Software developers worldwide are increasingly turning to generative artificial intelligence (AI) text-to-code tools to streamline their workflows and boost productivity. Tools such as IBM Codenet, GitHub CoPilot, Amazon's Code Whisperer, StarCoder by ServiceNow, and Hugging Face are gaining popularity, with claims of increasing efficiency by up to 50%. These Gen AI models can swiftly generate code from simple text prompts, accelerating the development process by 55% and ensuring code quality across various programming languages, including C++, Java, Python, and more.

According to Google Trends, searches for GitHub Copilot have surged tenfold in the past year alone, with over 1.3 million paid subscribers globally, including major Indian IT firms like Tata Consultancy Services, Infosys, and HCLTech. ServiceNow reports a remarkable 52% increase in developer productivity attributed to its text-to-code model. Sumeet Mathur, senior vice-president and MD of ServiceNow India Technology and Business Center, highlights how generative AI within the Now Platform converts text into high-quality code suggestions, fostering collaborative review and implementation processes.

While these tools promise significant productivity gains, their widespread adoption by major IT companies remains experimental. Concerns about code correctness and security persist, prompting cautious deployment strategies. Despite these challenges, industry experts project a rapid uptake of AI code assistants, with Gartner estimating that 65-75% of developers within IT organizations are already leveraging these tools. As Prashanth Kaddi, Partner at Deloitte India, notes, the integration of AI in technical artifacts necessitates transparency and adherence to security protocols, ensuring a seamless transition to this innovative approach to coding.