Generative AI, also known as chatbots, is stirring up a lot of discussion in India. While there are risks associated with data, privacy, and security, industry leaders believe that generative AI offers more opportunities than risks. Its true potential to enhance productivity, creativity, efficiency, and communication is yet to be fully explored.
Vic Gupta, Chief Technology Officer at Coforge, stated that generative AI, particularly large language models (LLMs), has attracted significant interest and can augment human creativity and ingenuity. In anticipation of the need to adapt and empower the workforce with the necessary skills and tools, Coforge has developed internal learning paths and curriculum.
Coforge has partnered with Microsoft, as their investments in OpenAI align perfectly with their goals. They have integrated the public version of OpenAI into their Intelligent AI Platform, Quasar, enabling them to utilize ChatGPT APIs. This integration facilitates tasks such as data summarization, classification, and segmentation.
It is essential to understand that generative AI encompasses more than just ChatGPT. Anil Kaul, Chief AI Officer at Infogain, explained that algorithms like DALL-E can generate images based on given text prompts. GenAI has numerous potential applications across various sectors. For instance, a portfolio manager at a bank could use GenAI to generate investment advice.
Prabhakar Srinivasan, Director of Technology, AI/ML/Data Science at Synechron, highlighted the role of GenAI in areas such as customer relationship management (CRM) systems, technical support, cybersecurity, and finance. GenAI can assist in summarizing conversation transcripts, finding resolutions to technical issues, and detecting anomalies in transactions or network traffic. Srinivasan emphasized that GenAI augments human experts and acts as a co-pilot.
While generative AI offers many benefits, there are also challenges. Artificial Intelligence hallucinations occur when systems generate responses without completely understanding or misinterpreting questions, leading to incorrect information. Additionally, generative AI algorithms have limited information and struggle with new or unfamiliar data, lacking creativity and missing nuances. Jacob Joseph, VP-Data Science at CleverTap, mentioned the importance of human intervention to correct these limitations and highlighted concerns regarding legal, ethical, and biased applications.
Despite the challenges, generative AI shows promise, particularly in the field of marketing. Marketers can leverage generative AI to scale hyper-personalized content, address longstanding challenges, and unlock new possibilities. The adoption of generative AI tools is expected to increase as businesses recognize their potential to enhance productivity and innovation.
In conclusion, generative AI holds vast opportunities in India, although risks related to data, privacy, and security must be addressed. By leveraging generative AI responsibly and with human validation, businesses can benefit from its potential to enhance productivity, creativity, and efficiency across various industries.
