"Your biggest risk in AI isn't prompt injection or data poisoning: it's people-specifically, a shortage of talented people. If your organization can't field enough staff who know how to apply AI to your actual business, you will spend a lot of money on tech that will take you absolutely nowhere. None of this is new: During the cloud computing wave and the first big-data boom (and really, every technology trend), we saw technology race ahead while talent lagged."
"The smartest companies are skipping the hiring arms race and turning their existing engineers, analysts, architects, and developers into AI producers. Why? Because domain knowledge is always the key to unlocking technology, and the people with that knowledge already work for you, as Gartner analyst Svetlana Sicular's observed years ago: "Organizations already have people who know their own data better than mystical data scientists.""
"Enterprises can further accelerate internal talent by leveraging the technologies they already know. The point isn't to avoid learning anything new; it's to minimize context switching so more of your staff can contribute. That's why the "bring AI to your data" guidance matters. If your core systems run on relational databases, for example, use features that let teams keep using SQL while adding embeddings, vector similarity, and JSON/document patterns where they help."
A shortage of people with AI skills is the primary organizational risk, not technical attack vectors. Companies that cannot field staff who can apply AI to real business problems will spend money on ineffective technology. The most effective approach is to upskill current engineers, analysts, architects, and developers who possess domain knowledge. Minimizing context switching and using familiar technologies accelerates adoption. Bringing AI to existing data platforms—such as adding embeddings, vector similarity, and JSON/document patterns while retaining SQL—enables more staff to contribute without a costly hiring arms race. Wage premiums demonstrate the scarcity of AI talent.
Read at InfoWorld
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