DISCO Box – Data-Driven Decision Tool for AI Portfolios

The development and deployment of AI systems pose technical, organizational, and regulatory challenges for organizations. A structured, comparable assessment of use cases is essential to identify risks at an early stage and leverage potential effectively.

The DISCO-Box supports decision-makers and agile teams in evaluating AI use cases within their broader organizational context rather than in isolation. Based on current scientific insights and empirical analyses of more than 30 AI projects across key sectors such as industry, logistics, healthcare, and public administration, the central dimensions of AI systems, their implementation, use, and regulatory classification have been identified. This approach makes AI applications systematically comparable both within organizations and across sectors.

On this foundation, patterns, correlations, and synergy effects become visible that are often hidden in traditional project evaluations. As a result, priorities can be set in a data-driven manner, resources can be allocated more effectively, and strategic misallocations can be avoided.

The structured analysis enables project leaders and executives to make well-informed investment decisions, identify scaling potential early on, and proactively address regulatory risks. Individual ideas evolve into a manageable and strategically aligned AI portfolio.

The demonstrator was developed as part of the BMDS project “CRAI – Real-World Laboratory for Trustworthy AI in SMEs”.