What Sets India Inc’s AI Leaders Apart From the Rest
Leaders who get AI right are rewiring their companies, not just upgrading tech
Topics
News
- India to Roll Out First Homegrown Chip From CG Semi's Sanand plant
- Anthropic Foils AI-Powered Cybercrime Spree
- Team Computers and Yotta Data Services Partner to Accelerate AI Adoption in India
- Databricks to Buy Enterprise Feature Store Tecton
- OutSystems Names Ganesh to Accelerate AI-Powered Low-Code Growth in India
- OpenAI to Open First India Office in Delhi by Year End
Artificial intelligence is no longer a boardroom buzzword in India’s corporate sector. It has become the scaffolding of strategic execution. From consumer goods and insurance to payments, cybersecurity and urban infrastructure, some of the country’s key business leaders now speak of AI not as a peripheral tool but as the fulcrum for rethinking how their organizations create value, compete and grow.
This shift mirrors global developments. A report by McKinsey in March this year on the state of AI said more than three-quarters of major organizations now use AI in at least one business function.
Generative AI adoption has surged, with 71% of firms surveyed in the study reporting regular use. Yet despite this momentum, just 1% say their deployments are mature, underlining a significant gap between experimentation and enterprise-wide transformation.
Jagdish Kumar, Chief Technology Officer of Worldline, the global payments and financial services provider, is clear that generative AI enhances strategic execution rather than redefining it.
“As a global leader in payments, our strategic priority has always been delivering value to our clients and partners,” Kumar says. “We see GenAI as a valuable tool to enhance and strengthen decision support systems, bringing speed and efficiency to data-driven programs, operational processes, customer experience and compliance. But these were priorities we already had, so GenAI is an enabler, not a strategic pivot.”
That distinction is key. McKinsey’s research shows that redesigning workflows, and not just automating tasks, is the single most influential factor in translating gen AI deployment into profitability gains. Yet only 21% of organizations surveyed had fundamentally redesigned workflows.
At PB Fintech, parent of Policybazaar and Paisabazaar, joint group CEO Sarbvir Singh believes that change is already underway.
“AI-driven development is accelerating our build cycles and enabling faster execution,” he says. “We’ve moved toward decentralized, application programming interface (API)-driven problem solving as the backbone of scale.”
This hybrid model of centralizing oversight while decentralizing implementation, echoes McKinsey’s findings. Most large firms now follow a partially centralized approach, especially in areas like talent and adoption.
At PB Fintech, open-source models are fine-tuned internally and paired with human oversight to ensure accountability, particularly in risk and fraud detection.
Singh calls it “a strategic enabler” that is unlocking new market segments through hyper-personalized outreach.
The same principle is at work at Hindustan Unilever Ltd (HUL), one of India’s most sophisticated users of digital infrastructure.
Chief Digital and Information Officer Meenakshi Burra says AI is integral to HUL’s “ASPIRE” strategy, from AI-powered campaigns for 1.4 million kirana stores to virtual try-ons for Lakmé and Pond’s.
“This isn’t just about keeping pace, but about leading,” she says. “AI offers a unique opportunity to elevate experiences, while optimizing spend and driving greater effectiveness in campaigns.”
McKinsey’s report reinforces that the firms seeing the greatest value from AI are those that adopt best practices: setting clear KPIs, mapping out adoption roadmaps, building internal champions and investing in capability training.
Yet fewer than one in five companies surveyed are tracking KPIs for gen AI today.
Workflow visibility is another blind spot. According to Pari Natarajan, CEO of Zinnov, most companies still lack clarity on how employees spend their time: a key prerequisite to meaningful automation.
“Mapping workflows is essential before deploying AI, whether it’s automating repetitive processes or empowering sales teams,” Natarajan says. “Once mapped, the real challenge becomes change management.”
Nowhere is this urgency more evident than in cybersecurity.
“Threat hunting used to happen weekly, even fortnightly. Today that’s untenable,” says Muraleekrishnan Nair of UST. “Bad actors operate in hours, not days, and manual detection can’t keep up.”
UST has deployed a real-time AI platform for continuous threat exposure, while firms like Seclore are applying AI to data governance.
“We analyze data and determine the security policies it needs,” says Seclore founder and CEO Vishal Gupta. “We even decide if data should be accessible to AI or restricted to humans.”
Yet risk oversight remains uneven. McKinsey’s study shows that while many firms have started addressing risks related to inaccuracy, cybersecurity and intellectual property, only 27% of organizations review all gen AI outputs before they are used.
Larger companies are more proactive, with growing demand for compliance and AI ethics specialists.
At Gnani.ai, co-founder and CEO Ganesh Gopalan sees voice AI addressing not only productivity but also accessibility gaps.
“We’re deploying for Tata Motors to capture showroom feedback, and in healthcare to assist with maternal care,” he says. “This is about more than automation. It’s about inclusion.”
Genesys International is pushing into digital infrastructure with city-scale AI.
“We stopped thinking like a service provider and started thinking like a platform company,” says chairman Sajid Malik. “The goal is to democratize intelligence and build a digital infrastructure layer over India’s physical infrastructure.”
This level of ambition often requires organizational reinvention.
At Happiest Minds Technologies, a dedicated Generative AI Business Services unit now operates with its own CEO and COO.
“We’re improving efficiency in software development and helping clients create new revenue streams,” says unit CEO Sridhar Mantha.
Sasken’s CTO Girish B.V.S. identifies three AI vectors: enhancing user experience, boosting developer productivity and streamlining workflows.
“Our intelligent log analyzer for embedded software has already reduced time spent diagnosing defects,” he notes.
Still, the workforce impact remains nuanced. While McKinsey’s respondents expect headcount to fall in areas like customer service and supply chain, many also predict growth in IT, product development and data science. One in two say they’ll need more data scientists over the next year. Meanwhile, 38% expect no major change in workforce size from gen AI in a sign that AI’s value is less about replacement, more about reallocation.
“GenAI expands our toolset and deepens impact, but it must remain subservient to the real-world problem statements we aim to solve,” says Shekar Sivasubramanian of Wadhwani AI. “Innovation for its own sake has no value. Practical, scalable solutions do.”
Pragmatism may be India’s greatest competitive edge in this AI race. As McKinsey notes, the companies realizing value are not just investing in tools, but rewiring governance, workflows and culture. The rest, including many Indian firms, are getting there fast.
