Building a Bright Future with Data-Driven AI Decision Making Systems
If your remit is to help your organisation add AI agents to accelerate its processes, you have to start at the foundation - and that means making your data available for AI consumption. Agentic AI scales on data strength, as Niels Zeilemaker, global CTO at Xebia, explains. “If you don’t think about that, you can quickly find yourself struggling to implement AI agents in a meaningful way.” This is because the effectiveness of AI decisions depends heavily on the quality and quantity of available data.
In order to effectively leverage AI, organisations need to invest time and resources into creating a robust data foundation. This involves collecting, processing, and storing relevant data that can be fed into AI models for analysis. Without a strong data base, AI agents will struggle to provide accurate insights and recommendations, leading to subpar decision making systems.
The consequences of neglecting the data foundation can be severe, including reduced business efficiency, decreased revenue growth, and even organisational instability. To avoid these pitfalls, organisations must prioritise building a reliable data infrastructure that enables them to harness the power of AI agents effectively. By doing so, they can unlock new levels of innovation, agility, and competitiveness in their markets.