Introduce AI into your organization and into all your new or existing RPA processes
AI (artificial intelligence) can contribute to the improved use of RPA (Robotic Process Automation) for companies and organizations. For example, by making RPA smarter, performing accurate analyzes and predictions, and with more efficient operational processes.
Intelligence: Traditional RPA can automate standardized, repetitive tasks, but when the tasks become more complex and require human intelligence, it falls short. With AI, companies can automate more complex tasks such as understanding natural language, making decisions based on complex algorithms, recognizing patterns and predicting future trends.
Efficiency: AI can increase the efficiency of RPA by automating tasks that are time-consuming or require human input. Consider, for example, customer service tasks, data processing or inventory management. With AI, these tasks can be completed quickly and accurately, saving companies time and money.
Predictive Analytics: AI can also improve RPA by performing predictive analytics. This means that the system can predict future trends based on historical data. This can be used, for example, to predict demand for a product, assess the efficiency of a process or calculate return on investment.
As MvR Digital Workforce, we attach great importance to transparency, a fixed way of working and governance. We also ensure that all aspects of privacy and security are safeguarded in a pilot phase to ensure that the pilot can be carried out safely. We use Microsoft Azure AI Services. Azure has already been fully embraced and implemented in many organizations. This way you avoid a discussion about IT infrastructure and software and you can keep focus on your AI experiments.
We have now brought various AI applications into production. O.a. the use of smart assistants using the GPT model and the integration between Azure and OpenAI for specific target groups. And the application of image recognition in combination with analyzing and formulating actions and file formation. But automatically analyzing texts (for example in a Service Desk environment) and formulating next steps is also possible.
More information about the combination of Microsoft Azure AI Services, Large Language Models (LLMs) such as GPT and the integration with OpenAI can be found on this page: Large Language Models (LLMS) – MvR Digital Workforce
MvR organizes inspiration sessions for organizations that want to know more about the use of AI and the combination with new or existing RPA processes.