Even companies that started relatively recently are struggling with legacy systems that do not connect well and with data stored in multiple places. This often leads to privacy and security challenges.
The emergence of these problems is often a result of wrong decisions, force majeure, the influence of vendors enforcing their own standards and a certain degree of naivety. The tendency of techies to rely on technology also plays an important role in this.
To cope with the complexity and associated high costs, we are deploying more and more technical solutions. Integration solutions have also evolved tremendously in recent years. The choice of integration platforms, both in the cloud and on-premise, is huge. The possibilities are only limited by the imagination and creative brain of the team working with them.
Because the IT department often cannot deliver what the business demands fast enough, no-code and low-code solutions are often used to try to quickly meet the demand for new applications. However, these tools also require data from external applications or databases, which further increases the need for integration solutions.
This is where AI (Artificial Intelligence) comes in. By adding AI to integration tools, we aim to make the process of getting the right data faster and with fewer errors. Easy-to-understand flow diagrams, for example, help the integration solution to find the right communication protocol itself or provide the right transformation template.
AI can help the expert establish a link quickly and learns more and more from the expert’s actions. But AI can also quickly help others, who do not have the same extensive knowledge of the data, to find the wrong data together. This can be problematic because AI does not distinguish between these two types of users. Therefore, training AI is a task that should always be done by experts.
It is important to start AI early so that specialists can focus on AI’s functionalities and limitations. Ensuring that decisions, which AI models confront users with especially at the beginning, are made by specialists will ensure that the system is trained appropriately.
Integration is complex and has a huge impact on all components touched by integration software. A good start is half the battle. Rather start too early and with the right people than too late, in the overstrained expectation that AI will solve the problems.
