100% TEAM ADOPTION AND 2X AI MATURITY FOR A LEADING AUTOMOTIVE RETAIL GROUP

The initiative achieved 100% team adoption, nearly doubled AI maturity from 33 to approximately 65 out of 100, and enabled AI to support 80% of the development workflow through six practical use cases.

INTRODUCTION

AI adoption creates greater impact when it becomes part of how teams work every day, rather than being limited to isolated tools or experiments.

A leading automotive company saw an opportunity to increase AI adoption while its data team worked on a complex modernization initiative, reverse-engineering and migrating data from a legacy platform to a modern data environment.

CI&T introduced six practical AI use cases across the development lifecycle, supporting activities from story creation and code review to testing, deployment, and documentation.

Powered by CI&T Flow, AI capabilities were embedded into day-to-day engineering workflows, helping the team increase adoption, automate repetitive activities, and build greater confidence in using AI across delivery.

The initiative achieved 100% team adoption, increased AI maturity from 33 to approximately 65 out of 100, and enabled AI to support 80% of the development workflow.

THE CHALLENGE: MODERNIZING DATA WHILE BUILDING AI READINESS

A critical data modernization initiative required the team to reverse-engineer and migrate legacy data while maintaining delivery quality. At the same time, AI adoption was still limited, creating an opportunity to embed AI into everyday engineering workflows and increase team maturity.

Complex Data Modernization

The data team was responsible for a high-stakes modernization initiative involving the reverse engineering and migration of data from a legacy platform to a modern data environment.

The project was critical to rebuilding client trust and required teams to maintain quality throughout the migration.

Building AI Maturity

AI was not yet consistently embedded into day-to-day engineering activities. The team needed to move beyond occasional AI use and establish more mature habits across its development workflow.

Increasing Productivity Across Delivery

Activities such as code review, story creation, testing, work item management, data migration, and release documentation created opportunities to reduce manual effort through AI.

THE SOLUTION

CI&T introduced six AI-powered use cases designed around real activities already performed by the engineering team.

Instead of treating AI adoption as a separate initiative, the approach integrated AI directly into existing development workflows, helping teams build new habits while delivering ongoing work.

AI-Assisted Development and Code Review

AI supported code review by analyzing pull requests and identifying issues by severity before human review.
It also helped generate development stories directly from design documents, reducing manual preparation and helping teams move more efficiently into implementation.

Automated Quality and Testing

AI generated and scored test cases as part of the delivery pipeline, bringing automated quality activities closer to development.

This helped teams integrate testing into their day-to-day workflow rather than treating it as a separate step.

Automated Data Migration

An AI-powered stored procedure converter automated the migration of stored procedures from the legacy data platform to the new environment.

This supported the broader modernization initiative while reducing repetitive manual conversion work.

Simplified Engineering Operations

AI capabilities also supported work item management directly within the development environment and automated change request documentation.

Automating change request documentation alone saved approximately four hours per release cycle.

THE IMPACT

The initiative increased AI adoption and expanded its role across the engineering workflow.

FULL TEAM ADOPTION

100%

team adoption

AI incorporated into daily engineering activities

Greater use of AI beyond isolated or ad hoc interactions

HIGHER AI MATURITY

AI maturity increased from 33 to approximately 65 out of 100

Team progressed from a beginner to an intermediate maturity level

AI usage increased from approximately 1x to 2x maturity within four weeks

LOWER COSAI ACROSS THE DEVELOPMENT WORKFLOW

80%

of the development workflow supported by AI

Six AI use cases supporting activities from story creation and development to testing and deployment

AI embedded into existing engineering workflows

REDUCED MANUAL EFFORT

Automated code review before human validation

AI-generated development stories and test cases

Automated stored procedure migration

Approximately four hours saved per release cycle through automated change request documentation

TECHNOLOGIES USED

CI&T FLOW

CI&T Flow Enterprise AI Management System supported the integration of AI capabilities into day-to-day engineering workflows, helping the team increase AI adoption, automate development activities, and improve AI maturity across the delivery lifecycle.

DEV SUPPORT

AI capabilities supported pull request analysis and generated development stories from design documentation, reducing manual effort before and during implementation.

AI TESTING

AI generated and evaluated test cases within the delivery pipeline, helping integrate quality activities more directly into software development.

DATA
SHIFT

AI automated the conversion of stored procedures from the legacy data platform to the new environment, supporting the broader data modernization initiative.

WORK SUPPORT

AI supported work item management and change request documentation within existing engineering tools, reducing repetitive administrative work throughout the development process.