Why India Inc is Slow to Adopt AI Technology
Indian companies are showing interest in exploring AI deployment, but many projects remain stuck in the pilot stage. There is a hesitancy to fully embrace AI due to various concerns and challenges.
At GyanDhan, a non-banking financial company specializing in education loans, the use of the AI tool ChatGPT led to a significant increase in content output. Co-founder and CEO Ankit Mehra praises AI tools like ChatGPT for their ability to generate text in response to prompts. However, widespread deployment faces obstacles such as pricing issues, the generation of inaccurate content, and ethical and privacy considerations.
Mehra highlights the importance of addressing bias in AI models, citing instances where limited datasets led to errors. Despite these challenges, the adoption of large language models (LLMs) like ChatGPT, Gemini from Google, and Copilot from Microsoft is on the rise.
“Bias is a major concern; the datasets used to train these AI models are limited and can throw potential error,” Mehra explains.
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Privacy Concerns and Caution
Privacy emerges as a major issue in the use of commercial AI tools. Companies like GyanDhan are cautious about analyzing proprietary data with enterprise LLMs. Instead, they are developing their own LLMs using open-source models to ensure data security.
While fintech companies seem ideal for rapid AI adoption, the reality is more complex. Despite the hype surrounding AI tools, many companies, including payments banks and telecommunications firms, have limited AI deployment. The slow progress is attributed to factors such as exaggerated expectations and the need for further clarity on data protection laws.
A recent IBM study reveals that although a significant percentage of Indian IT professionals are exploring AI deployment, most projects remain at the pilot stage. The focus of tech firms is primarily on research, training, and developing proprietary LLMs. Challenges such as bias, lack of expertise, ethical concerns, and data provenance issues hinder widespread adoption of enterprise LLMs.
IT vs. Non-IT Use of AI
Industry experts suggest that India is at the early stages of AI adoption, with enterprises primarily using AI to enhance existing workflows through automation and chatbots. The transformation to AI-led enterprise applications is expected to take time, with larger IT firms currently experimenting with proof of concepts and upskilling their workforce in AI technologies.
Sachin Arora, Partner and Head of Lighthouse Data, AI, and Emerging Technologies at KPMG India, predicts that India’s engagement with AI will follow a pattern similar to previous tech cycles, with the IT sector leading in adoption while non-tech enterprises proceed cautiously.
The Value Proposition of AI
Tech giants like Microsoft are advocating for AI integration at the boardroom level, emphasizing the significant returns on investment. Puneet Chandok, President of Microsoft India and South Asia, highlights the positive impact of AI on customer satisfaction and business performance.
Abhigyan Modi, Senior Vice President at Adobe, stresses the importance of demonstrating the value that AI can bring to end-users. While AI is perceived as innovative, its true value lies in enhancing productivity and delivering tangible benefits.
In conclusion, the slow pace of AI adoption in Indian Inc. reflects a cautious approach driven by privacy concerns, ethical considerations, and the need for clear data protection regulations. As companies navigate the complexities of AI deployment, the focus remains on mitigating bias, upskilling the workforce, and demonstrating the tangible value that AI can offer.
