LG CNS AI-DLC for Enterprise

Across the entire lifecycle, AI-DLC manages AI deliverable validation, compliance with quality standards, risk and issue management, change and configuration management, security and compliance governance, documentation, and traceability. Through this end-to-end governance, LG CNS AI-DLC enables a trusted AI-driven delivery model for enterprise environments.

**AI-DLC Lifecycle**

LG CNS AI-DLC supports the following lifecycle stages:

• Initialization :

The preparation stage for AI-driven delivery, covering organizational readiness, technical setup, and delivery environment configuration.

• Ideation :

The stage where business ideas are developed into concrete requirement candidates.

• Inception :

The stage where requirements are refined and transformed into actionable designs and delivery plans.

• Construction :

The stage where AI-driven design, implementation, testing, and validation are performed.

• Operation :

The stage focused on post-deployment operational stability and continuous improvement.

**Technical Architecture**

LG CNS AI-DLC is structured into three layers.

Layer 1: Core Workflow Backbone and Layer 2: Detail Rule Prompts operate on the foundation provided by AWS. On top of these layers, LG CNS applies an additional Override Layer to further enhance enterprise delivery execution.

The LG CNS Override Layer supplements key delivery capabilities, including effort estimation, test design, code review stages, project-specific environment configuration, business domain knowledge, pre-designed test cases, and operational rules such as preventing AI from arbitrarily generating code values, enforcing code quality reviews, and assessing impact across multiple repositories.

**Application Areas**

LG CNS applies AI-DLC across Application Management (AM), Service Management (SM), and Legacy Modernization (Migration) to provide a consistent AI-driven delivery framework from requirements definition to operational handover.

• AM: Application Management

In the Application Management domain, AI-DLC is applied to new system implementation and application development initiatives. It connects requirements, designs, and deliverables into a single integrated flow, converts the results into assets ready for operational handover, and verifies the quality of each deliverable through Review Gates to ensure a seamless transition to operations.

• SM: Service Management

In the Service Management domain, AI-DLC is applied to change requests for systems already in operation. It supports AI-driven change requirement analysis, impact assessment, and modification planning, while converting the outcomes into reusable assets. By generating requirement clarification questions and change planning assets simultaneously, AI-DLC helps reduce the effort required for change execution.

• Migration: Legacy Modernization

In the Legacy Modernization domain, AI-DLC is applied to modernization initiatives for legacy systems. It supports the entire modernization process, from reverse engineering-based legacy system analysis to transition planning, pattern-based conversion, and test asset generation.