The rapid boom of digital transformation has given rise to many technologies, and one of them is intelligent process automation (IPA).
It was born out of the dire need for businesses to tackle macroeconomic conditioning, which was hampering profits across different sectors.
Many businesses were looking for a powerful technology that can help them optimize and expedite their business processes.
That’s where IPA helps. Its automation capabilities have made it a vital part of many organizations’ operation models and tasks.
Apart from automating repetitive tasks, IPA can also help reduce processing time and increase return on investment.
In this article, I’ll talk about IPA and understand its importance for businesses.
What Is IPA?
Intelligent process automation (IPA) is a convergence of modern technologies that work together to produce automation capabilities to automate different digital processes.
As automation takes over many business processes, IPA has become an important aspect of the rapidly changing modern world. In essence, IPA is a set of technologies and applications that are implemented in business processes to enhance operational efficiency, business value, and query response.
By combining ML and AI with other technologies, businesses can utilize an IPA tool or software to create an intelligent business process that can think, learn, and adapt automatically to improve efficiency. It is continuously evolving with time so that automation can be elevated to a whole new level.
This amalgamation of technology is designed to help humans in automating routine and repetitive tasks and create an effective operating environment. In addition, it’s used to enhance customer experience, simplifying the interaction process and creating effective solutions in a shorter time.
Today, IPA has made its way into different industries in various forms, and one of the most popular forms is chatbots to enable customer interaction.
Benefits of Using IPA
Intelligent process automation (IPA), when used in modern businesses, can benefit them in a variety of ways. Some of them are:
Reduced Operational Time
IPA can automate many repetitive and labor-intensive tasks in your business, which helps in reducing processing time. According to McKinsey’s, the implementation of IPA has not only helped organizations to reduce process time by 50% but also over half of the manual tasks.
More Employee Engagement
Repetitive tasks in most organizations cause boredom in employees, and it ultimately leads to lesser engagement. Using IPA tools that can easily automate many tasks, employee engagement increases. The reason is instead of spending time on boring work, they can shift their focus to more essential, exciting tasks.
Lower Error Rates
You wouldn’t believe it, but there are approximately 1-5% of error rates in business data for most organizations unless they make some extraordinary effort.
Also, it is pretty hard to address them because employees have to enter a lot of data manually. Implementing IPA helps increase data accuracy and reduce the rate of faulty decision-making and missed opportunities.
Deeper Process Insights
IPA tools enable you to complete various processes with speed and efficiency by providing deeper insights into processes. You will get reports and valuable data to detect any bottlenecks and immediately work on them.
Improved Customer Experience
By implementing IPA tools in business operations, you can witness improved customer experience. It automates tasks so that customer queries of customers get resolved quickly and accurately. Since most customer dealings are automated, businesses can expect an increase in customer engagement and loyalty.
As IPA tools handle most routine and repetitive tasks, employees will get more time to focus on important tasks, making them more productive. This ultimately enhances the operational efficiency of a business and leads to better ROI.
Using AI and ML in IPA
Artificial intelligence and machine learning have a massive impact on IPA, helping it to expand its automation abilities beyond regular office tasks. Both AI and ML serve as important pillars of modern IPA platforms.
IPA platforms, when integrated into a process, utilize ML algorithms for analyzing real-time and historical data. IPA tools can optimize the process for better efficiency and result. These tools can leverage ML to automatically assign workflows based on the role and project demands.
Similarly, AI empowers IPA platforms to work on large sets of unstructured and structured data and evaluate them to find many essential pieces of information. IPA tools use this information in intent detection, finding anomalies in infrastructure, natural language processing, and other processes.
Moreover, using all these resources, IPA can help you create chatbots to interact with customers, learn their intent, and respond accordingly. Using the available set of models, AI also assists IPA tools in solving customers’ issues without needing human interference.
ML and AI have helped IPA to go beyond simple automation of existing tasks and combine modern technologies like deep learning to create new processes. This helps optimize processes, enhance business efficiency, and yields better ROI.
Technologies Involved in IPA
Intelligent process automation (IPA) utilizes numerous technologies to automate business processes. These are:
Artificial intelligence (AI): One of the most vital components of IPA is AI. It helps users create a knowledge base and optimize business processes. For IPA, AI serves as the central brain behind decision-making, enabling users to customize the processes and achieve the best possible results.
Robotic process automation (RPA): Along with AI, RPA also serves as an essential part of IPA that helps in recording and executing repetitive processes in business operations using software robots. It’s also known as software robotics that assists in performing rule-based tasks by leveraging the power of AI and ML.
Machine Learning (ML): IPA uses ML algorithms to analyze old and current datasets to predict new output values and make adjustments accordingly. Thus, machines can learn from old business processes and adapt to current industry standards to produce better results.
NLP: Natural language processing (NLP) is also a part of AI that IPA utilizes in order to understand languages, interpret them, and represent them in the form of text. With the interpreted information, NLP assists in interaction using chatbots, generating emails, and doing much more
Digital process automation (DPA): Digital process automation involves different potent tools that strengthen IPA by helping it automate or semi-automate tasks. It has played an important role in optimizing the workflow and improving data management. Ride booking and shopping apps are prime examples of DPA.
Business process management (BPM): BPM is another technology associated with IPA that helps automate business workflows to enhance consistency and agility. It has been instrumental in improving customer interaction and streamlining business processes for better efficiency.
Computer Vision: Computer Vision, as a component of IPA, allows users to analyze and interpret images to gain insight into data. IPA actively utilizes computers to not only gather data for improving the business process but also to understand anomalies in security settings.
IPA vs. RPA
While intelligent process automation and robotic process automation look similar, they are pretty different from one another in many aspects. Many people often confuse IPA and RPA, but the latter serves as a component of an IPA tool suite.
Let’s compare IPA and RPA.
Intelligent Process Automation (IPA)
Robotic Process Automation (RPA)
Intelligent process automation is a combination of various AI technologies, including RPA that helps in managing and automating complex business processes.
Robotic process automation is also a technology involving software robots to automate labor-intensive, repetitive, and routine-based tasks in businesses.
IPA is used chiefly for optimizing and creating new processes that enhance the ROI and efficiency of a business.
RPA, on the other hand, is mainly used for performing rule-based tasks.
IPA is capable of handling complex operations and decision-making operations.
RPA can only handle user-defined tasks and can’t make decisions by learning from data.
It involves many new innovative technologies like NLP, computer vision, BPM, data extraction, etc.
It has evolved from three leading technologies – AI, workflow automation, and screen scraping.
IPA involves a lot of programming skills and requires a lot of upfront investment.
RPA can be implemented with a bit of programming and investment.
It has the ability to handle different types of data formats.
It is limited by specific data formats.
Challenges of IPA
Like others, implementing intelligent process automation also involves some challenges, such as:
Inability to utilize IPA: Although the world of automation is evolving rapidly, not every company knows how to harness the capabilities of intelligent process automation. Many organizations lack the awareness of how they can integrate it into their business.
Limited Knowledge Base: Intelligent process automation requires a lot of programming languages to implement in a business model. If your employees don’t have that kind of knowledge, then it would become highly challenging to automate your processes or manage them.
Time-consuming: Intelligent process automation projects are pretty daunting to implement as it is time-consuming apart from requiring a good knowledge base to integrate them properly. You will have to train your employees and also perform a lot of trials before optimizing the process perfectly.
Resistance to change: A large part of the workforce in different organizations is resistant to the implementation of IPA in business operations. Although company executives and leadership panels are supportive of automotive, most of the employees don’t approve integration of IPA. They still prefer the old ways and systems.
Implementation cost: Implementing IPA in a business model is costly, and each of the components of IPA requires high investment. Whether it is hardware parts, monitoring, governance, software, or employee training, each of these aspects would incur a lot of upfront investment. The more efficiency you try to achieve with your business process, the more costly it will become to run them.
Future Scopes of IPA
The future of intelligent process automation is unmistakably bright, and more and more organizations are going to adopt IPA in their system. All the technologies are evolving in leaps and bounces, and it is also facilitating IPA to evolve subsequently, which will ultimately help it to provide better results and efficiency.
Moreover, the correlation between business and IT is multiplying as organizations are benefiting a lot from this growth, and they are able to use their resources for other cognitive tasks. Most importantly, customer relationships are also improving with automation because customers are getting comfortable with chatbots that quickly and effectively solve their queries.
Although IPA is still an expensive and time-consuming implementation, the mass adoption of these technologies and affordable alternatives will surely bring down the upfront investment in the future.
Online Learning Resources on IPA
Here are some books and courses that will help you to get deeper knowledge on IPA.
#1. Intelligent Process Automation
The “Intelligent Process Automation A Complete Guide” book by Gerardus Blokdyk is a highly-rated guidebook that tells almost everything you want to learn about IPA. It is a 314-page long guidebook that helps you uncover many things if you are working on IPA.
From learning about basic automation, RPA methodology, and the journey of IPA to getting deep into the operation of IPA tools, you will have complete coverage. Unlike standard textbooks, it highlights a lot of essential facts about IPA along with its challenges and solutions to those challenges.
#2. Intelligent Automation Simplified
Authored by Debanjana Dasgupta and available in both Kindle and Paperback options, this book is dedicated to developers and tech professionals. Through this book, the author wants to guide professionals to take a simple and practical approach to developing and using intelligent process automation.
It is beneficial for professionals adapting IPA tools in their organization because it adequately explains the basic concept of smart automation and how you can implement it. You will also get to learn about each stage of automation design and how you can utilize the knowledge for good use.
#3. RPA & Intelligent Automation Using Python
Created by SeaportAI, RPA & intelligent automation using Python is a highly rated course in Udemy that has benefited many professionals. It is a comprehensive course that includes 3 hours of on-demand video, 17 downloadable resources, and assignments.
If you are working on IPA tools, it will be highly helpful for you because it covers RPA, Python programming, extracting data from a table, and many other aspects. Many top organizations have appreciated this course and have offered this to their employees.
Intelligent process automation (IPA) has become a core part of next-generation business models. As humans are making more advancements in the AI and machine learning field, it is helping IPA to get better with time, enhancing its effectiveness and efficiency.
As a result, many top organizations have already adopted it in their future development goals. They are gradually realizing the benefits of IPA in their business operations and how it would mold their future. Although IPA still has a long way to go, it still serves as an effective solution for intelligent automation in the business.
Amrita is a freelance copywriter and content writer. She helps brands enhance their online presence by creating awesome content that connects and converts. She has completed her Bachelor of Technology (B.Tech) in Aeronautical Engineering…. read more
Narendra Mohan Mittal
Narendra Mohan Mittal is a Senior Digital Branding Strategist and Content Editor with over 12 years of versatile experience. He holds an M-Tech (Gold Medalist) and B-Tech (Gold Medalist) in Computer Science & Engineering.
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