It’s no longer a secret: without AI solutions, businesses will soon run out of steam when it comes to competitiveness. Even those who have buried their heads in the sand in the face of the (perceived) AI avalanche should pull them out now at the latest and get an overview.
It quickly becomes clear that AI solutions for businesses can solve many typical challenges, such as process automation and efficient data processing – but only if they are used correctly. So how can businesses find out which AI software solution really offers an advantage and what is important for a successful implementation?
Our key takeaways:
The best-known tool is, of course, ChatGPT – but it is by no means the only one. Deepseek from China and Mistral from France are other prominent examples. AI solutions use intelligent systems and machine learning to automate processes, analyze data, and optimize decisions. They can recognize patterns, make predictions, and perform human-like tasks, thereby increasing efficiency, reducing errors, and gaining new insights.
When we talk about AI solutions for businesses today, we are therefore referring exclusively to weak AI, or more precisely, generative AI (GenAI), which uses statistical methods to create new content such as text, images, and music. It uses large amounts of data and recognized patterns – think ChatGPT or OpenAI. The label “intelligence” should therefore be used with caution.
What AI already does extremely well is relieve your employees of tedious tasks and perform them more efficiently and with fewer errors. Among other things, AI solutions offer real advantages for companies in the following areas:
And now let’s get specific: What are the areas of application for AI software in companies, and which tools are capable of solving your current challenges? Here are a few examples…
The tools available on the market cover many areas of application to a greater or lesser extent, but none of them cover individual workflows. That is why it often makes sense to use a customized, centralized tool (e.g., based on ChatGPT, Deepseek, Mistral, or others) that maps real use cases from your company.
When it comes to introducing AI in companies, it is best to start with a clearly defined use case. Accounting is a good example here because many processes are routine and can be automated in a meaningful way:
Accounting involves many time-consuming routine tasks that take up capacity for value-adding work. Manual entry and verification of invoices and financial transactions are also prone to errors, resulting in high costs for rechecking and corrections.
With the support of an AI solution, you can automate document recognition and extract relevant data so that accounting entries can be created after automatic categorization and invoices can be assigned to projects. This does not necessarily require completely new accounting software if, for example, you integrate AI tools into existing ERP systems – as already described in the hybrid model.
It must be clear that there is currently no AI solution that can do everything for your company – human control points are necessary and important. However, in line with the Pareto principle, the tool can reduce the time required by 80 percent, giving your employees more time for other tasks while improving your tax compliance.
So what is the best approach for implementing artificial intelligence in your company? First, you need a concrete business case – a clearly defined use case where optimizing processes really pays off for your operational business. You can find this by asking yourself the following questions:
You don’t need to understand AI in detail. It is much more important that you know your company. You know which areas need greater efficiency and lower costs in order to remain competitive.