Automating business processes with RPA and AI
Automating business processes with RPA and AI
Faster, more productive, more customer-friendly: automating business processes with RPA and AI technology
Faster, more productive, more customer-friendly: automating business processes with RPA and AI technology
From master data management and customer service to marketing and sales. Robotic Process Automation (RPA) and Artificial Intelligence (AI) promise to automate many standard tasks in modern companies, free up employees and increase productivity. We explain how RPA and AI work and how small and medium-sized companies can save time and money and increase customer satisfaction by using the new technology.
RPA: What does robot-assisted process automation mean?
Robotic Process Automation (RPA) is a technology for standardizing and automating business processes in companies. You use software robots wherever you process structured data:
- Filling out forms
- Update databases
- Carry out registration
- Opening files
RPA really comes into its own when you link several small tasks together to automate multi-stage processes.
The difference between RPA and AI
In the public debate, RPA and AI technologies are often discussed together. But there is a fundamental difference between software robots and artificial intelligence: AI programs learn – RPA software does not.
RPA software works like a virtual assistant. It relieves you of time-consuming, repetitive tasks and always produces the same result.
An AI, on the other hand, should react dynamically to different challenges like an employee. It simulates human learning and thinking and adapts its approach based on experience. AI can therefore also handle unstructured data.
With AI software, you can therefore also automate processes that involve images or natural language.
Example: AI-controlled and RPA chatbots
Chatbots are small programs that respond to user input. They are very popular in both customer service and internal communication. Chatbots illustrate the difference between robotic process automation and artificial intelligence.
An RPA chatbot does not understand the other person’s input. Instead, it works with a series of keywords for which predefined answers are stored. If a customer asks: “How much are the shipping costs?”, the robot recognizes the keyword “shipping costs” and answers the question.
This limits the software robot. If the customer uses a formulation without a keyword (e.g. “How expensive is shipping?”), it will not receive an answer to the question. In this situation, the AI-controlled chatbot shows its strength. It learns as it is used and is therefore able to understand unstructured input.
RPA and AI: intelligent process automation
RPA and AI describe two different approaches to automating different types of processes. RPA robots deal with structured data, AI with unstructured data. In business practice, however, there are always overlaps. Many processes contain both structured and unstructured data. Chatbots, for example, often rely on AI-controlled processes to understand user input or generate response texts.
Even if RPA and AI pursue fundamentally different approaches, the importance of intelligent process automation (IPA) will grow in the future because it best reflects the reality in companies.
The goal of RPA + AI: end-to-end automation
The modern customer is impatient. Thanks to the triumph of digital platforms, we are used to being able to satisfy a need at any time. Salesforce recently showed in a study that this habit is increasingly becoming a requirement for companies. 89% of all customers expect the same convenience when booking services that they are used to in their everyday lives.
Accordingly, end-to-end automation is a kind of Holy Grail in the combination of RPA and AI technology. It describes the automation of the entire process chain from the customer to the company. This has a decisive advantage for customers: they get what they want immediately, without having to rely on an employee.
RPA and AI combined: complete automation of a new application
A company operates a trading platform for cryptocurrencies. Anyone wishing to open a wallet must not only register, but also submit documents for verification. To do this, an employee looks at the documents, checks them for authenticity and carries out a data comparison. This process is time-consuming and not scalable. Every new customer costs the employee the same amount of time.
With a combination of RPA and AI technology, you can fully automate this process:
- In the initial contact, a chatbot verifies the type of account and provides the customer with the appropriate link.
- Once the form has been completed, it is forwarded to another robot, which carries out the necessary processes in the background.
- An AI-controlled OCR robot analyzes the documents that the customer has uploaded for verification.
- The customer misspells their name. So the robot forwards the case to an employee.
- The employee uses the ID card number to manually check the accuracy of the data.
- The robot learns from the employee’s behavior and will gradually incorporate the verification into its own routine.
Four advantages of RPA and AI: intelligent process automation in practice
Robotic process automation offers companies of all sizes a range of benefits:
Electronic data processing ties up human resources. Software robots take over a large part of the standard tasks and thus save time and financial resources.
The use of RPA in personnel and order management has a positive effect on productivity. Nevertheless, the fear of job losses proves to be unfounded when using software robots: Software robots are dependent on human employees.
Standardizing and automating processes helps to create a uniform customer journey across all channels and thus a consistent customer experience. By using chatbots for initial contact, for example, you can pre-sort inquiries and answer simple standard questions immediately.
Big data offers a great opportunity: all data is available in digital form and can therefore be compared with each other. A robot helps to analyze key figures and make them available to the user automatically.
In combination with AI, complex methods of predictive analytics can also be carried out automatically. Predictive analytics makes predictions about the future. Mathematical models are used to analyze and extrapolate existing data points. You use this valuable information to make better, data-based decisions.
Conclusion: For whom is the use of RPA and AI worthwhile?
Many decision-makers in German companies believe that AI technology and automation are only worthwhile for large corporations. However, the use of software robots is also worthwhile for small and medium-sized companies in all sectors.
Against the backdrop of digital transformation, the pressure on small and medium-sized companies is increasing: They all need to work more efficiently and productively in order to keep up with young start-ups and other competitors.
Companies should therefore take a close look at their own business processes: Where do you find recurring standard tasks that you can automate by using (AI-supported) software robots?
