AI in business processes: Opportunities, challenges and success factors

The demand for artificial intelligence (AI) is constantly increasing and more and more companies want to integrate AI systems into their business processes. However, before this technology can be used effectively, some fundamental questions need to be clarified. What requirements are necessary? How can existing processes be optimized to create sustainable added value? And where is the greatest potential for rapid success?

AI use in practice: two typical use cases

Processes such as incoming orders and lead scoring in sales are an excellent starting point for the use of AI in companies. Many small and medium-sized companies receive orders in unstructured formats, such as PDF files, which have to be processed manually. AI can be used here to automatically read orders, assign them correctly and integrate them into systems such as CRM or ERP. One such use case was successfully implemented at one of our customers and led to a drastic increase in efficiency.

AI also offers great advantages in sales. Lead scoring, i.e. the prioritization and evaluation of potential customers, is an area in which AI helps sales teams to work more efficiently and ultimately increase sales. However, before AI can take on such tasks, the company must ensure that the underlying data is consistent and of high quality.

Process analysis and optimization as a basis

Before companies implement an AI solution, they need to analyze their current processes in detail. It is crucial to understand the current state and check whether it is ready for AI. For example, if leads are recorded on notepads or in Excel spreadsheets, the process must first be digitized before AI can be used.

There are four stages that companies should consider when introducing AI:

• Current state: the current process without AI.
• Current state plus AI: What could the current process look like with AI?
• Future optimized process: An optimized process without AI.
• Future optimized process with AI: The final, improved process supported by AI.

Companies should consider what stage they are at and where they want to go. The question often arises as to whether existing systems, such as CRM or ERP systems, are already sufficiently integrated or whether additional tools are required in order to use AI effectively.

Technical and personnel challenges

In addition to analyzing and optimizing processes, companies must also examine their technical and personnel capacities. Do they have the necessary expertise and resources to successfully implement AI projects? Especially in smaller companies with limited IT teams, it can make sense to bring in external support or special tools to facilitate integration and automation.

Another important aspect is data quality. Without high-quality data, no AI solution can deliver satisfactory results. Companies must ensure that their data is consistent and comes from a reliable source. A practical example shows that asynchronous data records in CRM and ERP systems first had to be harmonized before the data could be used for AI processes.

Successful AI implementation: a practical example

Successful AI implementation starts with a clean database and clear structuring of processes. A practical example: a company received orders in the form of PDFs that were structured differently and difficult to read by machine. The manual effort required to process these orders was enormous. By implementing an OCR solution combined with a Large Language Model (LLM), the order data could be captured and processed automatically. The output was integrated into the ordering system, reducing the manual workload by up to 90%.

Conclusion: AI requires thorough preparation

The introduction of AI into business processes offers enormous potential, but requires thorough preparation. Companies need to analyze their processes, ensure data quality and create the technical and personnel requirements to be able to use AI successfully.

With the right strategy and the right tools, such as the frends platform, companies can not only increase their efficiency, but also pave the way for innovative, AI-supported solutions. Start your AI journey now and transform your business processes with us!