There are many reasons why AI projects fail. However, the methods, algorithms and technologies usually work and deliver insights from structured and unstructured data. But these results need to be taken into account so that they can have an impact on business processes and contribute to success. If employees have a hostile stance toward a project because they don’t see the possibilities, lack confidence in the new technology, or worry about being displaced by AI, projects will fail even though the technology works. Old World Computing’s standard process for establishing Data Science takes a holistic approach that avoids the biggest pitfalls in AI adoption. “For us, Data Science is more than just a technical solution. It requires understanding throughout the organization and suitable processes” explains Sebastian Land and adds, “Because once employees are familiar with the new tool AI, they will find plenty of use cases and thus also utilize their own Data Science team to capacity. With the right approach, they then find the most suitable cases for their own first steps. Together with our customers, we master the various challenges along the way.”
Many years of experience have resulted in the SPEDS, which prevents many errors. Errors are not only costly, but can also lead to Data Science being off the table for many years. Companies that permanently turn a blind eye to advances in the outside world will be left behind over time.
It is important that competence building takes place within the organization itself, as Sebastian Land explains. Not only to maintain used solutions, but also to be able to identify and implement new use cases for this new method itself. In the medium term, this is simply more favorable and thus a prerequisite for establishing the use of AI in the long term.
Old World Computing (OWC) enables companies to utilize artificial intelligence in a technically and organizationally sustainable way. Therefore, OWC establishes a knowledge transfer in training courses, practical workshops for all levels of the organization and within implementation projects in which the company’s own AI team can be built up and first solutions are put intoGo to exhibitor »