{"id":3340,"date":"2020-11-21T16:46:13","date_gmt":"2020-11-21T16:46:13","guid":{"rendered":"https:\/\/logicplum.com\/?p=3340"},"modified":"2023-04-27T06:58:41","modified_gmt":"2023-04-27T06:58:41","slug":"rpa-and-machine-learning-the-promise","status":"publish","type":"post","link":"https:\/\/logicplum.com\/blog\/rpa-and-machine-learning-the-promise\/","title":{"rendered":"RPA and Machine Learning: The Promise"},"content":{"rendered":"

Robotic process automation<\/a> has caused a great sensation in many different industries. When companies focus on the digital revolution, repetitive task automation can increase effectiveness while reducing human error, which is an attractive outcome. RPA will not feel tired, will not feel bored, and will accurately perform tasks to help its human counterparts and increase productivity. RPA allows others more time to focus on higher-level work. In addition to simple RPA, intelligent automation can also be achieved by combining RPA and machine learning, thereby realizing the automation of repetitive everyday jobs and human-like decision making.<\/p>\n

Thanks to RPA, the human workforce no longer has to perform massive amounts of manual work. As a result, employees can spend extra time on essential tasks, improve their work results, and add more value to other important business tasks.<\/p>\n

RPA has already proven to be a significant driver of digital transformation for companies by increasing throughput, reducing expenses, and ultimately fostering profits and business growth. RPA is more than just an idea; its market size is expected to reach $ 3.97 billion by 2025. By incorporating machine learning with RPA, we bring together functions of automation processes, but we go further. We can create high levels of RPA bot that can identify, understand, and draw conclusions from unprocessed data. This creates new intelligent RPA data analysis before working on it, continuously learning from data attributes, makes it smarter over time, and drives smarter decisions based on historical results.<\/p>\n

Companies looking for the next innovation should consider using RPA and ML to smartly automate process automation. Machine learning<\/a> encompasses learning and thinking but is managed by the RPA. Machine learning functions used in conjunction with RPA are technologies such as image and voice recognition or document information.<\/p>\n

Linking machine learning to RPA makes sense when business equipment is installed in an integrated way with their system. The goal is to drive business processes near perfection.<\/p>\n

Practical Case: Automated Payment Accounts<\/h5>\n

Let’s look at a prevalent business case. Many accountants worldwide get a message from their vendors every day, telling them how much to pay.<\/p>\n

Thanks to digital innovation today, invoices arrive at the desktop as PDF files attached to an email.<\/p>\n

The never-ending updates the accountant has to update the information is the same process over and over.<\/p>\n

Here is what we can see is inherent in this process:<\/p>\n