AI lead the RPA into a new heights, RPA + AI leading business figures reshaping
of: UB Store
Artificial intelligence (AI), since its advent, has been receiving attention. However, the development in recent decades has not made it widely available. At present, the actual implementation of AI application scenarios is still relatively rare, and specific applications still remain in the small areas of predicting machine failure rate, text sentiment analysis, and facial image recognition.
However, the surge of RPA (Robot Process Automation) products in recent years seems to have solved this problem. On the one hand, RPA and AI have certain similarities in terms of replacing manual operations. On the other hand, RPA is faster and has a lower threshold than AI.
RPA can quickly promote the digitization and automated upgrade of business processes without interrupting existing enterprise applications. The application of AI technology is a very important part. RPA+AI will be a major trend in intelligent automation.
The relationship between RPA and AI
The relationship between RPA and artificial intelligence is closer than we thought. We can understand it as human hands and brain.
Artificial intelligence, which usually plays the role of the human brain, is mainly responsible for issuing commands and has the ability to "think" and "learn". On the one hand, AI combines machine learning and deep learning to have autonomous learning capabilities; on the other hand, it has cognitive capabilities through computer vision, speech recognition, natural language processing and other technologies; in addition, AI can also be continuously corrected through big data Own behavior, thereby having the ability to predict, plan, schedule, and reshape process scenarios.
RPA, on the other hand, plays more of the role of human hands, is good at receiving and executing commands repeatedly, and has the ability to "hands on". As a software robot, RPA needs to rely on fixed scripts to execute commands. It is good at performing a lot of repetitive and mechanical tasks based on clear rules. RPA cannot think independently, and can only work rigidly according to the pre-set procedures for it.
AI is mainly data-centric, while RPA is highly process-centric. In specific tasks, RPA can automate repetitive and mechanical workflows while providing artificial intelligence with a large amount of data. Based on the data provided by RPA, AI conducts self-learning, imitates and improves related processes.
The glue for companies to digitally reshape
In the past ten years, technologies such as cloud computing, mobile Internet, blockchain, and AI have brought earth-shaking changes to our lives and work. In these ten years, RPA has also undergone tremendous changes from birth to development, and then to becoming an industry standard.
In the future, how to deeply integrate RPA with AI and other emerging technologies to bring greater value to enterprises and change the way of human-machine collaboration is a question that every RPA practitioner and enterprise customer should think about.
In the next period of time, companies will face the transition from digital transformation to digital reshaping. The difference between digital transformation and digital reshaping is that digital reshaping is subject to various IT systems within the enterprise through restoration, fragmentation, and aggregation to quickly respond to the agile and fast-changing business needs of customers and partners.
In this process, RPA will play a decisive role. With the advent of the AI era, there will be various AI systems, such as: video analysis systems, image processing systems, natural language systems, etc. In the future, the entire IT industry will inevitably present more AI systems and cooperate with each other to handle business. RPA will play a very good role in this process.
At present, many customers have passed the preliminary trial stage of RPA, and many companies are establishing a new service system through RPA. When an enterprise needs to communicate with multiple systems, the data interaction between the systems is complicated. By applying RPA to establish a new automated process at the bottom of the service, the overall business efficiency has been qualitatively improved.
AI embedded in RPA, transformed into a "super robot"
There is no doubt that all walks of life are becoming thriving because of the massive explosion of data. Giants such as Google, Microsoft, and Facebook spend billions of dollars each year on the development of crawling and storing data. The combination of RPA+AI will further solve the problem of enterprise data.
Generally, enterprise data is mainly divided into two categories: structured data and unstructured data.
1. Structured data. The row data is stored in the database, and the realized data can be logically expressed in a two-dimensional table structure. Most companies are using structured data that machines can understand and query.
RPA is born to be a master at dealing with structured data. RPA simulates human employees to automatically execute a series of specific work processes by recording the behavior of manual operations and according to manual operation rules. It has the characteristics of low error rate and high efficiency.
2. Unstructured data. Including office documents in all formats, text, pictures, XML, HTML, various reports, images and audio, video information, etc. Unstructured data is difficult or impossible to explain through algorithms. Most companies are still in the stage of extracting information from unstructured data, and the more important thing to achieve zero-touch operation is the ability to process unstructured data.
RPA equipped with AI technologies such as OCR and NLP will be more than sufficient for the identification and extraction of unstructured data.
The biggest advantage of RPA+AI integration is that it can process a large amount of unstructured data, especially those business processes that consume more manpower and material resources, thereby helping companies save costs and improve work efficiency.
Widespread application of RPA is only the first step for enterprises to become intelligent. With the rapid development of RPA technology, the "century combination" of RPA and AI in the future will set off a trend of change in more industries.
McKinsey has predicted that by 2025, the total value of the global artificial intelligence application market will reach 127 billion US dollars, and it will become a new breakthrough point in the development of the intelligent industry. In such a development, RPA+AI is bound to be promising.