Transforming application development and maintenance operating models on AWS with generative AI - AWS Prescriptive Guidance
Intended audienceObjectivesBenefits of integrating generative AI into ADM

Transforming application development and maintenance operating models on AWS with generative AI

Dhana Vadivelan, Amazon Web Services (AWS)

April 2025 (document history)

Organizations face unprecedented challenges in application development and maintenance (ADM) practices today. Generative AI is fundamentally changing how applications are built, designed, tested, documented, and deployed—transforming the entire software development lifecycle (SDLC).

ADM encompasses the complete application lifecycle from business requirements analysis through development and maintenance, representing a comprehensive practice of managing applications. The SDLC defines the structured methodology and phases for building software within this broader ADM framework.

To assist your organization's transformation journey to AI-powered ADM practices, this strategy document offers:

  • Comprehensive analysis of AI's impact on ADM, including operating model and role-specific changes

  • Strategies for enhancing organizational capabilities and addressing key challenges

  • A framework for building and implementing an AI-powered ADM operating model

  • A phased implementation approach to an AI-powered ADM operating model, from quick wins to full AI integration

Intended audience

This strategic document is recommended for the following audiences:

  • IT leaders, such as chief technology officers (CTOs), technical directors, technical leads, architects, and program managers

  • Business leaders, such as chief information officers (CIOs), chief data officers (CDOs), vice presidents (VPs) of product engineering, and VPs of business operations

Objectives

This strategy document can help your organization achieve the following objectives:

  • Examine your current ADM operating model for transition to the AI era.

  • Address the unique challenges of generative AI integration.

  • Implement a phased transformation strategy to integrate generative AI into your organization's ADM.

Benefits of integrating generative AI into ADM

For IT leaders, integrating generative AI into your organization's ADM can provide the following benefits to enhance your organization's capabilities:

  • Accelerate innovation cycles through rapid prototyping and responsive software development.

  • Automate routine tasks in architecture definition, code generation, and testing.

  • Enhance software quality and reliability, minimizing defects and mitigating risks.

  • Improve operational scalability by handling increased complexity and development volume.

For business leaders, integration of generative AI can deliver benefits that extend beyond technical improvements to create business value:

  • Deliver customer-centric applications faster, adapting quickly to market demands.

  • Gain competitive advantages by increasing operational efficiency with AI technologies.

  • Position your organization as a leader in AI-driven development, attracting top talent.

  • Achieve cost efficiency through improved productivity and optimized resource allocation.

Early adopters across industries are reaping the benefits from using AWS generative AI services in ADM:

  • Development speed – BlackBerry improved SDLC agility and quality with Amazon Q Developer.

  • Code generation – BT Group automated 12 percent of repetitive tasks using Amazon CodeWhisperer, which is becoming part of Amazon Q Developer.

  • Modernization – Novacomp used Amazon Q Developer to reduce a Java application modernization time from 3 weeks to 50 minutes.

  • Documentation – ADP used Amazon Q Developer to cut legacy system documentation time from weeks to less than a day.

  • Productivity – National Australia Bank used Amazon Q Developer to achieve 50 percent acceptance of AI-generated code suggestions.

  • Application modernization – Deloitte uses Amazon Q Developer to accelerate modernization phases, reducing project complexity and completion times. TCS used Amazon Q Developer to accelerate mainframe modernization, quickly analyzing and documenting legacy COBOL code.

  • Application migration – Cognizant uses Amazon Q Developer to automate complex migration processes, increasing speed and simplicity in transformation projects. Also using Amazon Q Developer, HCLTech employs AI agents for accelerating VMware, .NET, and mainframe workloads.

  • Application efficiency – IBM Consulting's AI-based SDLC solution on AWS Marketplace makes use of Amazon Bedrock to enhance efficiency and quality throughout the application lifecycle.