Revolutionising Industries with Cloud and AI: Key Takeaways from Industry Thought Leaders

Revolutionising Industries with Cloud and AI: Key Takeaways from Industry Thought Leaders

This is undoubtedly the age of AI. With the explosion of generative AI tools answering to several use cases, AI is making significant inroads into solving some rather tricky business problems, and doing it faster, and more consistently. AI models, the less talked about cousin to generative AI tools, have quietly revolutionised the way businesses use analytics and are enabling stronger decision making than ever before.

Having said that, AI, particularly generative AI is brand new. It remains to be seen how this technology will evolve, what the problems are likely to be, and how it will shape businesses in the decades to come. To navigate this as yet uncharted landscape, Google Cloud and Persistent Systems, in association with Moneycontrol, are bringing together thought leaders from diverse industries to explore the pivotal role of cloud adoption in reshaping modern businesses.

The second Leaders Circle brought Persistent's Associate Vice President, Shantanu Ghosh and Google India's Head of Customer Engineering – Digital Natives, Debasis Bhattacharya together with Edul Patel, CEO & Co-Founder, Mudrex; Avijeet Singh, Head of Artificial Intelligence, Arya.ag

Karthik Shashidhar, Senior Vice President and Head, Analytics, Business Intelligence and Data Science, Delhivery Pvt. Ltd; Pramod Agrawal, Chief Technology Officer, IBSFINtech; Amit Dixit, Chief Technology Officer, ZoloStays Property Solutions; Rahul Shukla, CTO, M.Fine; Praveen Prakash, Director Of Engineering, TrusTrace and Satyapal Sharma, Director of Engineering, ALYF, to discuss the Power of AI in Transforming Industries. The session was moderated by News18's Paromita Chatterjee.

Karthik Shashidhar kicked off the discussion by acknowledging the particular FOMO that Digital Native businesses face - to collect, or not to collect data. Data being the fuel that drives the development of machine learning models, the more data, the better. Having said that, it is important to break out of the old ways of thinking in silos and instead look at creative ways to leverage AI.

Edul Patel felt that one of the biggest advantages of AI models is their ability to filter signals from noise. All of us are drowning in data and information, and AI models can help users, particularly in the context of Mudrex, identify the information that is relevant to them, and also make it easier for them to recognise when something is true, and when it is fake news. Mudrex's Satoshi GPT chatbot helps users do just that, and it does so in over 40 dialects, making user adoption easier.

According to Santanu Ghosh, the beauty of combining Cloud and AI is that they combine the ability to scale with the computational power that AI needs. AI was invented over 70 years ago, but it wasn't until it combined with the scalability of cloud that businesses were able to effectively leverage AI to gain competitive advantages.

For Pramod Agarwal, the transformative power of AI comes from allowing businesses to interact with their data in more intuitive ways. One no longer needs to wait for detailed data analysis, and this is invaluable when it comes to strategic evaluations of one's goals and business planning. Debasis also built on the advantage that AI models bring to compressing timelines fornew builds by leveraging pre-existing AI models, including LLMs. In this way, these technologies play the role of accelerator, allowing businesses to go to market with new offerings much faster, without the cost of expensive AI/ML engineers and specialists.

Satyapal Sharma, on the other hand, expressed his delight with the implications of generative AI in the real estate space where buyers will now be able to visualise the end product early enough in the project when prices are low. This opens up several avenues for both buyers and realtors to make the most of new construction projects.

When it comes to MFine, the problem for Rahul Shukla is disambiguation. In his line of work, when he's dealing with people who are ill, and often confused, there is a need to zero down on the customer problem even when the customer isn't being very clear about it. Often, customers are only able to talk about symptoms, and may leave key information out, which the chatbot needs to dig into with the right questions.

Praveen Prakash at TrusTrace mentioned that he is looking forward to the multipliers that AI will unlock as time goes by. For TrusTrace, which needs to bring in traceability for the supply chain, AI speeds up the digitization of brands' supply chain footprint, thereby enabling greater transparency, and the ability to mitigate risks even in highly complex and involved supply chains.

For Amit Dixit, time is indeed money, particularly when it comes to startups. He loves how several traditional "vanilla" use cases are already serviced by existing AI models. Businesses can leverage these vanilla models to free up resources who can then be redeployed into areas that are more complex. Moreover, this has an enormous implication on costs - using existing AI models is often far more cost effective.

The conversation also covered key areas like data privacy concerns, cost implications, balancing ROI with TCO, data security concerns, concerns around using customer data to train LLMs and AI models and much more. You can watch the entire discussion here. For more Leaders Circles,stay tuned.

Moneycontrol journalists were not involved in the creation of the article.