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AI pattern

Code generation use cases

AI that writes, reviews, tests or migrates software code.

Use cases
7
Deployments
44
Organizations
42
Outcome disclosed
66%

7 Code generation use cases

42 organizations in 12 countries run these use cases in public. 66% of those 44 deployments disclose a measurable outcome.

Cross industryBanking

AI assistant for developers integrating a company's APIs

An AI API integration assistant answers developers' integration questions and recommends the right endpoints on a company's developer portal and in its documentation. It also helps debug connections and generates sample calls, grounded in the API catalogue, reference docs and test material, so clients and partners integrate faster with fewer support tickets.

Deployments
6 public, best grade B
Reported contact deflection
30%
Mapbox, organization claim
Cross industryBanking

AI coding assistant for software developers

An AI coding assistant helps software developers by completing and generating code in their IDE and code review flow. It also explains unfamiliar modules, drafts unit tests and reviews pull requests for common defects, while generated code goes through the same review, testing and change controls as any other code.

Deployments
10 public, best grade B
Median productivity gain
22.5%
4 deployments, 1 "up to" value left out
Insurance

AI copilot for insurance pricing and actuarial analysis

An insurance pricing and actuarial copilot is AI that speeds up the work of pricing and actuarial teams, from risk and demand model building to natural language analysis of data. It builds automated, transparent risk and demand models and analyzes rate filings, experience data and reserving diagnostics, while actuaries select the models, sign off the rates and own the professional judgment.

Deployments
9 public, best grade B
Reported productivity gain
5x
Generali France, organization claim
Cross industryBanking

AI for legacy code modernization

AI for legacy code modernization reads old code such as COBOL and explains what each program does. It also works on languages like PL/I or old Java, mapping each program's data flows and dependencies, drafting the equivalent modern code or specification, and generating the regression tests needed to prove the new system behaves like the old one.

Deployments
7 public, best grade B
Reported cycle time reduction
about 50%
Google, organization claim
Technology and softwareCross industry

AI for product feedback and bug report triage

AI bug report triage is AI that reads incoming bug reports, crash logs and product feedback, and classifies each item for engineering teams. It gathers these from support tickets, app store reviews and error monitoring tools, then sorts them by severity, component and likely duplicate before routing each to the right team. For well specified defects, it drafts a starting code change or reproduction steps for an engineer to review.

Deployments
2 public, best grade C
Reported accuracy
90%
Gelato, vendor claim
Cross industryTechnology and software

AI for software vulnerability triage and remediation

AI vulnerability remediation is AI that takes security findings from scanners, fuzzers and bug reports and turns the real ones into a drafted code fix for developers. It filters out duplicates and false positives, reproduces and ranks the findings, and drafts a fix with a test for each, which a developer reviews and merges through the normal change process.

Deployments
6 public, best grade B
Reported automation rate
about 70%
AMD, vendor claim
Cross industryBanking

Governed text to SQL analytics assistant

A governed text to SQL analytics assistant turns a business user's plain language question into a query against governed data. It runs the query under that user's own data permissions and returns the table or chart together with the SQL and the tables used, so routine ad hoc questions no longer queue for the data team.

Deployments
6 public, best grade B
Autonomy
Assist

What the evidence says

Computed from the 44 public deployments behind these use cases. Numbers update with every checked record.

Benchmarks with at least 3 pooled values

Benchmarks across Code generation use cases
KPIMedianReported rangeData pointsClaimed by
Productivity gain25%
8.7% to 90%
Not pooled: up to 30%
5plus 1 up to2 organization, 3 vendor
Industries these use cases also serve
Business functions
Deployments by stage
  • Pilot
    2
  • Production
    33
  • Scaled
    9
Public deployments by region
  • North America
    18
  • Global
    12
  • Europe
    10
  • Asia Pacific
    3
  • Middle East
    1

Organizations with a public deployment

  • AMD
  • ANZ
  • AXA Spain
  • Accelerant Holdings
  • Accenture
  • Airbnb
  • Amazon
  • Anaconda
  • Bank of America
  • Bayer
  • Bridgestone Americas
  • CME Group
  • CWT
  • Canal Insurance Company
  • Canopius Group
  • Cathay Pacific
  • CircleCI
  • Citi
  • Coinbase
  • Duolingo
  • Europ Assistance
  • Gelato
  • Generali France
  • Google
  • Hitachi, Ltd.
  • Kinsale Capital Group
  • Labelbox
  • LinkedIn
  • MAIF
  • Mapbox
  • Meta
  • Morgan Stanley
  • National Renewable Energy Laboratory
  • PatientPoint
  • Regnology
  • Thomson Reuters
  • Toyota Motor Europe
  • U.S. Bank
  • Uber Technologies
  • United Rentals
  • Wakam
  • monday.com

Explore the library

All AI use cases

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State of AI Use Cases

Aggregate findings across every record.

KPI benchmarks

Definitions and reported values per KPI.

Methodology

How every record is verified and graded.