---
id: "claim-ai-roi-timeline"
type: "claim"
source_timestamps: ["¶1"]
tags: ["timelines", "statistics"]
related: ["entity-deloitte", "concept-j-curve-organizational-adjustment", "prereq-traditional-roi-mechanics"]
confidence: "high"
testable: true
speakers: ["Baba Prasad"]
sources: ["spine"]
sourceVaultSlug: "hbr-seg-spine"
originDay: 1
articleStem: "hbr-edu-47-5-types-ai-investment"
sourceUrl: "https://hbr.org/2026/06/the-5-types-of-ai-investment-and-how-to-capture-their-value"
sourceTitle: "The 5 Types of AI Investment–and How to Capture Their Value"
---
# AI ROI takes significantly longer than traditional tech investments

**Claim.** Citing a [[entity-deloitte-d1|Deloitte]] survey of nearly 2,000 executives, achieving a satisfactory ROI on a typical AI use case takes **two to four years** — drastically longer than the **seven-to-twelve-month** payback period typically expected for standard technology investments ([[prereq-traditional-roi-mechanics]]). This timeline gap contributes to the perception that AI is failing to deliver returns.

The mechanism behind the lag is the [[concept-j-curve-organizational-adjustment]]. Confidence: **high**; testable: **yes** (a benchmarkable figure).

**Enrichment / external validation.** The 2–4 year claim is *plausible* and directionally consistent with adjacent research, but the search set does not include the underlying Deloitte source itself, so the specific figure should be treated as **unconfirmed from the evidence available**. Treat it as a credible practitioner benchmark rather than an independently verified statistic.