AI in the software development lifecycle

The inherent complexity of the software development lifecycle (SDLC) means it gives rise to a multitude of potential pain points, from unclear requirements and scope creep to communication breakdowns and budget overruns. Some studies have revealed only 16% of projects are completed on time and within budget. This has led organizations to increasingly deploy AI to help accelerate and streamline the process. 

While utilizing AI for certain tasks in the SDLC is not new – with coding assistants for example helping to do some of the heavy lifting – it is the more recent advances in Agentic AI for software development that is proving to be the real game changer.  

Muthulakshmi Nellaiappan, head of AI and Data for Consumer Business Group at Tata Consultancy Services (TCS), has been working with AI for eight years and has seen rapid improvement in the last three years.  “Where its advances have really been felt is understanding and coding from human language instructions, bridging human knowledge with machine capabilities. Not knowing how to code does not prevent us from turning our ideas into working prototypes,” she said. It is this role as an ‘intelligent intermediary,’ which can understand and contextualize  between humans and technology has made a significant impact. 

Unlike previous iterations of AI which were limited in their scope and were harnessed largely for coding, GenAI assistants support broader aspects of the SDLC, providing tools for DevOps engineers, architects and test managers among others. 

Instead of merely functioning as tools for task execution, these technologies enhance the quality of output produced by human team members and empower them to make better informed decisions.  

Harnessing the power of AI with TCS 

TCS has developed a range of tools and services designed to help enterprise organizations fully leverage the latest advancements in AI technology.  

TCS GenAI SDLC Assistant can be utilized by everyone on the development team, providing tools to DevOps engineers, architects and test managers among others. It supports the team to carry out tasks with contextualised knowledge, helping them make smarter decisions and build quality content for artifacts like user stories, architecture, design documents, code, and test cases for application changes.  

While TCS’ AI Catapult Forward provides an integrated platform hosted on Microsoft Azure Marketplace, which can be used in various phases of the cycle, it enables the entire development team to work on a single platform together by sharing prompts and artifacts. 

Integration is essential  

But despite its advances, AI is not a silver bullet and must be properly integrated correctly into an organisation if its benefits are to be fully realised. Muthulakshmi said: “AI models and tools can save time, improve project management, and increase productivity; however, both explicit and tacit knowledge still reside within the organization. It’s important to assemble and manage organizational knowledge to effectively integrate AI into software development.” 

Combining people with technology is a crucial component of realising the complete advantages of AI. TCS can help organisations integrate AI effectively to harness its full potential.  

To learn more, visit TCS and Microsoft Cloud: Driving Business Transformation