One of the major advances in process technology today is robotic process automation (RPA), which simplifies business operations. According to Gartner, RPA is growing rapidly and shows a 20% increase in 2022 (in comparison with 2021).
Forrester estimates that by 2025, the RPA market will grow to $22 billion, and millions of robots will be performing office, administrative, and commercial work. In its latest Future of IT report, it identified automation as one of the top five trends transforming successful businesses.
Also, Statista predicts that the RPA market size will have exponential growth.
The industry is surely promising, so let’s investigate the latest trends to follow in the coming year.
By 2030, more than 800 million people will be out of work because of robots — this is a fifth of the entire working population. More and more companies are starting to think about automating various processes. In the future, this approach will become necessary for business survival.
RPA systems are now most often used in finance, accounting, healthcare, HR, supply chain management, etc. Analysts believe that in the near future, the sales and customer support services of companies' front offices will show the greatest interest in implementing RPA projects.
So far, RPA systems are being implemented more often in large companies, but software robots will gradually cease to be exotic and “go down” to small and medium businesses.
Currently, industries that use RPA solutions the most are insurance (38%), retail and hospitality (36%), energy and utilities (30%), and healthcare (30%).
Source - https://flobotics.io/wp-content/uploads/2022/08/Use-of-RPA-across-industries-800x416.jpeg
For several decades, when companies needed to create the desired product, they had two alternatives. Organizations could create a platform, different apps, or anything else with the help of a team of programmers or order product development from outsourcing companies. Today, there is a third alternative — affordable and easy to use.
No-code and low-code tools closely match business requirements, allowing faster implementation of tasks and, as a rule, costs much less than programs developed in-house.
The trick is that programmers pass on a minimal amount of their own experience to other users who do not know what code is and do not know how to use it. Thanks to the intuitive interface, people have the chance to develop and implement their own ideas without programming experience.
The peculiarity of using low-code and no-code is versatility. These technologies can help both individuals and large companies boost productivity and speed up digital transformation.
(*Mainly used by developers since basic programming knowledge is required).
Low-code tools are something in between development without code and full-fledged programming. Although it requires some programming knowledge to finish the product, low-code is still much easier and faster than coordinating entire projects from scratch. Similar to no-code platforms, low-code tools use visual components to create mobile or business applications.
Low-code has almost all the same advantages as no-code tools: speed to market, lower costs, and ease of modification and maintenance, although not at the same level. If no-code technologies don't offer all the functionality you need to create a user interface, then low-code is sure to be a good alternative.
(*Used by anyone who has learned how to use it. Can be implemented immediately).
One can be skeptical that creating a product without using code is possible. The trick is that technologies that help create the product without code still have this code. It's just not visible to regular users.
As we have already said, this product is aimed at people with little or no programming experience. People rely on visual features to implement workflows, user interfaces, data modules, and everything else. For example, a UX designer can use pre-designed and coded modules, dragging and dropping them into a single blockchain in order to achieve the desired result.
Such tools offer a number of advantages over traditional programming. Startups that need to cut costs can use them to start working as soon as possible and don't hire highly-paid specialists.
Also, no-code tools can make it easy to modify or update some existing applications by adding or removing blocks as needed. At the same time, a person must be sure that new modules will be correctly integrated with existing ones. Otherwise, nothing will come of it.
Implementation of RPA is not necessary for every company. First of all, we are talking about organizations that operate in a virtual environment and require simultaneous work with several information systems. In this case, it becomes necessary to manually enter certain data not only for each system but also for each application. In most cases, such data is the same but not recognized by different systems.
RPA allows you to quickly and efficiently copy information data of large volumes when moving from one information system to another or when integrating work in several systems at once.
Also, the need for robotization and automation of production processes is necessary when switching to new versions of systems and working with several sources of information simultaneously.
First of all, enterprises that require frequent repetition of the same type of operations need RPA the most.
This applies to:
In these cases, the introduction of robotization of manufacturing processes will save a lot of time. Using AI tools, you can receive and acknowledge receipt of emails much faster than manually, send standard documentation to pre-generated addresses, exchange other necessary information, and control the timely sending of any information data. The robot cannot make mistakes in entering data and is able to send them at a speed exceeding normal human capabilities.
The main business benefits that automation is designed to provide are cost reduction and workflow optimization. Integration is relevant in many areas, from the administration of IT infrastructure to structuring financial and accounting reports.
Instant processing of requests ensures that the correct information is received, allowing corporate employees to focus on solving more important tasks. Practice shows that system products improve the efficiency of production cycles by reducing the number of errors associated with the human factor.
The positive aspects that distinguish the technology under consideration are:
RPA can reduce the risk of a cyberattack in 5 powerful ways:
An additional benefit of implementing RPA to mitigate cybersecurity risks is the ability to track and log the activities of software robots. Due to this, interference with personal data becomes impossible.
Also, RPA can help businesses comply with regulatory requirements such as the EU's General Data Protection Regulation (GDPR) or the Payment Card Industry Data Security Standards (PCI DSS).
Wondering how RPA can grow by 2030? Add machine learning, advanced data analytics, and blockchain to it.
The use of AI (RPA +AI = Intelligent Automation (IA)) allows, for example, to automate the decision-making process to some extent, including risk management in the supply chain. Instead of doing it manually, the employee enters many relevant data sources into the AI data repository, then sets up several “what if” risk scenarios for the system to analyze all this and return answers. For each risk model, it can usually produce several scenarios for the development of events, but the final decision — to accept it or reject it — depends on the person.
Further empowering AI with ML allows it to independently discover and analyze data patterns and learn from them. The advantage of this automation method lies in the speed inaccessible to humans, with which the system can independently process data and recognize patterns. ML can quickly detect important patterns and trends in the situation under study by the enterprise, which potentially gives a person time to react to an event.
Thus, we have a great trio:
The latter is trained using patterns and trends that occur at data points that AI is tasked with evaluating. Together, RPA, AI, and ML play an important role, but for them to become effective tools for business process automation and learning, they need to be intelligently organized together.
Undoubtedly, the trends of 2023 will soon be replaced by a number of brand-new hardly imaginable ones that will come together with wider adoption and development of the technology.
Already now, we can see that a person is surrounded by a large number of technologies and developments that automate processes: applications, bots, assistants, and so on. This approach is also actively beginning to be used by businesses.
RPA is one of the most effective technologies for process automation in 2022-2023. And in the era of digitalization, enterprises that first adopt these “wild" solutions will sooner adapt to the changing world and maximize their performance indicators.
RPA is ideal for systems where a high level of human data processing is required. For example, manual transfer of information, filling out reports, collecting data from different systems, etc. Such processes take a lot of time and require extra costs. Therefore, RPA tools are a perfect solution.
Do you want to know how else your business can benefit from this technology? Are you wondering how RPA will develop in 2023? Click the link!
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