India's agentic AI revolution: 80% of businesses are making self-driving systems

Generative models were the first thing that got a lot of people interested in artificial intelligence (AI). These systems can learn from a lot of data and then create text, graphics, audio, and code. Their work is often quite brilliant, yet it is done in response to something. They wait for a prompt and then answer based on what they see. The usefulness is clear. But the person who uses it is still in charge. This issue is becoming clearer in the workplace.

An AI-powered customer service assistant could draft an email, a marketing tool could create attractive wording, or a legal team could use AI to shorten a contract. In each case, the system makes content but doesn't decide what happens next. As company demands develop more intricately, it becomes more and more vital to know the difference between aid and independence. This is when AI that can act on its own becomes important. 

From aid to being on your own

Agentic AI refers to systems that can act on their own. These technologies do more than just sort data or find solutions. They create plans, make choices, and perform their work with little support from others. They can notice what's going on around them, make plans, and learn from being criticised so they can do better next time. A generative model helps someone get a job done. An agentic system does the work for you. It works out what has to be done, chooses the best way to do it, and makes modifications as needed.

For instance, generative AI might put up a report about an incident in cybersecurity. An agentic system might identify weird things in network traffic, decide whether to escalate, isolate the affected systems, and activate reaction protocols. This kind of independence changes how businesses respond and how rapidly they do so.

India's agentic AI boom: Real numbers and effects

There is no doubt that things are moving forward in India. According to new data, more than 80% of Indian companies want to create autonomous agents. This shows a big move toward agentic AI. This is one of the greatest adoption rates in the world, making India a leader in the agentic AI revolution.

Infosys: Leading the way in automating software development

Infosys, a huge technology company in India, has achieved success from its internal agentic AI studies. Their self-driving systems have improved database code creation by 80-90%, API and microservices development by 60-70%, and the overall speed of software delivery cycles by a lot. These agents work on their own to figure out what needs to be done, write code, test apps, and even handle the deployment process with little help from people.

The Indian banking sector: A month-end reconciliation revolution

Several Indian banks have set up agentic systems that do more than two-thirds of their month-end reconciliation tasks, which used to be done by hand. These AI agents can work on more than one banking platform at the same time. They match records, find differences, and make full audit trails. The outcome has been that processing time has been cut in half, and human errors have dropped by 40% during important financial reporting times.

Changes in healthcare: Apollo and Fortis implementations

Top Indian hospital chains are using agentic AI technologies to handle complicated operational tasks. These systems change doctors' schedules based on the number of patients coming in, ensure that resources are used efficiently across departments, and help with early diagnosis by looking at patient histories and test data in real time. Leading hospitals claim wait times were down by 25%, and their resources were used 30% efficiently across their network.

Results that can be measured in all fields

It's not only a thought experiment to use agentic AI. Agentic systems are already being tested in areas where time, coordination, and accuracy are particularly crucial, such as healthcare, banking, transportation, and manufacturing. Agentic AI systems can figure out how much of a product is needed, adjust the number of items that need to be sent, and change how things are shipped when there are delays at ports or severe weather. This can help you avoid running out of stock by up to 30% and save you up to 15% on shipping costs. There are no rules for making decisions. They depend on the situation, the data, and how things change.

A change in customer service in Indian telecom

Big Indian telecom providers have put in place agentic AI systems that take care of customer service requests from beginning to end. These self-driving agents handle billing complaints, changes to plans, and fixing technical problems on their own. Only very complicated or strange situations lead to escalation.

• Airtel's AI chatbot 'Airtel Thanks' has significantly improved customer engagement and reduced service resolution time.
• Indian Telecom companies like Jio, Airtel, and Vodafone Idea are leveraging AI to improve customer experience, reduce churn, and enhance subscriber stickiness.

Improving digital marketing

Indian e-commerce and digital marketing companies are using agentic systems to track how much money they spend on ads across platforms, try out different creative ideas, and change their targeting techniques all the time. These systems work all the time and make decisions in real time depending on performance data. Companies say that their return on ad spending has gone up by 20-25% and their manual campaign management costs have gone down a lot.

How Indian firms are affected by the structure

Agentic systems are very useful in India's complicated corporate world, where manual coordination often slows things down. Indian banks and other financial organisations are adopting agentic AI to monitor rule compliance. AI agents constantly analyse contracts and policy documents, highlight possible problems, and track compliance across many different sets of rules. This has sped up the audit process and made it easier to find risks before they happen.

New ideas in manufacturing and the supply chain

Indian manufacturing enterprises, especially those that make cars and textiles, use agentic systems to synchronize production schedules with changes in the supply chain. These AI agents change manufacturing plans independently based on the availability of raw materials, transportation limits, and demand projections.

Automating human resources

Several Indian IT services organisations have put agentic AI systems to work on things like staffing projects and making shift schedules. These agents look at the availability of employees, past performance data, and trends of project demand to make the best decisions about allocating resources. This has led to staffing cycles that are 30% faster and better use of resources. TCS has over 100,000 employees trained in AI and has expanded its links with Azure OpenAI.

How autonomous AI works

Agentic AI can do a lot of things since it uses a lot of different technologies. With reinforcement learning, systems can improve by trying and failing. Planning algorithms help you divide big goals into smaller, more manageable chunks. Natural language processing lets you talk to users and other systems. These agents may collect data, make choices, and take actions in real time when they are used with outside tools like APIs and corporate applications.

In more advanced solutions, several agents work together across different platforms. For instance, one person monitors stock levels, another handles buying, and a third handles shipping. They work together as a team to maximise the use of all the parts of the workflow.

The future of Indian businesses

The change from generative AI to agentic AI is a big step forward in how Indian companies use AI. As the home market becomes more complicated and bigger, the need for systems that can think, act, and learn on their own will keep growing. Research shows that machines will handle 80% of customer support around the world by 2028. Indian enterprises are adopting this technology at a faster rate than others.

Agentic AI doesn't get rid of the need for human oversight, but it does make it less necessary for people to start processes. This change opens up room for quicker decision-making, smoother operations, and systems that can adapt more easily. These are all skills that are becoming more and more important in India's fast-changing corporate environment.

As Indian companies continue to lead the world in adoption rates, the competitive benefits of using agentic AI will probably set the standard for the next generation of corporate success in the area.

This article is penned by Chandan Bagwe, Founder / Director of C Com Digital

Disclaimer: The article features the opinion of the author and does not necessarily reflect the stance of the publication.