India, Sept. 30 -- Let's jump right into it: By now, we have learnt that AI tools can only act on the information they receive. As companies move to tools that assess creditworthiness, support clinical workflows or execute tasks, data quality is becoming a condition for safe deployment when utilising AI agents.

The challenge goes beyond correcting typos. Data can be stale, duplicated, inconsistent or incomplete, and AI agents may lack the organisational context needed to use technically accurate information. The issue is whether companies can trust data for each decision, and what can be done to ensure that happens, along with its impact to the organisation.

Let's explore the realm of data quality for enterprise AI in this edition of Th...