By Uma Ganesh
Agentic AI has been considered as one of the key trends shaping the generative AI space for 2025. Its applications are supporting workflows and enhancing productivity across various sectors. Agentic AI is a paradigm shift in the advanced AI system that is capable of acting on its own, adapting real time in dynamic environments and solving multi step problems.
Agentic AI is being implemented across various sectors. Autonomous vehicles like Tesla leverage it for navigation, traffic management and avoiding obstacles. In the financial services industry, algorithmic trading bots are able to make real-time decisions related to buying/selling stocks. Banks like HDFC Bank, SBI and others use agentic AI systems for autonomous fraud detection and prevention; loan providers such as Razorpay expedite loan approvals based on its knowledge of customer profiles and risk assessments.
Virtual assistants are getting smarter by the day, going beyond reactive responses to proactive searches and making recommendations. Netflix provides entertainment options based on its agentic AI’s capabilities to analyse past buying patterns and preferences of customers. Robotics has also got enriched with agentic AI. NASA’s Rovers and ISRO’s Pragyan navigate in space, gather and analyse data independently.
Amazon and Flipkart have been in the forefront of agentic AI making periodic product purchase recommendations based on various actions and preferences of the customers. Many learning platforms are able to enhance productivity by agentic AI grading assignments and making personalised recommendations to learners. Skills Alpha is an example of the agentic AI platform that is enabling the youth to identify their skill gaps and supports them with customised learning pathways and career opportunities. Renewable energy systems use agentic AI to autonomously monitor and optimise the performance of solar and wind energy installations.
Moving forward, agentic AI will drive further advancements for space missions, enabling collaboration between human and robots through swarm intelligence and even supporting elders through humanoid robots. Personalisation could get more and more granular with dynamic investment advice based on risk profiles of individuals and medical care and treatment based on edge data being tapped for lifestyle and genetics related factors. While the possibilities are exciting and vast, there are questions around ethics and regulatory frameworks.
All AI models are based on algorithms. How to ensure biases are minimised and equitable outcomes are derived is the question that continues to be a matter of concern. Prevention of misuse and loss of control of agentic AI systems need careful attention as experienced in Rohingya crisis, who were negatively impacted with social media algorithms spreading misinformation, forcing many to flee from Myanmar. Therefore, alongside technological advancements, it is important for stakeholders to urgently define the charter and ethical role of agentic AI.
The writer is chairperson, Global Talent Track.
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