Long before artificial intelligence became the dominant narrative in workforce strategy, NIIT, which offers talent development and managed training services, had begun stepping away from its high-street classroom model. The change was structural and in step with evolving needs, as digital access became ubiquitous and enterprise transformation cycles accelerated.
Today, with enterprise contributing 62% to its revenue, the shift has fully matured—from physical training centres to platform-led, enterprise-embedded, AI-aligned capability building.
In an interaction with AIM, Anshumaan Prasad, Business Head, NIIT Digital and Head of Marketing at NIIT Limited, explains that the transformation was not tactical but structural.
“In the early decades, physical centres solved a real access problem—computers and connectivity were limited. Today, access is ubiquitous. The constraint is no longer infrastructure; it is relevance and speed,” he notes.
Stepping Away From Retail Centres
For years, NIIT was synonymous with widespread physical training centres across India. But that has now changed.
“As technology cycles shortened and enterprise transformation accelerated, learning had to move closer to the workplace,” Prasad explains. “We consciously evolved from an infrastructure-led retail model to a platform-led and enterprise-embedded skilling model.”
AI, he adds, has intensified the shift. “Skills now evolve too quickly for static, centre-based distribution to be the primary vehicle.”
While NIIT remains open to multiple delivery formats, the centre-based retail model is no longer its core growth engine.
New Core Engine
The numbers reflect the pivot.
In Q3 FY26, the enterprise contributed approximately 62% of its revenue, while the consumer side of the business contributed around 38%, with technology programmes accounting for 76% of total revenue.
NIIT reported revenue of ₹101.4 crore in the third quarter, up 3% year-on-year but down 3% sequentially. The results factored in an exceptional expense of ₹5.4 crore to account for the impact of the new labour code and related strategic actions.
Enterprise learning, Prasad argues, has become structurally more important because organisations are prioritising productivity and workforce transformation over incremental hiring.
“L&D (learning and development) investments are increasingly tied to digital adoption, AI enablement, and measurable business impact,” he says.
Enterprises, he adds, are not just hiring new talent but “extensively focusing on training their employees in the era of AI.”
“Clients increasingly link skilling investments to productivity improvements, faster deployment cycles, reduced dependency on lateral hiring, internal redeployment ratios, and measurable business KPIs,” Prasad notes.
From Broad Skilling to Role-Mapped Outcomes
The nature of corporate training has also shifted dramatically.
“Training today is tightly role-mapped and outcome-linked,” Prasad said. “Enterprises are no longer asking for broad-based skilling programmes; they want pathways aligned to job families, transformation priorities, and performance metrics.”
Through RPS Consulting—an NIIT subsidiary serving over 250 global capability centres and global system indicators through 32 OEMs—programmes are built around applied labs, simulations and project-linked capability building rather than classroom-style instruction.
“The emphasis is on deployment readiness, not certification volume,” he remarks.
Automation is Redefining Entry-Level Roles
As AI automates repetitive tasks, NIIT has re-engineered its curriculum.
“Automation is reducing the value of repetitive execution skills. As a result, we have redesigned curricula to emphasise AI-assisted development, workflow orchestration, systems thinking, data literacy, and domain integration,” Prasad says.
The shift, he explains, is from “can you execute?” to “can you design, validate, and integrate intelligent systems into business workflows?”
Entry-level roles are not disappearing, he stresses, but “the baseline capability expected from day one has increased significantly.”
In response to growing enterprise demand, NIIT introduced the Building Agentic AI Systems programme in November 2025, focused on AI system creation and orchestration. The course costs about ₹1.5 lakh.
“As organisations began moving beyond basic AI adoption toward autonomous, goal-driven systems, it became imperative to equip learners with the capability to design and build agentic architectures that can operate within complex business environments,” Prasad adds.
AI-Orchestrator Ready
The definition of “job-ready” has evolved sharply in the AI era.
“Being job-ready today means being productive in an AI-augmented environment from day one. Knowing syntax or tools in isolation is no longer sufficient,” Prasad observes.
Coding remains relevant but is increasingly AI-assisted. The differentiator now lies in “judgement, system design thinking, and the ability to evaluate and govern AI outputs.”
With the rise of agentic AI systems that can reason, plan and act autonomously, enterprises require engineers who can design multi-agent workflows, build retrieval-augmented systems grounded in enterprise data, implement safety guardrails, and balance performance, latency, cost, and governance.
“Job-readiness in this context means being able to architect and operate intelligent systems, not just use them,” he notes. “It is about moving from AI consumption to AI orchestration.”
Differentiation in a Crowded Skilling Market
In a market crowded with bootcamps and online platforms, NIIT positions its edge around scale and integration.
Its B2B tech learning venture, StackRoute, has partnered with over 90 Fortune 500 organisations for IT skill development, and the company maintains a 97% client retention rate. It offers custom programmes in data science, data engineering, and cybersecurity.
“We design role-based, enterprise-aligned capability frameworks that integrate directly with transformation agendas,” Prasad says. “That level of integration is harder to replicate through standalone bootcamps.”
Prasad observes that companies are building foundational AI literacy across broad employee bases, while deeply skilling smaller, high-impact cohorts in advanced capabilities such as cloud-native engineering, AI orchestration, and cybersecurity.
NIIT’s curriculum architecture is structured around modular and stackable pathways to support both scaled literacy programmes and intensive, role-specific tracks.
Continuous Learning
Looking five years ahead, Prasad believes skilling will become continuous and embedded within roles rather than front-loaded before employment.
“The half-life of skills, particularly in AI and digital domains, continues to shrink,” he observes. “Skilling will increasingly be continuous and embedded within roles rather than front-loaded before employment.”
NIIT is reorganising accordingly, strengthening enterprise partnerships, expanding digital delivery platforms, and embedding AI-enabled personalisation within learning journeys.
BFSI Bet Was Demand-Led
NIIT’s domain-specific push is not new. Its BFSI-focused initiatives dates back to the establishment of the Institute of Finance, Banking, and Insurance in 2006 to address skilled manpower requirements in financial services.
“Since then, over 300,000 individuals have been trained through these pathways, with programmes aligned to leading BFSI organisations,” Prasad notes.
The company’s BFSI portfolio continues to be anchored in bank-aligned, job-linked programmes delivered in collaboration with leading institutions such as ICICI Bank, HDFC Bank, and Axis Bank.
Offerings range from short-duration sales and relationship management certifications to longer-format banker training programmes. These initiatives combine mentor-led formats with role-specific curricula.
“The move into domain-specific programmes was demand-led,” he says, adding that BFSI today requires regulatory awareness, digital fluency, analytics capability, sales and relationship skills, and customer-centric capabilities—making technology integration essential.
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