Here are the top 10 intelligent automation technologies set to gain prominence in 2022
Intelligent automation technologies support the design and creation of end-to-end processes that make flexible, resilient, modern business operating models possible. Intelligent automation (IA) combines robotic process automation (RPA) with advanced technologies such as artificial intelligence (AI), analytics, optical character recognition (OCR), intelligent character recognition (ICR), and process mining to create end-to-end business processes that think, learn and adapt on their own. Intelligent automation is sometimes referred to as intelligent process automation (IPA) and hyper-automation. This article features the top 10 intelligent automation technologies set to gain prominence in 2022.
Artificial Intelligence
Artificial intelligence utilizes sensors, digital data, or remote inputs, to combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data. Artificial Intelligence is surely one of the best intelligent automation technologies set to gain prominence in 2022.
Machine Learning
Next on the list of the top 10 intelligent automation technologies is Machine learning. It is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. Machine learning algorithms use historical data as input to predict new output values.
Structured Data
Structured data is data that is organized and formatted, normally in a database. It follows a predetermined structure or set of rules—meaning these records are the same from one to the next. The more structured data is, the easier it is to process. Examples of structured data include a list of names, addresses, phone numbers, purchase history, or social media followers.
Computer Vision
Computer vision is a field of intelligent automation that enables computers and systems to derive meaningful information from digital images, videos, and other visual inputs — and take actions or make recommendations based on that information.
Natural Language Processing
Natural language processing is one of the top 10 intelligence automation technologies that are set to rule in 2022 and beyond. NLP is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data.
Process Mining
Process mining is a part of intelligent automation and process management to support the analysis of operational processes based on event logs. The goal of process mining is to turn event data into insights and actions.
Virtual Assistants
A virtual assistant is an application program that understands natural language voice commands and completes tasks for a user while providing a variety of remote services to a business. Virtual assistant chatbots combine virtual assistant services with chatbot functionality. A virtual assistant is one of the best intelligent automation technologies you should keep an eye on in 2022.
Retail and Warehouse Robots
Warehouse robots are specialized automated robots used for completing essential warehouse tasks, such as picking, sorting, and transportation. Retail service robots bring the intelligence of big-data knowledge of consumers to provide useful and smart customer service in-store.
Robotic Process Automation (RPA)
Robotic process automation (RPA) is a software technology that makes it easy to build, deploy, and manage software robots that emulate human actions interacting with digital systems and software. Just like people, software robots can do things like understanding what’s on a screen, completing the right keystrokes, navigating systems, identifying and extracting data, and performing a wide range of defined actions.
Optical Character Recognition
Optical character recognition or optical character reader is the electronic or mechanical conversion of images of typed, handwritten, or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene photo, or from subtitle text superimposed on an image.
Source: analyticsinsight.net
