OPINION. The AI gap in the corporate world
The discussion about artificial intelligence in companies still revolves around a question that is starting to become outdated: how many people are using AI? The relevant question now is a different one: how much work can AI already perform from end to end, with autonomy, measurable quality, and clear economic return?
The discussion around artificial intelligence in companies has shifted from how many people are using AI to how much work AI can execute autonomously with measurable quality and clear economic return. While many companies are still trying to reach the second phase of AI adoption, labs are already working on the third phase: systems that execute tasks, evaluate their own performance, identify failures, and improve.
The technology is advancing faster than most companies can incorporate, and the main bottleneck is no longer access to good models, but rather administering them and measuring their performance. Companies need to establish evaluations to measure the quality, efficiency, and reliability of AI work, similar to how they measure human performance, in order to give AI autonomy and ensure it is doing a good job.
Written by urgent.news from Brazil Journal's report — not a translation of it. Machine-written — may contain errors; check the original before relying on it.
