Artificial intelligence will change almost all areas of life. This has also gained a foothold in the industrial sector. However, there is a huge discrepancies between these ambitions and current reality. Worldwide, only about 16% of all industrial companies have already implemented a solution based on Artificial Intelligence. [1]

Strategy & Roadmap

What distinguishes those companies that already use Artificial Intelligence from the masses is first of all a clear strategy and a practical roadmap. It is important to understand in which areas the use of Artificial Intelligence can bring added value and how the implementation of these solutions must look in detail and can be evaluated.

The road to Artificial Intelligence begins with having a clear goal. The first step is to evaluate the problems and potentials that can be solved or exploited by Artificial Intelligence. A comparison with direct competitors or the industry in general is just as useful. Often clear trends can already be identified and the positions of the own company as innovation leader or even as taillight become clearer.

As part of this evaluation, a high-level digitalisation strategy should be developed that includes clearly defined fields of application. These fields of application must in turn be evaluated and coordinated with all participants so that a clear picture of the use of Artificial Intelligence in the company can be formed and a corresponding roadmap can be developed.

Management is the key

Management also plays an important role, as its role is not only to express its commitment to the use of Artificial Intelligence, but above all to define clear (personnel) responsibilities within the company.

Often there is a lack of basic knowledge about the possibilities of Artificial Intelligence at almost all levels, which ultimately means that potentials are not recognised. Irrespective of whether these are internal or external to the company, people with the appropriate background and experience are needed whose tasks and responsibilities are defined in terms of developing and implementing a clear roadmap to the implementation of Artificial Intelligence.

Pilot projects and agile development

On the basis of the roadmap, initial pilot projects can then be implemented in selected areas of the company in cooperation with all those involved in the respective departments.

These projects are implemented in the form of so-called Minimum Viable Products (MVP), which are the first, minimally functional iterations of a solution. The purpose of this approach is to make the solution available to users in a comparatively simple and cost-effective form and to obtain their feedback in order to expand and improve the MVP in the course of agile development.

Agile development in this context means that there is no attempt to develop a finished solution at the first attempt, but that new feedback is constantly collected in the form of short further development processes (sprints). This ultimately makes it possible to make the entire development process more flexible and streamlined than is the case with classic process models.

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[1] Boston Consulting Group (2018): AI in the Factory of the Future; URL; https://www.bcg.com/Images/BCG-AI-in-the-Factory-of-the-Future-Apr-2018_tcm58-188454.pdf [18.06.2018]