Real-time and accurate - AI automates processes

AI is not an end in itself. It must have an effect where it demonstrably generates enormous significant time and cost advantages and leads to acceleration in B2B communication.

Companies should look for an ideal use case. It is important to start with concrete available AI tools to make processes more effective and efficient through useful complementary techniques.

Operational purchasing, for example, is predestined for this. The reason for this is that the process chain here is still predominantly manual, with many error-prone activities.

There is a high need for automation from internal ordering to invoicing the vendor. Lack of standards, interface problems (internal and external), poor data quality and incorrect entries have an impact on downstream processes in accounting and controlling, production, warehousing and logistics.

Customer satisfaction falls by the wayside. In many cases, the following activities are still performed "by hand": Receiving and checking supplier self-disclosures; sending inquiries to suppliers; obtaining quotations; sending orders; manually entering incoming customer orders; checking, comparing, and entering incoming supplier order confirmations, shipping notifications or delivery bills, and supplier invoices; processing attachments to documents (drawings, certificates, etc.).

The pressure is on. The effort for manual operational processes increases exponentially with the number of document flows or transactions and the number of suppliers.

Once you have calculated the (high!) effort in black and white, you should be very interested in automating your operational activities, if only for reasons of self-protection.

Purchasing, for example, is expected to make demonstrably higher contributions to earnings. However, "traditional" techniques do not solve the problem. EDI, OCR and supplier portals have acceptance problems. They simply cannot offer sufficient benefits to all sides.

This is where AI comes into play! It adds enormous value - if it demonstrably leads to automation, facilitation and acceleration in B2B communication. It can support the exchange of information and at the same time put content into relation.

During processing, it imitates the human behavior of the process participants. In real time, precisely, silently. In operational purchasing, for example, this applies to the extraction of data, the validation of information, the comparison of data and information, and the further processing or transfer of the correct/clean information to the downstream company systems.

The less a buyer has to intervene "by hand" here (preferably not at all!), the better. In the area of strategy, the requirements are growing immensely. Here, human expertise (experience, anticipation, consideration, decision-making) is increasingly becoming the critical factor for success. AI creates more time and space for this.

AI also has to learn. The learning effect increases proportionally with the data volumes supplied (training!). The more complex, the better, and the more transaction volume, the more accurate the result.

Once the AI has been taught to read, it can then read any number of books in any language. Ideal combination: AI is "coupled" to a software-as-a-service platform (SaaS).

This means that, for the first time, unstructured data in free texts or documents such as order confirmations and customer orders can also be harmonized. Manual intervention is no longer necessary.

Conclusion: The advantages of innovative technologies should be made accessible to all internal business partners as far as possible. However, new approaches also need to be presented externally.

This is AI that can replicate human ways of thinking and working, taking over the checking, validation, matching and further processing of documents and data, and ensuring extremely high (close to 100 percent!) data quality.