Automation 101: RPA and Intelligent Automation Explained

In today’s dynamic and highly competitive business landscape, companies constantly seek ways to streamline operations, reduce costs, and increase efficiency. One way to achieve these goals is through automation. Simply put, automation involves using technology to perform repetitive and time-consuming tasks that humans would otherwise do.

By automating these tasks, businesses can free up their employees to focus on more strategic and high-value activities while also reducing the risk of errors and improving overall productivity. In this blog post, we will explore two popular types of automation – Robotic Process Automation (RPA) and Intelligent Automation – and explain how they work, their benefits, and how to choose the right solution for your business.

Robotic Process Automation (RPA) is a type of automation technology that uses software robots or “bots” to perform repetitive and rule-based tasks that are typically time-consuming and prone to errors. RPA is designed to mimic human actions, such as logging into applications, copying and pasting data, filling out forms, and more. It can be used to automate a wide range of processes across various industries, including finance, healthcare, manufacturing, and more.

Key Features of RPA: Speed, Accuracy, and Scalability

Robotic Process Automation offers several key features that make it an attractive solution for businesses looking to automate their processes. Three key features of RPA technology, but not limited to, are given below:

RPA Use Cases: Industry Examples and Success Stories

Many industries have adopted RPA to automate various processes, from mundane administrative tasks to complex financial processes. For example, in the banking and finance industry, RPA is used to automate processes such as account opening, credit card processing, and mortgage underwriting. In healthcare, RPA automates claims processing, patient data management, and appointment scheduling tasks. Other industries that have adopted RPA include manufacturing, retail, and telecommunications.

One real-world example of successful RPA implementation is Audi Japan KK, a leading automotive manufacturer. Audi Japan has successfully implemented Robotic Process Automation (RPA) to automate its finance approval process. This has reduced processing time by 75%, translating to significant time savings of 60 hours per week, benefiting 20 departments. The successful implementation of RPA has enabled Audi Japan to enhance its operational efficiency, lower costs, and focus on more strategic initiatives.

Another example is AgFirst Farm Credit Bank in the United States, which recognized the need to improve its loan approval, special asset management, and onboarding processes to keep up with the ever-changing regulations of the finance industry. To address this, AgFirst implemented RPA to develop agile and efficient business processes. The bank successfully delivered a responsive and mobile RPA platform, resulting in improved compliance consistency and a 60% faster case closing rate than expected. Additionally, the bank achieved a 100% on-time completion rate for information requests and analyzed 97% of loans within expected timescales. This project’s success has enabled AgFirst to remain competitive in the industry while complying with stringent regulations.

For more detailed information about RPA, we kindly invite you to read our blog post: “What is Robotic Process Automation?“.

Although RPA has significantly contributed to automating repetitive and rule-based tasks, it should be noted that it is only one aspect of the larger picture of intelligent automation. Intelligent automation combines RPA with other technologies, such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), to automate more complex tasks and processes. Intelligent automation is designed to go beyond the repetitive, rule-based tasks that RPA is best suited for and can handle unstructured data and processes.

Intelligent automation has a wide range of applications across various industries, from customer service and marketing to supply chain management and financial analysis. By leveraging the power of AI and ML, businesses can automate tasks that were previously thought to require human intervention, such as fraud detection and sentiment analysis. Intelligent automation can also help companies to make better decisions by providing insights into data that would have been too time-consuming or difficult to analyze manually.

AI and Machine Learning in Intelligent Automation

Intelligent automation leverages a combination of RPA, AI, machine learning, and natural language processing to create systems that can operate independently and make decisions alone. By using machine learning algorithms, intelligent automation can identify patterns in data that can be used to optimize business processes and improve decision-making. AI and machine learning also allow intelligent automation systems to learn from previous actions and improve their performance over time.

In addition, AI-powered chatbots and virtual assistants are increasingly being used in customer service to provide quick and personalized responses to customer queries. These bots can understand natural language inputs and provide human-like responses by combining NLP and machine learning algorithms.

Benefits of Intelligent Automation: Advanced Capabilities and Strategic Value

Intelligent Automation goes beyond the capabilities of RPA, providing advanced capabilities and strategic value to businesses.

You can learn more about Intelligent Automation in our blog post “Intelligent Robotic Process Automation and Its Uses in the Industry“.

While RPA and intelligent automation share similarities in automating processes, the two have key differences. RPA mainly focuses on automating repetitive and rule-based tasks, while intelligent automation includes machine learning and AI capabilities to enable more complex decision-making. Intelligent automation can also automate end-to-end processes, while RPA is typically limited to a single task. Additionally, RPA is often used for short-term cost savings, while intelligent automation can drive long-term value and innovation for businesses.

Automation technology is rapidly evolving and will continue to transform the way businesses operate in the future. The future of automation will likely involve increased end-to-end automation of complex business processes as well as increased collaboration between humans and machines.

As a result, businesses that embrace automation technologies will be better equipped to compete in a fast-paced, digital-focused world.

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VoodooRPA. “Intelligent Robotic Process Automation and Its Uses in the Industry.” VoodooRPA, https://www.voodoorpa.com/intelligent-robotic-process-automation-and-its-uses-in-the-industry/.

IBM. “Intelligent Automation.” IBM, https://www.ibm.com/topics/intelligent-automation.

The ECM Consultant. “What is Intelligent Automation?” The ECM Consultant, https://theecmconsultant.com/what-is-intelligent-automation/.

Bizagi. “Audi Japan: Redefining Customer Experience with Digital Transformation.” Bizagi, https://bizagi.com/customers/case-studies/manufacturing-retail-audi-japan.

Bizagi. “AgFirst: Maximizing the Efficiency of Loan Servicing with Bizagi.” Bizagi, https://bizagi.com/en/customers/case-studies/financial-services-agfirst.