Automation is a technical concept that uses machines and control systems to perform repeatable and time-consuming processes previously done by human workers. Automation supports in industries since the dawn of the industrial revolution. In the era of digital transformation, Robotic Process Automation (RPA) takes automation a step further and automates a wide range of repetitive and rule-based business processes using software applications. Limited human intervention is required for these processes and software robots run tasks from start to finish. These processes are based on pre-defined business logic and structured inputs. Now, Intelligent Automation is becoming a buzzword in the IT industry. It takes automation to the next level by adding intelligence to the processes. Substantial improvement in computing power makes intelligent automation possible and, as a result, it helps reduce the complexities in business operations and expands the growth. In contrast to traditional automation techniques, Intelligent Automation does not require pre-defined instructions to automate the workflows. Furthermore, the Intelligence aspect of this technology supports automating the range of processes that require creativity and analytical skills that traditional automation isn't capable of.
Intelligent Automation (IA) is the combination of technological and business concepts including Robotic Process Automation (RPA), Business Process Management (BPM), and Artificial Intelligence (AI). It adds intelligent decision-making and analysis capabilities to the automation to accelerate the digital transformation of organizations. IA uses the latest cognitive technologies such as machine learning, deep learning, natural language processing, and computer vision to automate complex processes humans cannot do. For instance, IA can be used to analyze the probability of a mole being cancerous by assessing a photographic image or to manage the supply chain operations in the food industry based on the weather forecasts.
Components of Intelligent Automation
Artificial Intelligence (AI)
Artificial intelligence simulates human intelligence using computer systems. Machine Learning (ML) and Deep Learning (DL) are the widely known branches of AI. ML finds and analyzes patterns and structures in datasets to make decisions without human involvement. It allows systems to learn autonomously from real-world experience without being explicitly programmed. To recognize the patterns in big data, ML can use with the help of decision-making algorithms.
Business Process Management (BPM)
Business Process Management is a discipline that improves and standardizes the business processes of organizations. BPM uses various methods to design, model, execute, monitor, and optimize the processes. BPM is a methodology rather than a software product, and BPM suites (BPMS) are used to automate the operational and business processes.
Robotic Process Automation (RPA)
In RPA, software applications known as robots are configured to process transactions, manipulate data, trigger responses, and communicate with other systems based on pre-defined business logic and structured inputs. These robots are capable of executing other existing software applications to perform the organization’s business processes while making zero mistakes. RPA does not change the current system architecture, but runs alongside the existing applications and imitates what human workers would do.
In intelligent automation, AI technologies first observe and understand how business processes proceed, then it will analyze the workflow and determine the optimal ways to automate the processes. Intelligent automation is also capable of processing both semi-structured and unstructured data. The ability to handle large volumes of data allows IA to automate more complex processes would that require a massive human workforce. Therefore, IA technology can be used to drastically transform the key business operations of organizations such as HRM, finance, supply chain, IT, and customer care. As a result, organizations can reduce unnecessary overheads by deploying resources efficiently and accomplishing a higher job success rate. Although the IA approach lessens the human involvement in repetitive and complex business processes, human intervention is required to maintain the standards of the automation environment. Humans can contribute their knowledge to areas including decision making, training, error handling, monitoring of automation components, etc.
Difference between Robotic Process Automation and Intelligent Automation
Though RPA and IA are related, they do not denote the same technology. RPA remains an important component of IA, but RPA solutions could be implemented without IA capabilities. While RPA automates repetitive and time-consuming tasks, IA focuses on optimizing the processes by adding cognitive technologies to the system. RPA is programmed to process the structured inputs, however, cognitive technologies allow IA to automate the processes made up of unstructured data including audio, video, image files, chat conversations, log files, social media contents, etc. Therefore, IA can be considered a more robust and diversified automation approach compared to RPA.
Use cases of Intelligent Automation
Intelligent Automation could be beneficial to a large range of industries. These are some use cases of IA solutions that transform the end-to-end business processes of organizations.
Healthcare
The Healthcare industry largely benefited from IA solutions. In traditional practices, doctors are responsible for assessing and prescribing patients’ medical treatments. They mostly make decisions based on their experience and knowledge. Using IA solutions, patients’ illnesses can be diagnosed more reliably by analyzing their medical reports and symptoms, allowing AI-powered robots to suggest better treatments to the patients. AI capabilities can also help accurately read medical images such as CT, MR, and X-rays.
Inventory Management
Inventory Management is an important component in any business organization. Conventional inventory management faced several challenges include obsolete stocks, stock-outs, increasing storage cost, misplaced stocks, operational inefficiencies, etc. IA brings new benefits to organizations by transforming existing inventory management processes. Since IA applications could process large amounts of data within a small period, it will increase the speed of operations and reduce manual labour. Automated processes reduce the operational inefficiencies that lead to an improved customer experience.
Driverless Cars
One of the main purposes of autonomous vehicles is to reduce the risks associated with human drivers. A large amount of data needs to be processed instantly to achieve a higher level of intelligence than human drivers are capable of. Autonomous vehicles are equipped with cameras, sensors, and other communication devices, and these devices constantly provide important data based on their surrounding environment. IA technologies process the provided data and enable intelligent decision-making capabilities which ensure a higher level of safety on roads.
Telecommunication
With intelligent automation, telecommunication companies could transform their important business operations, including customer account management, call centres, network operations, etc. RPA solutions can be used to automate all customer subscriptions and account management processes. AI-powered bots could handle the call centre operations more efficiently and provide personalized service to customers. IA technologies could also be used to manage network performance and automate areas such as maintenance and updates. All these transformations aim to reduce operational costs and deliver a good customer experience.
Manufacturing
The manufacturing industry has reaped the benefits of automation from the beginning of the industrial revolution. Industry 4.0 changes the traditional manufacturing practices by using smart digital technologies such as Internet of Things (IoT), AI, smart sensors, cognitive computing, etc. Cognitive technologies need to be added to automated processes to completely replace human labour in manufacturing. IA introduces intelligence to the production lines and it will bring an efficient, safe, and reliable working environment to the factory floor. Flaws in machinery can be easily detected using AI-powered technologies like Machine vision, and repaired before they affect the entire production line operations.
