Your Best AI Asset Has Been Working Here for Years | Opinion
Summary
The article explains that artificial intelligence (AI) often fails in real work settings because it lacks a deep understanding of how tasks are actually done every day. It says AI needs to work closely with experienced people who know the exceptions and complexities of real-world work to be truly useful and reliable.Key Facts
- AI systems may give recommendations that don't consider real-world details like old equipment, weather, or special situations.
- Many AI projects get stopped before full use, with 42% abandoned after initial tests.
- AI technology is improving and available, but turning it into trusted, everyday tools is hard.
- AI needs to understand not just data but how work is done, including rules, exceptions, and judgments people make.
- Experienced workers should help guide AI development to teach it what to know and when to act.
- Real workflows have exceptions and special cases that simple AI models miss.
- Success means measuring AI by real business outcomes, like avoiding losses or speeding critical repairs, not just task speed.
- The next step for AI is to partner with human experts to handle real-life complexities.
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