The Age of Thinking Machines

RPA, or Robotic Process Automation is an important step – but it is only a first step. These systems can scrape data from the Internet and format it according to the user’s requirements. This automatically turns unorganized and coarse data into structured, readable and scalable information. Based on the „scraped“ data, the tool can be instructed to perform certain tasks, such as automatically filling out a web form.

For example, hiring a new employee in most companies, especially larger ones, requires simultaneous data entry and provision in several systems. If these systems cannot communicate with each other, the same data must be entered manually in several places, if necessary. And because mistakes are made wherever people are working, avoidable costs and disruptions in operational processes are incurred.

Cognitive Automation, the next step, allows the software to do without predefined processing rules. Such systems can „read“ archived documents or e-mails or emails and categorize unstructured data volumes through digital data training. The more data the software organizes and processes using machine learning, the faster and more effectively it develops. Scanned incoming invoices are evaluated by this process automation in accounting using text recognition and payment advice notes are interpreted.

Taking things to the next level, system will use software robots and chatbots to iput both text and voice to perform tasl based om natural language processing. Digital assistants recognize spoken and written language and have the skills to understand the information it contains. They extract relevant data, process it further and act as a link between people and the system. Their assistance starts with making appointments and extends to supporting complex customer processes. Over time, the system learns to independently recognize anomalies in the data and can proactively inform the user.

The fourth and highest level of automation is reached when intelligent software can act independently and initiate processes. It can make decisions without human intervention and control processes independently. They can process huge amounts of data in a very short time, which will make them irreplaceable in the field of predictive analytics. Unfortunately, however, only two percent of German companies are working with such autonomous systems, while a further three percent have started testing them. This will have to change for many companies if they want to remain internationally competitive in the long term.

Since RPA accesses core business processes, security is a key issue. There must be integrated protection devices that can detect and localize unusual or conspicuous behavior. In fact, most RPA vendors are focusing on what could almost be called a cyborg approach to this issue.  With all the automation, people will still have to be the focus, but with RPA they will have superpowers. RPA could help to bundle alarms, organize countermeasures and categorize damage events so that they are more manageable.

What does the future hold for a more comprehensive integration of information flow between companies – from AI and robots to business functions such as planning, billing, inventory management and marketing?  Where does RPA really start to make an impact?

The answers are not yet clear, but the first trends are already emerging. Both automation and general business processes need to be further improved and transformed to meet increased consumer demand. In today’s market, the customer is the driving force behind product design, development and delivery. To remain competitive in their respective markets, manufacturers must implement an integrated system that includes a customer-centric platform.




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