimes also called hyperautomation.
Examples of intelligent automation technology
While the interpretations of intelligent automation differ greatly between experts and organizations, you can consider IA to include different business operations that are enabled by artificial intelligence or machine learning. The five key categories of IA tools include advanced process intelligence, robotic process automation, intelligent document processing (IDP), conversational AI and intelligent integrations.
Advanced process intelligence
One of the earliest forms of intelligent automation is process mining software that was developed in the late 1990s to automate process analysis and process discovery in business operations. Process mining is a technique used to discover, analyze and improve business processes using data mining methods.
Today, many process mining algorithms utilize Machine Learning (ML) to categorize and visualize business processes based on data extracted from event logs in enterprise resource systems, such as ERP or CRM databases.
A second key category of process intelligence software is task mining software. In task mining, advanced task capture algorithms capture business insights from the user interface of business applications using object character recognition (OCR) and other AI-enabled technologies such as Work API.
Robotic process automation (RPA)
The second key category of intelligent automation tools is robotic process automation. RPA is a form of business process automation where software robots are used to emulate humans actions interacting with digital systems and software. The roots of RPA can be traced to the early 2000s when the first commercial process automation software vendors emerged. The term RPA was first coined by Phil Fersht from HFS Research.
The goal of RPA is to use software bots to replace some of the manual and repetitive tasks previously done by humans in a digitalized workforce. Examples can include automated invoice approval in accounts payable or tasks within loan credit checks in consumer banking.
Intelligent document processing (IDP)
Intelligent document processing (IDP) is a technology that uses AI to automate the process of extracting, validating, and transforming relevant information from documents such as invoices, receipts, contracts, and forms. Typically IDP tools utilize natural language processing (NLP) to read and extract key information from digitalized documents.
IDP systems can be used to quickly and accurately extract unstructured data from documents and store it in an organized manner without the need for manual data entry. IDP can also include forms of digitalization, where object character recognition (OCR) and computer vision is used to scan and create digital copies of key business objects, such as invoices or contracts.
Conversational AI is technology that enables machines to interact with humans in a natural and conversational way. It uses natural language processing (NLP), natural language understanding (NLU), and automated speech recognition (ASR) to process and understand human speech or written text. It then provides answers based on machine learning trained on a specific use case, or in cases like ChatGPT based on data collected from the internet.
Conversational AI an be used to automate customer service, create virtual assistants, and engage in chatbot conversations. The overall goal is to provide an automated way for users to get service previously supplied by manual work or human support agents.
The fifth key category of IA solutions is intelligent integration tools, such as Integration Platforms as a Service (iPaas.) IPaaS is a cloud-based platform for integrating data, applications, and processes across multiple systems. It provides a secure, pre-built environment for building, testing, and deploying integrations.
An iPaaS platform typically consists of a set of tools and services that allow users to connect different enterprise applications and data sources to each other. iPaaS platforms usually provide a graphical user interface to create and maintain integrations, as well as application programming interfaces (APIs) and pre-built connectors for quickly connecting to existing business applications or enterprise systems. The platform also typically has built-in security protocols, data transformation services, and analytics tools to monitor and analyze the performance of the integration.
Benefits of intelligent automation tools
Each organization or business will find unique benefits to automating their business processes. Some of the most common goals of intelligent automation tools include:
When many business operations face the task of doing more with less intelligent automation helps to automate mundane, repetitive tasks, freeing up enterprise employees to focus on more important and strategic tasks.
While skilled employees can be very knowledgeable about their work, repetitive tasks expose businesses to human error. Intelligent automation can help reduce errors by eliminating manual processes and inputting information accurately.
In many organizations the cost of inefficient work quickly stacks up. Automating manual processes can help reduce the costs associated with labor and other overheads.
For many businesses, speed is a competitive factor in improving business operations. Automated processes can help speed up and streamline operations, resulting in faster processing of tasks and data.
Improve decision making
One of the lesser known advantages of IA is the ability to cruch vast amounts of data to provide more data-driven decision making. Automated processes can help provide insights and analytics to help inform better business decisions.