GenAI is shaping the future
It is rightly said, 'the true power of Generative AI (GenAI) lies in its ability to not just predict outcomes, but to generate new possibilities based on existing data'. Corporate Citizen talks to Sandeep Agarwal, MD and Global CTO, Visionet, to know more about the power of GenAI, how it is generating new possibilities, its trends, and innovations
Corporate Citizen: What is GenAI, and why has it got so much importance and relevance?
Sandeep Agarwal: Unlike traditional AI and machine learning, which recognise patterns in data to make predictions, GenAI goes further by creating new data with similar characteristics. GenAI is gaining importance due to its potential to drive innovation and efficiency across various industries. Core technologies such as Digital Twins, Large Language models (LLMs), and Synthetic Data Generation are used widely. Businesses leverage GenAI to boost productivity, inspire innovation, and stay competitive in a rapidly evolving market. At Visionet, we use AI-driven solutions to optimise supply chain management, automate data processing, and personalise customer interactions globally. These applications enhance operational efficiency and help our customers remain competitive. The buzz around GenAI will continue to grow as more companies adopt it and find new use cases, integrating the technology into everyday processes.
CC: What are the most exciting trends in GenAI right now?
GenAI has already reached its “hobbyist” phase (experimental phase). And, as this progresses, the capabilities of these GenAI models would reveal themselves slowly and steadily. Here are some of the trends:
Multimodal AI
It represents a departure from traditional AI approaches focused on optimising performance within narrow domains, instead embracing diverse data inputs.
Integration of Small(er) Language Models (SLMs)
This process is gaining momentum among tech giants and startups alike. This is because, training smaller models on more data, yields better performance than training larger models on fewer data. Moreover, smaller models can run at lower costs. In addition, SLMs make AI more explainable
GenAI as a Service (AIaaS)
It is meeting a rising demand for AI capabilities in the workplace. For instance, in a survey, 45% of respondents believe GenAI technologies make their job easier, and 27% feel that these tools enable a focus on more critical tasks. However, while incorporating, enterprises aim to harness the power of AI without the burden of extensive infrastructure and expertise. This is where AI as a Service (AIaaS) platforms can help. This cloud-based delivery model makes access to AI features and functionalities widespread, helping businesses use the technology for business growth, similar to how we, at Visionet, support SMEs and startups.
In addition, customised local models represent another emerging trend in AI adoption. These custom AI models are trained on their proprietary data and fine-tuned to perform their specific tasks. Legal, finance, and healthcare are the prime examples of industries that can benefit from these local models.
CC: How is GenAI being used across different industries in India?
The integration of GenAI across various sectors in India highlights its transformative impact. A survey predicts that GenAI could contribute over $350 billion to India’s GDP. In retail, 71% of retailers see the need for GenAI as their online businesses expand. The retail AI market, valued at $6 billion in 2022, is expected to grow over 30% annually by 2032, driven by solution providers like Visionet.
We encourage the adoption of AI-driven solutions to enhance customer engagement, optimise supply chain management, and improve operational efficiency in retail. In banking and finance, GenAI is set to enable savings of over $487 billion globally by the end of 2024. These savings come from better fraud detection, personalised customer interactions via chatbots, and improved risk management through predictive analytics.
In the biotech industry, AI is expected to generate around $19.3 billion in revenues globally by 2026. This growth is driven by AI's ability to speed up drug discovery, optimise clinical trials, and improve efficiency in biotech companies. These advancements show how GenAI is driving economic growth and revolutionising operations across key sectors.
"GenAI is gaining importance due to its potential to drive innovation and efficiency across various industries. Businesses leverage GenAI to boost productivity, inspire innovation, and stay competitive in a rapidly evolving market"
-Sandeep Agarwal
CC: What role do you see GenAI playing in the future of industries like manufacturing, banking, and retail?
GenAI's transformative impact on manufacturing, banking, and retail is evolving amidst technological advancements. By 2032, the global market for GenAI in manufacturing is anticipated to grow to USD 7 billion, optimising operations, maintenance, and supply chains for enhanced efficiency and sustainability.
In India's BFSI sector, GenAI could propel it to become the world's third-largest domestic banking market by 2050, boosting economic growth. AI models will enable banks to improve decision-making, detect anomalies in real-time, and predict financial risks through simulated data analysis.
In retail, AI-driven solutions will cater to customer demands, refine shopping experiences, and streamline supply chain processes, with predictions indicating that half of retailers will integrate AI for personalised recommendations, boosting engagement and conversion rates significantly by 2028. These trends underscore GenAI's potential to revolutionise diverse industries through innovation and operational excellence.
CC: What are the biggest challenges faced by GenAI today and how can one address the ethical concerns associated with GenAI, such as deep fakes and misinformation?
Based on our observation, businesses face three main challenges with GenAI integration: a limited skilled workforce, high implementation costs, and data security concerns. Globally, there will be 97 million new AI and machine learning roles by 2025, creating an urgent need for upskilling in the tech sector. However, there is still a shortage of skilled AI professionals in India. Additionally, 53% of companies see high costs as a barrier to AI implementation due to the significant investment required for infrastructure, training, and business restructuring. These costs can be prohibitive for SMEs or those with limited budgets. Moreover, 56% of businesses identify data security as a major challenge. Addressing ethical concerns, particularly related to misinformation, is crucial. Implementing robust verification mechanisms can help mitigate the spread of false information. Collaboration with researchers and industry experts, as well as advocating for ethical guidelines and standards, is essential.
CC: How do you see GenAI transforming business models and economic landscapes in India?
In 2022, GenAI gained widespread attention and is now being integrated into businesses. By 2024, researchers and companies are working to make this technology a practical part of everyday life. It is estimated that by 2030, the global GenAI market will grow at a CAGR of 36.5%. GenAI can boost India's GDP, create new jobs, and drive sectoral impacts. It will foster digital transformation, supported by investments in AI infrastructure and regulations to ensure ethical use.
CC: What are your predictions for the future of GenAI?
GenAI will continue to make huge strides in the coming year. We believe that, in the coming years, most of the GenAI models that enterprises use will be specific to either an industry or a business function. The trends showcase that in conjunction with the increased availability of high-performing and commercially usable open-source LLMs, there is also an appetite for domain-specific models. These domain models, though smaller, would lower the risks associated with general-purpose models. Also, in the coming years we expect an ethical development within the GenAI space, focussing on addressing bias, privacy, and misinformation. To some extent, companies are already grappling with the implications of oversight with respect to the use of GenAI and are taking active measures to avoid misuse of AI. But the onus cannot just be on tech companies, we also need formal regulations that can put a stop to future misuse.