RPA and AI: The Dream Team Revolutionizing Modern Procurement

In today's fast-paced business environment, procurement departments face increasing pressure to deliver more value while reducing costs and improving efficiency. As part of the BME Buyers Day at MedtecLIVE 2024, Tim Hädicke from the Fraunhofer Center for International Management and Knowledge Economy IMW shed light on the combination of robotic process automation (RPA) and artificial intelligence (AI). This combination has emerged as a powerful solution to these challenges, creating what industry experts are calling a "dream team" for modern procurement operations.

Understanding the Power Players: RPA and AI in Modern Business

RPA represents a significant advancement in business process automation, functioning as a digital workforce that can handle repetitive, rule-based tasks. As explained by Tim Hädicke from the Fraunhofer Center for International Management and Knowledge Economy IMW as project manager at Mittelstand-Digital Center WertNetzWerke, RPA bots are software robots that interact with computer systems just as humans do – clicking, scrolling, and transferring data between applications. A key advantage is their non-invasive integration: "The software you want to automate doesn't need to be modified, because you create the bot and it operates just like you do with clicks, scrolling, etc." These bots can perform a wide range of tasks, from reading texts and processing forms to combining data from various sources like CRM systems, ERP systems, and warehouse management systems. They can even perform various calculations, create screenshots, handle emails, and generate reports.

AI, on the other hand, brings cognitive capabilities to the table. Unlike RPA's structured approach, AI systems can learn from experience, recognize patterns, and make decisions in situations where rules aren't clearly defined. This makes AI particularly valuable for handling unstructured data and complex decision-making processes.

The key distinction between these technologies lies in their approach to tasks. RPA follows predefined rules and processes, delivering consistent, predictable results. AI systems learn from data and can adapt to new situations, though their results may carry some uncertainty. This fundamental difference makes them naturally complementary in procurement operations.

The Strategic Advantage: Benefits of RPA Implementation

The implementation of RPA in procurement delivers both internal and external benefits that directly impact operational efficiency and strategic value. Internally, organizations achieve cost savings through faster, error-free processing and 24/7 availability. As Tim Hädicke emphasizes, "The computer works faster, works more frequently, and also avoids errors. When I have to transfer an Excel table manually over days, I might make a typing error. That doesn't happen to the computer." Additionally, RPA improves compliance through consistent execution and offers easy scalability - "You might not find a new employee as quickly, but copying an RPA bot and running it on another computer is less complicated."

Externally, customers benefit from improved service quality through error reduction and consistent processing. Unlike human workers who might have "stressful days, boring days, family problems, or illnesses," RPA bots deliver consistent performance regardless of circumstances.

Key advantages include:

●       24/7 operational capability without fatigue or errors

●       Improved compliance through consistent process execution

●       Enhanced service quality and consistency

●       Scalability to handle varying workloads

●       Reduced processing time for routine tasks

Perhaps most importantly, RPA implementation doesn't replace human workers but rather empowers them by eliminating mundane tasks from their daily responsibilities. This allows procurement professionals to focus on relationship building, strategic sourcing, and other high-value activities that require human judgment and expertise.

How RPA and AI Complement Each Other

The true power of these technologies emerges when they work together, each addressing different types of processes. As Hädicke explains, " An RPA bot needs a clear process. I need to know what the RPA bot should do to tell it the steps." In contrast, AI handles undefined processes: "The most famous example is facial recognition. Try explaining to someone step by step how to recognize a face in the pixels of a digital photo. That's where we have AI, which I teach or simply tell 'these are images, these are faces.'"

This fundamental difference makes them natural partners. RPA provides predictable, plannable results through stable, consistent processes, while AI offers adaptability and learning capabilities for handling unstructured data and complex decisions. However, it's important to note that AI results carry some uncertainty - as Tim Hädicke points out, "With AI, you don't always know how it came to the result it gave you and whether it's really correct."

For example, in invoice processing, AI can read and interpret unstructured invoice documents, extracting relevant data points, while RPA handles the subsequent steps of entering this information into various systems and initiating payment processes. This combination dramatically reduces processing time while improving accuracy.

Similarly, in supplier management, AI can analyze supplier performance data and market conditions to make recommendations, while RPA handles the routine tasks of data collection and report generation. This partnership enables procurement teams to make better-informed decisions while ensuring efficient execution of routine tasks.

Practical Applications in Procurement

Several practical applications demonstrate the power of combining RPA and AI in procurement:

• Invoice Processing Automation: AI systems recognize and extract data from invoices, while RPA bots handle the data entry and processing in accounting systems.
• Chatbot-enabled Ordering: AI-powered chatbots interact with users to understand their requirements, while RPA bots execute the actual ordering process in backend systems.
• Inventory Management: AI algorithms analyze historical data and predict future needs, while RPA bots collect data from various systems for the AI and then generate reports.
• Supplier Profile Analysis: RPA bots gather data from multiple sources, while AI systems analyze this information to create comprehensive supplier profiles and risk assessments.

Conclusion

The combination of RPA and AI represents a significant leap forward in procurement automation. While each technology brings its own strengths, their integration creates a powerful solution that can handle both structured and unstructured tasks, delivering unprecedented efficiency and value. As organizations continue to digitize their procurement operations, the RPA-AI partnership will increasingly become a crucial element of successful procurement strategies.

---

Editorial notice:
This article is based on the corresponding presentation during MedtecLIVE 2024 and was created with the support of AI. The supporting programme of MedtecLIVE 2026, which will take place from 5 to 7 May 2026 in Stuttgart, also offers numerous lectures. The trade fair brings together suppliers, providers from the development and production of medical technology, OEMs, distributors and other players in the medical technology community.