Data management in the advancing era of AI

Many organisations are currently investing in AI initiatives with high expectations – yet still fall short of the anticipated results. The reasons are rarely rooted in the technology itself, but rather in the underlying foundations: poor data quality, fragmented data landscapes, unclear ownership or insufficient governance. Only a professionally designed data management approach provides the basis for AI applications to deliver reliable results, scale effectively and create real business value. At the same time, the targeted use of AI opens up new opportunities to automate, accelerate and increase the transparency of data management processes.

A future-oriented approach: thinking data and AI together

Organisations that do not treat data management and AI as separate disciplines, but instead view them as an integrated target state, gain a clear long-term advantage. A holistic approach brings together strategy, organisation, architecture and use cases – ensuring that data is understood and leveraged as an enterprise-wide asset. The whitepaper illustrates how organisations can realise this target state. Complemented by insights from the Data Maturity Check and expert interviews, it provides valuable perspectives on the capabilities companies need today to successfully deploy AI – and how they can deliberately evolve their data management to unlock the full potential of AI.