This article presents a phase-based ROI model for enterprise AI, showing essential benchmarks for CFOs, indicating realistic expectations.
The single most damaging piece of misinformation in enterprise AI is the promise of rapid return. Drawing on 52 enterprise AI deployments, this article presents a phase-by-phase ROI model accounting for hidden costs of integration, change management, and data remediation. The AI ROI J-Curve framework matches observed production data and provides use-case-specific timeline benchmarks enabling CFOs to set defensible board expectations.
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Oleh Ivchenko (2026) studied this question.
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