A software process that combines robotic process automation and artificial intelligence
Intelligent automation (IA), or alternately intelligent process automation, is a software term that refers to a combination of artificial intelligence (AI) and robotic process automation (RPA).[1] Companies use intelligent automation to cut costs and streamline tasks by using artificial-intelligence-powered robotic software to mitigate repetitive tasks.[1] As it accumulates data, the system learns in an effort to improve its efficiency.[2] Intelligent automation applications consist of but are not limited to, pattern analysis, data assembly, and classification.[2] The term is similar to hyperautomation, a concept identified by research group Gartner as being one of the top technology trends of 2020.[3]
Technology
Intelligent automation applies the assembly line concept of breaking tasks into repetitive steps to improve business processes.[4] Rather than having humans do each step, intelligent automation can replace steps with an intelligent software robot or bot, improving efficiency.[5]
Applications
The technology is used to process unstructured content. Common real-world applications include self-driving cars, self-checkouts at grocery stores, smart home assistants, and appliances.[6] Businesses can apply data and machine learning to build predictive analytics that react to consumer behavior changes, or to implement RPA to improve manufacturing floor operations.[6]
For example, the technology has also been used to automate the workflow behind distributing Covid-19 vaccines. Data provided by hospital systems’ electronic health records can be processed to identify and educate patients, and schedule vaccinations.[7]
Intelligent Automation can provide real-time insights on profitability and efficiency. However in an April 2022 survey by Alchemmy, despite three quarters of businesses acknowledging the importance of Artificial Intelligence to their future development, just a quarter of business leaders (25%) considered Intelligent Automation a “game changer” in understanding current performance. 42% of CTOs see “shortage of talent” as the main obstacle to implementing Intelligent Automation in their business, while 36% of CEOs see ‘upskilling and professional development of existing workforce’ as the most significant adoption barrier.[8][9]
IA is becoming increasingly accessible for firms of all sizes. With this in mind, it is expected to continue to grow rapidly in all industries.[10] This technology has the potential to change the workforce. As it advances, it will be able to perform increasingly complex and difficult tasks.[11] In addition, this may expose certain workforce issues as well as change how tasks are allocated.[12]
Benefits
Streamline Processes
Repetitive manual tasks can put a strain on the workforce, these tasks can be automated to allow the workforce to work on more important matters that require human cognition.[11] Intelligent automation can also be used to mitigate tasks with human error which in turn increases proficiency.[11] This allows the opportunity for firms to scale production without the traditional negative consequences such as reduced quality or increased risk.[12]
Customer Service Improvement
Customers service can be improved drastically, this allows for a competitive advantage for the firm.[12] IA utilizing chat features allows for instant curated responses to customers.[12] In addition, it can give updates to customers, make appointments, manage calls, and personalize campaigns.[10][11]
Flexibility
Due to the wide range of applications, IA is useful across a variety of fields, technologies, projects and industries.[10] In addition, IA can be integrated with current automated systems in place.[10] This allows for optimized systems unique to each firm to best fit their individual needs.[10]
Capabilities
Cognitive automation: Employs AI techniques to assist humans in decision-making and task completion
Process mining: Applies data mining methods to discover, analyze, and improve business processes
Intelligent document processing: Utilizes OCR and other advanced technologies to extract data from documents and convert it into structured, usable data
Computer vision: Allows computers to extract information from digital images, videos, and other visual inputs
Integration automation: Establishes a unified platform with automated workflows that integrate data, applications, and devices.
