---
id: "claim-enterprise-lag"
type: "claim"
source_timestamps: ["§ Innovation Meets Speculation"]
source_url: "https://hbr.org/2025/10/is-ai-a-boom-or-a-bubble"
source_title: "Is AI a Boom or a Bubble?"
tags: ["enterprise-adoption", "roi", "risk-management", "enterprise-ai"]
related: ["concept-stranded-assets", "entity-stanford-ai-index", "question-enterprise-demand-timing"]
confidence: "high"
testable: true
sources: ["futures"]
sourceVaultSlug: "hbr-seg-futures"
originDay: 2
articleStem: "hbr-foci-74-ai-boom-or-bubble"
sourceUrl: "https://hbr.org/2025/10/is-ai-a-boom-or-a-bubble"
sourceTitle: "Is AI a Boom or a Bubble?"
---
# Enterprise AI Adoption Is Lagging Consumer Enthusiasm Due to Risk and ROI

**Claim (confidence: high · testable: yes).**

While consumers adopted ChatGPT at record speed (**100 million users faster than any prior app**), enterprises are hesitant. Citing the [[entity-stanford-ai-index|Stanford AI Index]], business adoption rose to **78% in 2024 (from 55% in 2023)** — but this adoption is *tentative*. Companies cite **privacy, reliability, compliance, security, and financial risk** as primary barriers. Furthermore, **MIT research** indicates that productivity gains *at scale* remain elusive, preventing enterprises from committing capital without a clear line of sight to financial returns. This adoption gap is what makes [[concept-stranded-assets|stranded assets]] plausible; whether the gap closes in time is [[question-enterprise-demand-timing|an open question]].

> **Enrichment / verification:**
> - **Direction — well supported.** A Cisco AI Readiness Index reports only a *small fraction* of companies successfully deploying AI at scale despite near-universal urgency; Fidelity notes capex is rising faster than returns.
> - **Numbers — survey-based.** The 55%→78% figures come from the Stanford AI Index and should be treated as survey estimates, not hard deployment metrics (exact percentages vary by edition).
> - **Counter-view.** Many large firms report rapid *pilots/targeted deployments* (customer service, coding, document processing); 2025 outlooks highlight cost-efficiency use cases getting real traction — enterprise adoption may be somewhat faster than portrayed, even if full transformation lags.


## Related across articles
- [[claim-ai-productivity-enabler]]
- [[question-enterprise-demand-timing]]