Do enterprise AI projects deliver measurable ROI?

Of 3,307 source-linked enterprise AI deployments tracked by AI Use Cases Hub, 1,522 (46%) report a measurable result. The most-documented is a median 50% reduction in time & speed, across 639 reported metrics.

What returns do AI deployments actually report?

The most-reported quantified returns are time & speed (median −50%), cost savings (median −43%), quality & accuracy (median +90%), productivity & throughput (median +43%). Vendor-published evidence skews toward successes, so read these as reported outcomes, not guaranteed results.

AI ROI

AI ROI: what actually works

The headlines say most enterprise AI never pays off. This is the other half of the story — what the deployments that shipped actually returned, and whether the gains lasted — computed from a continuously updated, source-linked corpus, not a survey.

Documented deployments

3,307

source-linked

Report measurable ROI

1,522

46% of cases

Median time & speed

−50%

across 639 metrics

Still live since 2023

97%

public evidence today

Most reporting on enterprise AI dwells on the pilots that stall before they return anything. This page measures the deployments that actually shipped: AI Use Cases Hub tracks 3,307 source-linked enterprise AI deployments, of which 1,522 (46%) report a measurable result — led by a median 50% reduction in time & speed across 639 reported metrics. Of the 166 deployments first documented in 2023 we can judge, 97% still have live public evidence today.

What the returns look like

Median reported change in the most-documented outcome categories, among the 1,522 cases with a quantified result. Longer bar = larger reported gain.

1,522 of 3,307

report a measurable result

Time & speed−50%

median reduction · 639 metrics

Cost savings−43%

median reduction · 324 metrics

Quality & accuracy+90%

median improvement · 266 metrics

Productivity & throughput+43%

median improvement · 205 metrics

Full outcome benchmarks →

Do the gains last?

Of the 166 deployments first documented in 2023 that we can judge, 97% still have live public evidence today — 67% because the organization has since been documented doing more AI. This measures the durability of public evidence, not whether a system is still in production.

66.9%Organization expanded
30.1%Original source live
3%Lost public footprint

How persistence is measured →

Build, buy, or compose?

Across 2,208 deployments where the build approach is documented (68% of 3,231), this is how teams split between building custom (Build), buying off-the-shelf (Buy), and composing with low-code (Compose).

70%

13%

BuildBuyComposeMixed

2,208 of 3,231 cases classified (68%) · Compare all use-case types

Go deeper

The full evidence base behind these ROI figures.

Outcome benchmarks →Deployment persistence →State of Enterprise AI →Browse every deployment →

AI ROI, answered

Do enterprise AI projects deliver measurable ROI?: Of 3,307 source-linked enterprise AI deployments tracked by AI Use Cases Hub, 1,522 (46%) report a measurable result. The most-documented is a median 50% reduction in time & speed, across 639 reported metrics.
What returns do AI deployments actually report?: The most-reported quantified returns are time & speed (median −50%), cost savings (median −43%), quality & accuracy (median +90%), productivity & throughput (median +43%). Vendor-published evidence skews toward successes, so read these as reported outcomes, not guaranteed results.
Do enterprise AI deployments last, or get quietly shut down?: Of the 166 deployments first documented in 2023 that can be judged, 97% still have live public evidence today — 67% because the organization has since been documented doing more AI. Only 3% have lost their public footprint.

ⓘ How this is measured

Every figure is computed from the AI Use Cases Hub corpus — a continuously updated set of real, source-linked enterprise AI deployments — not a survey or estimate. Outcome figures cover only the subset of cases that report a quantified result, normalized for comparability; persistence covers the 2023 cohort old enough to judge. Vendor-published evidence skews toward successes, so treat these as reported outcomes, not guaranteed results.

Data updated June 22, 2026.