Abstract: Artificial intelligence adoption consistently underdelivers on organizational expectations, with failure rates approaching 95% in some estimates. This article examines why AI investments fail when leaders treat implementation as purely a technical exercise rather than a behavioral change challenge. Drawing on behavioral science research and organizational change management principles, we introduce the Behavioral Human-Centered AI framework—an evidence-based approach that addresses human biases, cognitive shortcuts, and resistance across design, adoption, and management phases. Organizations that ignore fundamental psychological patterns—including loss aversion, algorithm aversion, and escalation of commitment—waste millions on sophisticated systems employees resist or abandon. By contrast, those applying behavioral insights across the full change cycle build AI capabilities that align with how people actually think and work, dramatically improving return on investment and long-term competitive advantage.
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