Using Generative AI in AI: Disrupting Industries | Sachin Dev Duggal

The Emergence of Generative AI

In a nutshell, the adoption of generative AI is growing exponentially due to better algorithms, more powerful computers, and larger datasets. In fact, according to a McKinsey survey, 65% of organizations use generative AI regularly in one or another business function; that’s significant growth compared to previous years. This surge shows a broader understanding of the potential of generative AI, from creativity enhancement in marketing to product development streamlining.

Generative AI's capabilities extend beyond simple content creation; it can produce complex outputs such as code, images, and music. This versatility makes it an invaluable tool in the entertainment and software engineering sectors. For instance, Builder.ai, co-founded by Sachin Dev Duggal, has transformed software development with its AI companion, Natasha, the world’s first AI product manager. Natasha interprets customer requirements, generates user stories and code, and manages projects with unparalleled transparency and consistency, compressing weeks of work into hours.

Problems and Contemplations

Despite its benefits, generative AI adoption comes with its own set of challenges. Organizations must address data quality, ethical, and governance questions as they adopt this technology. Generative AI’s effectiveness depends on the data quality used in training it. Inaccurate outputs can arise from using low-quality information, which is very dangerous in health care or banking sectors.

Additionally, there is growing concern over job displacement due to automation by generative AI systems. Although some roles may no longer be relevant, Sachin Dev Duggal believes that generative AI will create new jobs, especially in AI training and supervision areas. Companies need to reskill their workforce so that employees can thrive in an AI-enhanced environment.