AI has the potential to impact nearly every industry and department, but it's not universally applicable. Some projects fail because of infrastructure and data issues, but in other cases, AI is simply not the right tool for the job. It's essential for businesses to understand the problem they are trying to solve and to apply AI where it can bring the most value.
AI projects can fail to deliver in cases where there is a lack of high-quality, structured data or where objectives are too ambiguous. For example, automating customer service interactions without sufficient human oversight, the right data needed to support it or proper testing. Without a solid data strategy, AI models will always struggle to deliver meaningful insights.
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