Every enterprise now claims to be “AI-first.” Far fewer can show that their workforce has actually caught
up with that ambition. Cognizant’s Chief Learning Officer, Thirumala “Thiru” Arohi, argues that this gap — between the AI an organization deploys and the AI its people are actually ready to use — is where most transformation efforts quietly stall.
“AI investment and workforce transformation are not two separate agendas,” Arohi says. “Organisations that deploy AI before their people are ready to use it often get stuck: tools are adopted but underused, and investments are made without realizing their full value.”
That conviction sits behind two of the biggest bets Cognizant has made in the past several years: Skillspring, an AI-native learning platform built to replace the traditional corporate LMS, and a broader reengineering of how the company defines jobs, careers and readiness in an AI-saturated economy.
Together, they offer a window into how one of the world’s largest IT services firms — nearly 350,000 employees — is trying to move past the pilot-project phase of AI adoption and into something closer to permanent organisational muscle memory.
From System Integrators to AI Builders
Arohi frames the challenge less as retraining people for specific new tools and more as repositioning the entire workforce for roles that are still taking shape. “Many roles are evolving, some are emerging, and a smaller set is genuinely net new,” he says. “Our job in Learning & Development is to orchestrate that transition, aligning talent to AI-era roles and building precise capabilities, cohort by cohort.”
That reframing has changed what L&D is for at Cognizant. “L&D here isn’t just a training function, it’s a change agent,” Arohi says. “We’re moving from system integrators to AI builders, building interdisciplinary, AI-augmented teams that are simultaneously fluent in the business domain, operations, and technology.”
The shift is structural as much as philosophical. Cognizant has consolidated what Arohi describes as legacy job groups into future-oriented job families, each mapped across a current, evolving and future state. “At that scale, you need a system built to drive it,” he says. “That system is Skillspring.”
Why a Traditional LMS Wasn’t Going to Cut It
Skillspring is deliberately not a rebuild of the conventional learning management system. “A conventional learning platform is content-led and measures consumption and completions,” Arohi says. “Skillspring is outcome-led. We measure readiness, time-to-competency and applied usage.”
He points to a handful of design principles that shaped the platform. The team adopted what he calls an AI-first development mindset, running every feature through an AI lens before it’s built. They also committed to a “zero-UI” philosophy — learning delivered through voice, chat and contextual nudges embedded directly in the flow of work, rather than a destination employees have to log into.
Underneath that sits an outcomes-first architecture. “Adaptive pathways provide role-, skill- and outcome-aligned learning journeys that evolve with work,” Arohi explains. “Autonomous AI agents tutor, create content, and assess learners, allowing us to scale learning without proportionately scaling L&D effort.” Leaders, in turn, get real-time skill-readiness dashboards at the individual, team and business-unit level. “Conventional platforms cannot do this,” he says flatly.
The Hardest Part Wasn’t the Technology
Rolling out a learning platform to a workforce the size of Cognizant’s surfaces problems no pilot program would ever reveal, and Arohi is candid that the toughest obstacles weren’t technical. “The biggest challenge was redefining success,” he says. “For years, learning was measured by course completions and certifications; we had to shift the focus to readiness, deployability and time-to-productivity.”
Adoption at scale was the next hurdle — and it required rethinking what actually triggers learning in the first place. Rather than pushing generic courses on a schedule, Cognizant now tries to trigger learning from real work signals: a role change, a client need, an emerging capability gap mapped to a specific job-family pathway.
The third challenge, Arohi says, was ownership. “Capability building cannot remain an L&D agenda alone; leaders and managers must own it, while AI fluency becomes a baseline expectation.” To make that expectation visible, Cognizant built what it calls an AI Fluency Dashboard, tracking proficiency, training progress, tool adoption and innovation as associates move along a maturity curve the company labels “AI Aware” to “AI Champion.”
Measuring What Actually Matters
If there’s a recurring theme in Arohi’s answers, it’s a discomfort with vanity metrics. Asked how Cognizant judges the business impact of its learning investment, he lays out a three-tier framework. Leading indicators — AI tool adoption, learning-pathway engagement, skills-assessment completion — show whether the workforce is starting to move. Lagging indicators go deeper: speed to productivity in a new skill, internal mobility into evolving roles, demonstrated proficiency in live client delivery, and the depth of AI integration in daily work.
The third and, in Arohi’s words, most critical tier is business-impact linkage. “We connect skilling investments to project delivery needs, mapping who has a required capability, who is close, and what bridge learning can close the gap in time,” he says. “The shift is clear: we no longer measure only whether people learned, but whether capability has advanced and the business is better prepared to deliver.”
Three Decades In, the Biggest Shift Is Speed
Arohi has spent nearly 30 years building talent engines in India, and he sees the current moment as a genuine inflection point rather than another cycle of tooling change. “In the past, organisations gained advantage through what their workforce knew,” he says. “Today, competitive advantage increasingly comes from how quickly a workforce can acquire new knowledge, apply it, and adapt again as technologies, roles, and business models evolve.”
He traces a compression in how learning itself is delivered: from “macro learning cycles measured in months, to modular learning cycles measured in weeks, and now to continuous microlearning.” That compression is why Arohi describes learning agility — the ability to sense change, acquire a skill quickly, apply it immediately, and let go of what’s no longer useful — as the defining capability of the AI age. “Learning has moved from a chapter in your career to a constant in your workday.”
Scaling Beyond the Company’s Own Walls
Cognizant’s ambitions extend past its own payroll. Through its Synapse initiative, the company has set a goal of upskilling two million people by 2030 — a target Arohi frames as addressing a systemic problem, not just a corporate one. “Synapse addresses a challenge bigger than any single organisation: the growing gap between the speed of technological change and the speed at which talent ecosystems can adapt,” he says.
Synapse extends Skillspring’s reach into NGOs, academic institutions and broader communities, aiming to build AI fluency and digital capability well beyond Cognizant’s employee base. “Future skills are not a competitive advantage for a few; they are an economic necessity for many,” Arohi says, adding that success at this scale will be judged on capability creation, opportunity creation and long-term impact monitoring.
Why Cognizant Also Built a Physical Campus
In an era when nearly every learning conversation defaults to digital platforms, Cognizant’s decision to invest heavily in a physical facility — the Siruseri Immersive Learning Center — stands out. Arohi’s explanation draws on Daniel Kahneman’s dual-process framework of fast and slow thinking. “Digital platforms are excellent for fast learning: building foundations, answering questions in the moment, and developing technical skills at scale,” he says. “But creativity, judgment, collaboration, leadership and accountability require slow learning through deliberate practice, experimentation, reflection, feedback and human interaction.”
That, he says, is precisely the gap an immersive campus fills — a place where people navigate ambiguity together, challenge assumptions, and build trust through shared, real-world experience. “Skillspring helps people learn faster; the immersive center helps them learn deeper,” Arohi says. “One builds knowledge at scale, the other converts it into insight, confidence and behavioral change. The future of learning is not digital or physical; it is the intelligent combination of both.”
Redesigning Careers Around Capability, Not Hierarchy
Perhaps the clearest signal of how seriously Cognizant is taking this shift is what’s happening to its own career ladders. As AI agents take on more routine work, Arohi says the company is rethinking career progression “around capability, not hierarchy,” with growth defined as continuous movement from a current state toward a future one.
New “Frontier” tracks now sit at the center of that architecture. Frontier Certified Engineers are tasked with redesigning how work actually gets done; Frontier Business Operators own outcomes by orchestrating a blend of human judgment and digital labor. Both are earned roles, Arohi notes, entered through assessment and selection by a dedicated Frontier Center of Excellence rather than simple tenure or promotion cycles.
Even individual skill development is being reshaped by AI, through what Cognizant calls digital twins — AI-powered counterparts trained on an employee’s own knowledge and work patterns that can take on routine research, coordination and learning tasks. But Arohi is careful to draw a line around what doesn’t get automated away. “Accountability, ethics and judgment remain human responsibilities,” he says. “AI accelerates work; people still own outcomes.”
The Bigger Picture
Taken together, Arohi’s answers sketch a strategy that treats workforce transformation as inseparable from — not subordinate to — technology investment. Skillspring, the Frontier career tracks, the AI Fluency Dashboard and the Siruseri campus are less a portfolio of separate initiatives than different instruments pointed at the same problem: how fast an organisation’s people can learn, apply and relearn as the ground keeps shifting beneath them.
For CIOs and CHROs watching their own AI rollouts stall on adoption, Cognizant’s experience offers a pointed reminder. The technology is rarely the bottleneck anymore. The organisation’s capacity to learn is.