Technology has evolved messy processes, and integrating AI can exacerbate failures if not approached correctly. Trust in AI systems is essential; even high-performing solutions can fail if users do not believe in their outputs. Organizations often focus on traditional metrics of success such as performance and cost but neglect the critical aspect of trust. A five-pronged framework is recommended for decision-makers, emphasizing the importance of building trust, encouraging innovation, ensuring clear task completion, measuring implementation metrics, and allowing for adaptability.
Trust is a major factor for the success of AI programs. A superb black-box solution dies on arrival if nobody believes in the results.
Companies have various ways to measure success during AI implementation, but we rarely measure trust, which is crucial for success.
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