Give an AI agent bad data, and it can make bad decisions at machine speed.

AI agents are ushering in a new era of business automation, completing tasks, making decisions and taking action with far less human intervention. But their ability to deliver useful results depends on the quality, accessibility and governance of the data behind them.

Most businesses do not need more data. They are already drowning in it. The real challenge is turning fragmented, inconsistent and poorly governed information into data that AI agents can understand and use safely.

Gartner has predicted that inadequate data management infrastructure will be responsible for 60 percent of AI project failures. With autonomous agents, the danger is even greater because errors can spread rapidly across workflows, customers and business systems.

Data readiness is therefore becoming central to successful agentic AI. Here are four practical steps businesses can take to prepare their data, reduce risk and turn AI agents into a genuine source of value.

Traditional business approaches to data management have revolved around the fact that information is used solely by........

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