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Next steps - AWS Prescriptive Guidance

Next steps

This strategic document explores how generative AI influences each layer of the application development and maintenance (ADM) operating model. It describes how potential benefits can be achieved such as increased development velocity, reduced production defects, and improved customer satisfaction scores. To begin your organization's AI-powered software development lifecycle (SDLC) journey and implement its target operating model for next generation ADM, use the following steps.

Successful AI integration requires balancing AI capabilities with human expertise. This balance drives innovation, efficiency, and competitive advantage throughout your organization's SDLC processes and ADM practices. By following these steps, you can position your organization at the forefront of AI-augmented software development. This approach drives significant business value and enhances your competitive edge in the industry.

Step 1: Conduct a readiness assessment

Use the AI-Powered Software Development Assessment (AISDLC - V1.0) in the AWS Assessment Tool to evaluate your current SDLC capabilities and the readiness of your current ADM operating model. This assessment can help you:

  • Identify strengths and improvement areas in your existing SDLC processes and ADM practices.

  • Pinpoint areas where AI can have the most significant impact to your business.

  • Prioritize remediation activities and create an implementation roadmap.

Step 2: Build foundational capabilities

To understand and help build the foundational capabilities in your SDLC with generative AI, see Accelerating software development lifecycles on AWS with generative AI. This strategic document provides AWS architecture best practices and can help you with the following tasks to implement your roadmap:

  • Establish a solid base for AI integration.

  • Align your processes with industry best practices.

  • Prepare your teams for AI-augmented development.

Step 3: Implement the phased approach

To implement an ADM target operating model, refer to the roadmap that encompasses all phases from initial quick wins to full AI integration. Make use of the sample framework and implementation checklist.

Success stories from early adopters demonstrate the transformative potential of AI in application development and maintenance.