"The fact is, putting new technology into people's hands doesn't mean they will use it well. Fewer than 10% of gen AI use cases make it past the pilot stage. It's a matter of turning experimentation into value-creating acceleration. CEOs might accept that principle, but in practice they are nervous about getting it wrong. A critical way to get beyond the nerves is to build trust."
"Companies where gen AI usage accounts for at least 10% of earnings are committed trust-builders. They are also twice as likely to see high revenue growth (10% and up). In a survey of almost 1,400 companies, 43% of the gen AI high performers ensured that new models allowed audits, risk and bias assessment, compared to 18% for the rest. Four kinds of trust are essential."
Generative artificial intelligence (gen AI) functions as a broad capability rather than a narrow tool, deployable across many contexts to achieve diverse outcomes. Many organizations experiment with gen AI, but widespread, bottom-line impact remains limited despite high reported usage. Fewer than 10% of gen AI use cases progress beyond pilot stages, creating a gap between experimentation and value realization. Executives often hesitate to scale due to concerns about mistakes and governance. Building operational trust is critical for adoption and impact. High-performing companies treating gen AI as material to earnings emphasize auditability, risk and bias assessment, and governance. Four kinds of trust, beginning with trust in the data, are essential.
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