One way organizations have found success in building trust and achieving higher rates of project success for companies is by starting every AI project with a discovery and design process.
Trust in AI companies has dropped globally to 53%, down from 61% five years ago, with the U.S. experiencing a 15-percentage-point drop to 35%. Lack of trust is tied to human adoption challenges, alignment with business values, risk management, and costly data curation.
AI projects often face challenges due to human resistance in using models, and mismatches between real-world expectations and lab-designed models. Data and AI literacy are lacking, with less than 25% of the workforce considering themselves data literate.
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