KPI benchmark

How much does AI raise productivity?

Across 55 public AI deployments, the median productivity gain is 50%, and the middle half of them report between 28% and 70%. Increase in output per employee, or share of working time saved.

50%

Median productivity gain

28% to 70%

Middle half of deployments

55

Public deployments pooled

26 of the 55 values are claims by the organization itself, a regulator or an independent study; 29 come from the AI vendor. One value per organization; "up to" claims are listed but not pooled. Data as of 11 November 2026. Methodology

Productivity gain by industry

Median productivity gain by industry
IndustryMedianDeployments
Banking41.7%10
Healthcare40%7
Technology and software82.5%6
Manufacturing30%5
Retail and ecommerce50%5
Professional services52.5%4
Automotive86%3
Government and public sector46%3

How to measure it

Units of work per full time employee, or time studies on the task, before and after.

Across the library

Median 50% across 55 deployments, reported range 8.7% to 336%, plus 8 "up to" values not pooled.

Median 7.5x across 10 deployments, reported range 4x to 46x.

Higher is better. Unit: percent.

Reported values by use case

AI coding assistant for software developers

Real time AI assist for contact center agents

AI cash flow forecasting for corporate treasury

AI for security alert triage and investigation in the SOC

AI supplier discovery and scouting for procurement

AI copilots for production scheduling and sequencing

AI for supplier invoice processing in accounts payable

AI lease abstraction for commercial real estate

Use cases that should track productivity gain

Frequently asked questions

How much does AI raise productivity?
Across 55 public AI deployments, the median productivity gain is 50%, and the middle half of them report between 28% and 70%. Increase in output per employee, or share of working time saved.
How do you measure productivity gain?
Units of work per full time employee, or time studies on the task, before and after.
How does productivity gain differ by industry?
The median productivity gain is 41.7% in banking (10 deployments), 40% in healthcare (7 deployments), 82.5% in technology and software (6 deployments), 30% in manufacturing (5 deployments), 50% in retail and ecommerce (5 deployments), 52.5% in professional services (4 deployments), 86% in automotive (3 deployments) and 46% in government and public sector (3 deployments). Industries with fewer than 3 reported values are not shown.
Which AI use cases report the best productivity gain?
Among use cases with at least 3 reported values: AI for security alert triage and investigation in the SOC (median 60%, 3 deployments); AI coding assistant for software developers (median 22.5%, 4 deployments); real time AI assist for contact center agents (median 20.5%, 4 deployments); AI drafting of radiology reports for radiologist review (median 15.5%, 3 deployments).
Do AI vendors report a different productivity gain than the organizations themselves?
Claims by the organizations themselves, regulators or independent studies have a median of 43.2% (26 values); claims by the AI vendor have a median of 50% (29 values). The page lists both, and every value links to its source.
Where do these productivity gain numbers come from?
From public AI deployments in the Blits.ai AI Use Case Library. Every value is quoted from a named source, each organization counts once, and "up to" claims are listed but left out of the median. Data as of 11 November 2026.