While Agentic AI has yet to become fully mainstream, momentum is clearly building among the leading Indian IT firms. However, despite the growing appetite for adoption, full-scale integration remains gradual.
According to Deloitte’s fourth wave of the State of GenAI report (India perspective), over 80% of Indian organisations are exploring the development of autonomous agents, signalling a significant shift towards Agentic AI.
Yet, despite the growing appetite for adoption, full-scale integration remains gradual. The same Deloitte report noted that with AI evolving at an unprecedented pace, 28% of firms worry their current AI solutions could become obsolete within just two years.
Mukesh Bansal, founder of Nurix, CureFit, and Myntra, pointed out the disconnect between the AI agent hype and its actual production deployment in a recent LinkedIn post.
“Everyone is building AI agents, and yet so few AI agents are in production doing real work. LLMs keep getting better and better, and yet P&Ls are not changing by even basis points! What’s going on?” Bansal wrote.
For him, the reason is simple. Building real, enterprise-grade AI agents is not the same as coding an app or selling a SaaS tool. “Agentic companies are not like a traditional software or platform company at all. It is a cross between McKinsey and Infosys,” he said.
Amidst this, Wipro is placing a big bet on Agentic AI systems that can set goals, make plans, and take action on their own.
Wipro’s Take on Agentic AI
Recently, the company teamed up with Google Cloud to roll out 200 production-ready generative AI agents across sectors such as healthcare, banking, insurance, retail, manufacturing, and IT solutions.
It is designed to improve customer experiences, streamline business processes, and accelerate digital transformation using Google’s Gemini models and Vertex AI platform.
“Wipro is demonstrating how Google’s Gemini models and Vertex AI can be utilised to build powerful, industry-specific agents that transform everyday work across industries,” said Victor Morales, VP of global system integrators partnerships, Google Cloud, in a statement.
Meanwhile, Pushpa Ramachandran, VP and global head of AI at Wipro Limited, told AIM that these agents are capable of learning, planning, and acting independently within complex business environments.
The strategy is to build modular, domain-specific agents that plug into business processes across industries.
In healthcare, Wipro is creating agents that handle tasks like provider credentialing and onboarding. In energy and utilities, AI agents can spot equipment faults and adjust maintenance schedules without human intervention. In retail, they can process refunds, resolve complaints, and update prices and recommendations in real time.
One global retailer, as Ramachandran mentioned, used Wipro’s agentic AI to automate free trade agreement checks and customs paperwork across multiple countries. As a result, it reduced port delays, minimised duty leakage, and saved significant costs while speeding up product launches, the company claimed.
He further said that AI is now part of almost every client conversation. “We are in an era where we have AI-led delivery in all the client conversations,” Ramachandran noted. He added that industries such as BFSI, consumer goods, telecom, and manufacturing are rapidly advancing in this space.
What Others are Doing?
Meanwhile, Tata Consultancy Services built one of the largest enterprise AI stacks, quietly powering over 150 workflows with autonomous AI agents.
On the other hand, HCL Tech’s patented GenAI platform, AI Force, which revitalises the software development and IT-Ops lifecycle, has now been enhanced with Agentic AI capabilities.
Alongside this, its Talent Navigator solution leverages GenAI to search through vast resume databases, match candidates to job descriptions, simulate interview experiences, schedule interviews, and set up personalised onboarding sessions.
Infosys, too, is in the race and has launched over 200 enterprise AI agents powered by Infosys Topaz AI offerings and Google Cloud’s Vertex AI Platform.
Why is Wipro Focusing on SLMs?
Wipro is also working on small language models (SLMs), which are lighter, task-specific AI models trained on industry-specific data.
In the emerging Agentic AI trend, AI agents often don’t need a gigantic general model. They need lightweight, task-specific brains that can work in concert.
SLMs fit perfectly into this architecture.
Wipro also collaborates with Wipro Ventures, which brings together a network of startups focused on industry- and domain-specific solutions, including small language models (SLMs).
Each startup offers deep specialised expertise, enabling Wipro to accelerate SLM development and deliver business impact for clients. In addition, the company partners with the research arms of universities to address complex business challenges and broader ecosystem opportunities.
Skills remain a primary focus, with over 87,000 employees now certified in AI, covering areas such as prompt engineering, model fine-tuning, and AI ethics and governance.
Wipro is also expanding training to frontline roles like customer service agents, field technicians, and plant operators, so they can work alongside AI systems and ensure adoption at every level.
“This democratisation of AI knowledge is core to our AI-first transformation strategy,” Ramachandran mentioned.
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