Intelligent Process Automation (IPA) - combination of RPA and AI

Almost every company in Germany already has enormous potential to automate processes with robotic process automation (RPA). This potential is being significantly increased by the ongoing development of generative AI. The combination of RPA and AI, also known as Intelligent Process Automation (IPA), opens up new possibilities. By using the rule-based RPA bot to access generative AI, it is possible to automate complex process (steps).

RPA is already standard for many companies

Business processes with repetitive activities and definable workflows can be automated cost-effectively and often completely with Robot Process Automation (RPA). With RPA platforms such as UiPath or Automation Anywhere, cost-effective "off-the-shelf" automation is possible. As a result, surprisingly fast ROIs are regularly achieved in RPA projects. In particular, if the automated process (step) is associated with a high volume of work, a great deal of time can be saved. An increase in quality and savings in opportunity costs are also typical results of process automation.

This type of automation requires significantly less effort than automation through programming. Once the automated process is fully developed, changes are usually only necessary if the user interface of an application is changed without an interface.

Generative AI (GenAI) ‘thinks’ for itself

The major weakness of RPA to date has been the processing of unstructured data. In these cases, AI must be integrated into the automation solution. AI increases the potential of automation enormously by transferring unstructured process inputs into the required format and thus processing them automatically. For example, differently formatted and structured input documents can be analysed and transferred into a standardised target document and are therefore optimised for automated processing.

Another weakness of RPA was the creation of variable outputs that go beyond building block systems. For example, the texts of an RPA bot are either predefined or composed of certain building blocks. If this step is handed over to a generative AI, customised texts can be created. This means that even customer newsletters can be written by an IPA bot, which is enabled to send customer-relevant texts based on documents, product descriptions, etc.

One concrete example is the use of IPA instead of pure RPA in complaint management. While RPA systems can automatically answer simple queries such as status updates or standard complaints, IPA enables the processing and answering of complex customer complaints that require an analysis of emotions and the context of the problem. IPA can recognise the mood in the communication, merge relevant customer data from different systems and generate a personalised response that is specifically tailored to the customer's individual needs and previous experiences. This increases customer satisfaction and optimises the workload in customer service.

As the common RPA platforms already have a range of AI tools integrated, the combination of these two automation approaches is often low-threshold. However, other AI models such as ChatGPT can also be used for an IPA bot.

In addition, the issue of data protection must not be overlooked with conventional AIs. The input used to compile the AI prompt must be able to anonymise itself in an automated process and decrypt itself again after processing by the AI. If, for example, personal data is passed on to an AI data centre without consent, there is a risk of compliance problems.

IPA and Change Management

The implementation of IPA systems brings with it technical and organisational challenges. From a technical perspective, the integration of IPA requires harmonisation with the existing IT infrastructure. If this coordination is not carried out, continuous adaptation and reworking will be necessary. This drives up operating costs.

In organisational terms, companies must accept and promote a change in the way their employees work. This includes change processes for employees to promote their acceptance of the new technologies. It is also usually necessary to redesign processes in order to fully utilise the benefits of automation. An experienced automation team can make a crucial difference here and should not only support the technical implementation, but also offer change management and process optimisation to ensure seamless integration and acceptance within the company.

IPA is at the forefront of digital transformation

With the progressive integration of AI in the field of process automation, IPA is reaching a new level of efficiency and versatility.

• Advanced cognitive capabilities: Further developments in AI will enable IPA to perform even deeper analyses and make decisions that were previously reserved for human intuition.
• Seamless integration: The integration of IPA with IoT and other advanced technologies will continue to advance, enabling automation in other previously manually dominated areas.
• Proliferation of customised IPA solutions: The demand for customised IPA solutions will increase as companies strive to overcome specific challenges in their individual operating environments.

With the ability to process both structured and unstructured data and generate flexible outputs, IPA can automate a wider range of tasks that were previously beyond the reach of RPA. Companies can now not only rationalise repetitive tasks, but also handle complex processes that required human intelligence. This development promises not only cost savings and efficiency gains, but also improved service quality and the opening up of new business opportunities. IPA is therefore at the forefront of digital transformation and will continue to shape the way companies around the world operate and compete.