Business function

AI use cases for it and engineering

Software development, IT service management, infrastructure and data engineering.

Use cases: 16
Deployments: 109
Organizations: 100
Outcome disclosed: 73%

16 IT and engineering use cases

100 organizations in 20 countries run these use cases in public. 73% of those 109 deployments disclose a measurable outcome.

Telecommunications

Agentic AI for autonomous, intent based network operations

Autonomous network operations use AI agents that run closed loops over a telecom network, taking an intent from the operator and acting to meet it. For example, given a latency or availability target, the agents observe the network, diagnose deviations and execute corrective actions across radio, transport and core, within guardrails set by engineers and with human approval for major changes.

Deployments

10 public, best grade B

Reported cycle time reduction

at least 95%

Deutsche Telekom, organization claim

Cross industryTechnology and software

AI agent for cloud cost optimization and FinOps

An AI agent that continuously manages an organization's cloud spending to cut waste. It reads usage and billing data, uses machine learning to separate normal spend from waste, and either rightsizes resources and buys a mix of committed capacity matched to forecast usage on its own within set limits, or proposes higher risk changes for an engineer to approve.

Deployments

7 public, best grade C

Median cost reduction

50%

5 deployments, 1 "up to" value left out

Cross industryTechnology and software

AI agent for data quality monitoring and observability

AI data quality monitoring is an AI agent that watches data pipelines and tables continuously and flags anomalies before they reach a dashboard or a downstream model. It uses machine learning to learn the normal pattern of freshness, volume, schema and distribution for each one, and traces the lineage back to the change that caused an anomaly so an engineer can fix the source, not just the symptom.

Deployments

8 public, best grade C

Median time to repair reduction, vendor reported

20%

3 deployments

Cross industryBanking

AI agent for IT service desk resolution

An AI agent for IT service desk resolution takes the high volume IT support queue, resolves common requests and hands the rest to the right resolver group. It runs in Microsoft Teams, Slack or the intranet, covers requests such as password and MFA resets, account unlocks, VPN, device and software requests, and acts in the identity and IT service management systems, attaching the context when it hands a request on.

Deployments

9 public, best grade B

Median employee adoption

90%

3 deployments

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

Cross industryBanking

AI for IT incident triage and root cause analysis (AIOps)

AIOps incident triage is AI that turns a flood of monitoring alerts into one probable incident and routes it to the right team. It also proposes likely root causes and remediation from runbooks and past incidents, and drafts the stakeholder updates and the post incident review, while an engineer authorizes every change.

Deployments

9 public, best grade B

Median time to repair reduction

72%

5 deployments

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 industryHealthcare

AI for security alert triage and investigation in the SOC

Security alert triage and investigation is an AI agent in the security operations centre that picks up each new alert or user reported phishing email. It gathers the evidence from the SIEM, endpoint, identity and threat intelligence tools, gives a verdict with its reasoning and a draft incident summary, and closes clear false positives while an analyst approves every containment action.

Deployments

7 public, best grade B

Median productivity gain

60%

3 deployments

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 industryGovernment and public sector

AI for support knowledge article generation and maintenance

AI knowledge article generation is AI that drafts support knowledge base articles from resolved tickets, cases and conversations. It also detects questions the knowledge base does not answer and articles that are outdated or contradict each other, and proposes new or revised articles for a knowledge owner to review and publish.

Deployments

4 public, best grade B

Autonomy

Copilot

Cross industryBanking

AI for synthetic test data generation

Synthetic test data generation is AI that generates realistic synthetic datasets, such as customers, transactions, documents and conversations, without containing real personal data. The datasets keep the structure and statistical properties of production data, so teams can test software, train and validate models and run demos safely.

Deployments

7 public, best grade B

Reported cycle time reduction

75%

Patterson Dental, vendor claim

Cross industryBanking

AI system and model inventory with shadow AI discovery

An AI model inventory is a governed register of every AI system and model an organization builds, buys or uses, for risk and compliance teams. Each entry records the owner, purpose, data, risk tier and approval status, kept current by AI that discovers unregistered use, reads the documentation and assembles the evidence a board, auditor or supervisor asks for.

Deployments

7 public, best grade B

Autonomy

Copilot

Technology and softwareGovernment and public sector

AI that turns requirements into user stories, acceptance criteria and test cases

Requirements to test cases is AI that reads product requirements, specifications or recorded sessions and drafts structured user stories, acceptance criteria and test cases for QA engineers to review. It also checks the source for gaps, ambiguity and contradictions, drafts the cases in a format such as Gherkin, and traces each item back to the requirement it covers.

Deployments

6 public, best grade B

Reported cycle time reduction

67%

LTIMindtree, 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 109 public deployments behind these use cases. Numbers update with every checked record.

Benchmarks with at least 3 pooled values

Benchmarks across IT and engineering use cases
KPI	Median	Reported range	Data points	Claimed by
Productivity gain	46.2%	8.7% to 90% Not pooled: up to 30%	12plus 1 up to	3 organization, 9 vendor
Time to repair reduction	50%	17% to 95% Not pooled: up to 80%	9plus 1 up to	1 organization, 8 vendor
Accuracy	90%	42% to 98%	6	2 organization, 4 vendor
Cost reduction	50%	30% to 60% Not pooled: up to 70%	5plus 1 up to	2 organization, 3 vendor
Cycle time reduction	67%	40% to 95% Not pooled: up to 70%	5plus 1 up to	2 organization, 3 vendor
Automation rate	74% vendor reported	70% to 88%	3	3 vendor