AI alone is not the solution
Many digitization projects in the industry, launched with great expectations, fail. They drag on endlessly, have to deal with skyrocketing costs or fail to deliver the expected benefits – not even a trace of greater resilience to production downtime and more efficient processes that are supposed to lead to higher quality production with lower costs and increased sustainability. Experience shows that projects that involve artificial intelligence or machine learning – both technologies that are truly state-of-the-art and extremely versatile – are particularly often affected. So what is going wrong in companies?
Artificial intelligence delivers value only once it leaves the sandbox and becomes part of real-world processes. An example from the insurance sector shows that thanks to the OpenShift AI platform it is possible to deploy models to production, train them continuously, and improve them. The result is faster processing, fewer errors, and better risk control. Many artificial intelligence projects get stuck at the demo stage. The key is to establish a lifecycle from data and prompts through output generation to feedback that further improves the models. Such an approach requires a platform that enables reliable model operation, monitoring, and integration into existing applications. It can run on your own infrastructure or in the cloud, depending on the organization’s needs.From Prototype to Production
