By Ramprakash Ramamoorthy, Director of AI Research, Zoho Corp.
From its origins as a theoretical concept in the mid-20th century to its current pervasive presence in our daily lives, artificial intelligence (AI) has undergone a tremendous transformation. From rudimentary rule-based systems to sophisticated algorithms capable of learning, adapting, and even creating, AI continues to evolve with every passing day. This evolution, fuelled by exponential increases in computing power, the availability of huge datasets, and algorithmic advancements, has not only revolutionised industries but also begun to reshape the business landscape as a whole. Here’s a look at how AI is breaking boundaries for businesses:
Generative AI goes mainstream
Generative AI has made significant strides, transitioning from being a niche technology primarily associated with creative fields like content generation and design to a mainstream tool with widespread applications across sectors such as customer service, healthcare, education, and beyond. In healthcare, for instance, GenAI is today used to create personalised treatment plans, generate synthetic medical data for research, and enhance diagnostic accuracy through advanced image and data analysis. Besides, GenAI is also available in widely used software suites such as office productivity tools, CRM solutions, and development platforms, helping foster collaboration and productivity, automate repetitive tasks, and improve decision-making.
End user adoption of GenAI also saw a steep climb with individuals increasingly taking to GenAI for knowledge retrieval, much like a search engine but with the added capability of synthesising information, offering concise summaries, and creating detailed reports. While search engines still dominate the market, there is a noticeable trend toward integrating GenAI capabilities with traditional search to enhance user experiences. This hybrid approach combines the strengths of AI and conventional search algorithms to create more intelligent and context-aware search functionalities.
Agent-based AI systems: The future of autonomous collaboration
Another key AI development has been the rise of multi-agent AI systems, where multiple specialised AI agents collaborate to handle complex workflows. These systems enable different AI agents to work together, each focusing on a specific function or task, yet coordinating to achieve a larger goal. Agent-based AI has become instrumental in the enterprise space, helping streamline operations that require coordination across departments.
Take a large-scale manufacturing enterprise as an example; multi-agent specialised AI systems can enable supply chain optimisation through numerous agents managing different aspects. A demand forecasting agent, for instance, can learn from historical sales data and other factors to predict future product needs and share the demand estimate figures with production planning agents. This is one use case; there are millions more. Agent-based systems represent a shift toward more autonomous, context-aware AI applications that can adapt to ever-changing business environments.
AI democratisation through open source models
Open-source LLMs have gained significant traction, particularly in developing nations and smaller companies, making advanced AI capabilities more accessible than ever. The growing number of open-source models on marketplace platforms like Hugging Face has lowered barriers to entry for startups and research institutions that may not have the infrastructure to build large-scale AI systems from scratch. This opens up new opportunities for innovation and problem-solving, with AI applications being customised to address local challenges in emerging nations, such as healthcare accessibility or regional language support.
Meanwhile, efforts from global tech companies to localise AI tools for regional languages have been a major step forward in bridging the digital divide. In India, for example, AI tools are being increasingly tailored to support languages like Hindi, Tamil, and Telugu, helping people from diverse linguistic backgrounds harness the power of AI.
India’s leap in AI
India has seen significant AI development over the years, thanks to strong government support, private sector investment, and academia-industry collaboration. One of the most notable moves was the government’s approval of a ₹990 crore budget for establishing three AI Centres of Excellence (CoEs). This initiative aims to enhance India’s AI R&D capabilities, ensuring that the country plays a key role in global AI innovation. The CoEs will focus on developing AI models and solutions for healthcare, agriculture, and sustainable cities.
Furthermore, India is positioning itself as a strong contender in the global AI race, with several homegrown startups emerging in sectors like fintech, healthcare, and education, contributing to both economic growth and social development.
Warming up to AI regulations
As AI technologies become more embedded in our daily lives, the need for responsible AI governance has grown more urgent. While comprehensive regulatory frameworks have not been fully enacted yet, the growing momentum towards AI governance is a positive sign that policymakers are taking AI risks seriously.
Governments worldwide—particularly in the US and Europe—introduced draft bills aimed at ensuring ethical AI development. The proposed regulations majorly focus on algorithmic accountability, data privacy, and transparency. Besides, more and more governments are also piloting AI sandboxes, which are controlled environments where AI regulations can be tested in real-world scenarios before they are fully implemented.
The Future of AI
AI will continue to be a transformative force. The developments so far have set the stage for even more profound changes in 2025 and the coming years, such as a more inclusive and responsible AI-powered future. The technology will no doubt be a game-changer across industries, offering new opportunities for growth, innovation, and efficiency.