How GenAI is Rewriting Business Strategies Across Sectors

Artificial intelligence (AI) has driven tech innovations for decades. Its India journey started in the early 2000s when algorithms were incorporated into computing hardware. By the 2010s, AI usage was more prevalent due to the rise of big data analytics and AR-VR applications.

When OpenAI launched its GenAI (generative AI) application, ChatGPT, in 2022, it was a giant leap towards human-like creativity, conversational power and deep analysis of data and industry trends. The markets are now flooded with GenAI tools, offering various enterprise-level solutions to maximise efficiency and optimise costs.

Industry experts say this is merely the beginning. The GenAI boom will transform all businesses by improving processes, enhancing customer experiences and redefining decision-making. According to a recent McKinsey Global Survey on AI, 65% of respondents said their organisations regularly use GenAI, nearly double the percentage from the previous survey conducted less than a year ago.

While GenAI can drive business growth, one has to deal with multiple risks like data breaches, deep fakes and biases. So, enterprises must craft a well-balanced AI strategy to reduce costs, create value and increase trust in organisations by mitigating those risks.

To explore it further, Inc42 and Oracle hosted the final edition of their two-part series titled Boardroom: Powering Data With AI. Held in Delhi on August 22, the roundtable brought together 10 tech leaders from diverse sectors (travel tech, healthtech, manufacturing, electric vehicles and more) and deep-dived into the theme – Unlocking Data & AI Potential: Charting a Path to Innovation and Growth.

Moderated by Sameer Dhanrajani, CEO at AIQRATE & 3AI, the session was attended by: 

• Sushan Rungta, CTO at Absolute
• Vivek Agarwal, cofounder & CTO, Square Yards
• Diwas Sharma, principal engineer, Fashinza
• Dr Shakti Goel, chief architect & data scientist, Yatra Online
• Shiva Singh, director (engineering) at Moglix
• Sanjeev Singh, head of technology & data, Gensol EV
• Pushkar Aditya, SVP (technology), Clovia
• Gaurav Bagga, SVP and head of engineering & product, Pristyn Care
• Saravanan Palanivel, VP (cloud engineering), Oracle India

A Deep Dive Into Industry Use Cases

Dhanrajani started the discussion by emphasising that AI-GenAI was not a sudden phenomenon but a long continuum. He referred to the evolving debate over human versus AI, questioning this new-age technology’s capabilities and potential.

“With machines growing smarter and stronger, a time will inevitably come when human creativity and ingenuity have to confront a stark reality. We have long anticipated the possibility of machines surpassing human abilities, but will that happen?” he pondered.

As the conversation unfolded, Dhanrajani delved into the widespread adoption and application of AI-GenAI across industries, assessing how deeply it would be embedded into modern businesses.

Shedding more light on industry use cases, Rungta of Absolute detailed how AI transformed the platform’s on-ground advisory services for farmers, resulting in speedy reach and significant cost-cutting.

“Earlier, we spent a lot of time and money reaching the farmers in person and helping them use our agronomic solutions. But now we integrate satellite images and weather data to offer AI-powered insights, which are accurate and time-critical,” he explained.

When it comes to agritech, time-sensitive information is critical, helping farmers cope with weather patterns, pest attacks, soil conditions, crop health monitoring and more in real time. As AI applications are now extensively used in various areas of farming, farmers can optimise their harvests and gain a competitive edge, pointed out Rungta.

The shift towards a tech-led approach at the grassroots is significant, given that India’s agriculture sector contributes 18.2% to the country’s GDP and employs nearly 45% of the workforce.

Yatra’s Shakti Goel, a tech veteran with more than two decades of experience, also highlighted the remarkable journey of AI, from Lotus spreadsheets to Oracle databases to the advent of GenAI. According to him, AI has long been a trusted tech tool supporting human decision-making. But its potential to revolutionise business strategies has not been fully realised until now.

He cited how Coca-Cola introduced its cherry flavour in the US, where IoT-enabled dispensers allowed customers to add the flavour to their drinks. More interestingly, the initiative was based on data analytics instead of an on-ground market survey.

Goel revealed an interesting use case when talking about Yatra’s AI journey. Digging into its hotel data, it realised that it was selling a significant chunk of Hilton bookings. But Yatra did it for third parties and not directly for Hilton. Armed with this insight, the company approached Hilton with a proposal to supercharge their partnership. 

Gaurav Bagga of Pristyn Care (a startup specialising in elective surgery) discussed how modern healthcare providers can leverage GenAI to improve patient experience.

“We use GenAI to analyse and improve how our care co-ordinators engage with patients. The data gathered from these interactions allows us to prioritise action items so that care coordinators can make informed decisions and deliver on their commitments,” he said. 

Balancing Risk, Cost And Innovation In The Era Of GenAI 

AI has immense potential to transform businesses. But it also comes with significant risks such as data breaches, hallucinations (inaccurate/misleading assumptions), biases and lack of compliance.

According to a 2024 Orca Security report, 58% of organisations store sensitive data in the cloud. This data could leak if used for AI-GenAI training or validation purposes, leading to a breach of confidentiality and other damaging consequences. Orca Security report 

So, how can businesses confidently adopt AI-GenAI, balancing growth and efficiency with security concerns?

“It is not a one-size-fits-all solution. A single large language model (LLM) may not suit every industry. To achieve higher accuracy, you need a customised model built on your data, rather than relying solely on generic models,” said Palanivel of Oracle India.

He also mentioned Oracle’s Retrieval-Augmented Generation (RAG) technology in this context, which enhances the accuracy and effectiveness of AI applications by integrating retrieval (of training data) and knowledge augmentation (without retraining) in a unified system. This mechanism helps mitigate risks like hallucination, misinformation and bias, which occur in purely generative models that cannot reference knowledge sources outside training. 

Other experts on the panel also voiced their concerns about open-source AI applications, trained on widely available data that may lack accuracy or a neutral, cognitive approach needed for reliable GenAI functions. Nevertheless, they have a cost advantage. Startups, for instance, may not find it feasible to build custom LLMs and must opt for pay-and-use models. 

It will take time to gain trust in these third-party systems. A TCS survey found that 59% of corporate functions have AI implementations in progress or completed these projects. However, only 20% of corporate leaders feel well-positioned to leverage AI to their strategic advantage. Cloud providers are stepping up data security, while businesses will increasingly depend on high-quality and customised data for enterprise usage. 

The big question remains, though: Will artificial intelligence outsmart humans? 

Until we get closer to creating artificial general intelligence that can function on a par with a human’s cognitive capabilities, the answer is – no. In the foreseeable future, the new technology will continue to complement human capabilities, but it will also redefine the future of jobs.

To begin with, AI-GenAI will enhance human productivity by automating repetitive and time-consuming tasks. Again, AI and deeptech will continue to create new opportunities, from prompt engineering and agent-specific expertise (think of Copilot skills) to AI advisory roles, LLM development and more, our panellists said. In essence, the future of work will be driven by the three A’s – AI, analytics and automation. So, enterprises and individuals must strategise and develop skills to meet the requirements of a new epoch.

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