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Tech Advancement Propels India to Global AI Leadership: Driven by Innovation, Oversight & Enterprise Excellence
The year 2025 was a fruitful year for the Indian tech ecosystem, helping unlock the deep potential of AI in the business landscape. AI has more than evolved to meet the diverse and dynamic needs of Indian businesses as well as deliver unique capabilities.
Affordability, customisation, sustainability and efficiency were some of the key focus areas of AI businesses in 2025. Considering the environmental consequences of AI systems, businesses are beginning to look at sustainable AI models while still providing hyper-personalised offerings that cater to specific business needs. On a promising note, complementing the rapid evolution of AI, Indian enterprises have been found stepping up their privacy practices. According to a study by Arion Research LLC, commissioned by Zoho, around 71% of Indian organisations have strengthened privacy measures after adopting AI.
Countries should take a page from Indian enterprise's commitment to improve their privacy framework and begin evaluating their privacy practices.
Building on this positive momentum, Indian businesses can further focus on the following areas in the coming year, to position the country as a global AI power:
Energy efficient and hyper-personalised models
There is an increased business value for enterprises to move beyond parameter-heavy AI models and begin exploring performance-optimised systems. Business can bank on energyefficient Large Language Models (LLMs) to address environmental concerns due to high energy consumption of AI training. LLMs trained on different sets of parameters also offer personalised applications depending on the business context.
Fine tuning an LLM is essential to tailor the model to specific business tasks. Instead of wasting huge amounts of computational energy in fine tuning an entire LLM, organisations can make use of methods like parameter-efficient tuning and Low-Rank Adaptation (LoRA) for specific tasks. Through this, businesses can utilise advanced AI capabilities in a cost-effective way.
Model distillation of LLMs into smaller, task-oriented systems, is also being widely utilised. This method helps retain the efficiency of the large foundation model while reducing operational costs and environmental impact of a large-scale AI operation.
As much as LLMs are powerful, their performances get capped after a certain level without the availability of new training data. Agentic AI, capable of integrating with databases and Application Programming Interfaces (APIs), can help counter this. Equipped to make autonomous and dynamic decisions, agents understand the nuance of a business and can provide specific solutions. This allows agents to adapt and personalise interactions, making them a huge success in areas like customer service, healthcare and education. This hyper-personalisation of AI is especially necessary for a country like India with a broad range of users. AI models trained in regional languages are now on the rise.
Making AI affordable
Startups, and Small and Medium businesses may be constrained in terms of budget, making AI adoption difficult. Modular AI systems provide custom solutions for specific business requirements while still being affordable and adaptable. Businesses can utilise AI components instead of relying on monolithic AI systems. Modular AI offerings also provide vertical-specific solutions, addressing sectors like finance, retail, healthcare and automobile.
Standardisation of APIs and communication protocols have really helped improve interoperability. Communication between multiple AI systems have been streamlined through this, allowing different business operations within a single organisation to work together seamlessly.
Edge AI and Instantaneous decision making
Around 71% of Indian organisations have strengthened privacy measures after adopting AI.
With Edge AI's ability to deliver insights instantaneously, applications requiring immediate decisions are now making use of the technology. Equipped with edge AI, devices including autonomous drones, predictive maintenance and medical imaging, can deliver faster insights while minimising latency. Edge AI is capable of powering even advanced systems like self-driving cars, autonomous robots and Internet of Things (IoT) devices.
AI-specific hardware, such as neuromorphic chips and Tensor Processing Units (TPUs), are only set to further augment this technology. Businesses can experience the speed of On-Device Intelligence with the added benefit of energy efficiency. This will inevitably pave the way for AI to permeate unexplored areas.
AI Value Strategy
The scope of AI in the business landscape is vast. Hyperpersonalisation has greatly enabled enterprises across diverse sectors to deliver tailored customer experiences. Fine tuning an entire LLM is computational and cost heavy so companies are countering it with energy-efficient LLMs and parameter-efficient tuning. Edge AI coupled with predictive maintenance powered by AI can help identify equipment issues before they escalate while expediting the turnaround time.
Scaling Intelligence
Countries should take a page from Indian enterprise's commitment to improve their privacy framework and begin evaluating their privacy practices. Privacy should be a long-term focus for all businesses. Unregulated use of AI could increase the rampancy of misinformation. Generative AI models are also not forgetful of any data that is shared with them. Information fed into AI models is irretrievable and permanently lost in a vast ocean of data. Without serious and sustained privacy practices, this could pose grave business risks.
As we continue unlocking the potential of AI, it is essential to be aware of the risks and maintain a firm oversight. Given the massive development we saw in 2025, it will be interesting to see how AI evolution continues playing out in India in 2026. Rapid technological advancements and Indian businesses leading the way for their peers in terms of privacy has propelled the country to the forefront of global AI leadership.
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Ramprakash Ramamoorthy
He leads the AI efforts for Zoho Corporation. He has been instrumental in setting up Zoho's AI platform from scratch. He comes with a rich 13+ years of experience in building AI for the enterprises at Zoho Corporation. Mr. Ramamoorthy is a passionate leader with a level-headed approach to emerging technologies.
Owned by: Institute of Directors, India
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