Unlocking Success with AI The Hidden Data Foundation That Fails
If your remit is to help your organisation add AI agents to accelerate its processes, you have to start at the foundation - making your data available for AI consumption. Agentic AI scales on data strength according to Niels Zeilemaker, global CTO at Xebia. However, this often becomes a point of contention when trying to implement AI solutions. "If you don't think about that, you can struggle with scaling as the amount of data increases," he says.
Agentic AI requires robust data sets to function effectively, and without it, these agents will fail to deliver on their promises. This is particularly true for those organisations that rely heavily on traditional manual processes, which are often time-consuming and prone to errors. The challenge lies in getting the right data into the AI system - a task that can be tedious and resource-intensive.
The consequences of not having a solid data foundation can be significant, with some studies suggesting that up to 70% of AI projects fail due to inadequate data quality. This highlights the importance of prioritising data availability and scalability when it comes to implementing Agentic AI solutions. By doing so, organisations can unlock their full potential and achieve greater success with these powerful technologies.