The next enterprise AI advantage is better business context
By Selvakumar, Senior Director of Technology, Eucloid Data Solutions
Every few months, a new model tops the benchmarks. Yet in the enterprise systems my teams build, model capability is rarely what limits an AI use case in production. What limits it is how little the model can access the business it serves, and how reliable that access is.
Consider a simple question for an internal assistant: how many active customers did we have last quarter? To answer correctly, the system needs to identify the authoritative data source, understand how “active” is defined, account for duplicate records and respect the user’s access permissions. A more capable model cannot compensate for missing definitions, conflicting records, or unclear access policies.
This is driving a fundamental shift in data engineering. The discipline has traditionally been viewed as plumbing: move data from A to B, clean it up and make it available. Enterprise AI expands...
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