Inside Infosys’ AI learning strategy: Upskilling 300,000+ employees for the future of work

At a time when artificial intelligence is reshaping industries, institutions, and job roles, the role of talent development is undergoing a quiet transformation. But what does it truly mean to be AI-centric in an enterprise context? At Infosys, the answer appears to go beyond the deployment of intelligent tools. According to Thirumala Arohi Mamunooru, Executive Vice President and Head of Education, Training and Assessments, the shift is structural, cultural, and deeply human—one that touches the fundamentals of how people work, learn, and evolve.

In a recent conversation with People Matters, Arohi outlined how Infosys is approaching the creation of an AI-ready workforce—not just in terms of skill sets, but mindset. Through the integration of AI into various layers of learning, from personalisation to application, Infosys is seeking to adapt its talent development strategy to a rapidly evolving technological environment.

For many companies, adopting AI begins with tools and infrastructure. At Infosys, Arohi suggests it begins with people. “AI-centricity,” he notes, “means embedding AI into the very fabric of organisational thinking and decision-making.”

This approach involves more than simply layering AI onto existing systems. Instead, it calls for rethinking processes with AI as a foundational element. Initiatives like Infosys Topaz, an AI-powered transformation platform, and NaVi, a generative AI assistant for internal navigation, represent steps in that direction.

However, the transition is not without its complexities. “We're fostering trust in AI by making it explainable and accessible,” Arohi adds. Democratising AI literacy and encouraging human-machine collaboration are key pillars of this strategy.

Reframing Learning for an AI Era

Infosys has long been noted for its internal learning infrastructure, with platforms like Wingspan widely referenced in industry discussions. But with the emergence of AI, even mature systems have needed reconfiguration. Arohi describes a shift toward hyper-personalised, role-specific learning journeys that adapt to user behaviour through AI.

“AI now curates content based on career paths, skill gaps, and aspirations,” he explains. The company has moved from static training modules to dynamic learning experiences that adjust in real time. Algorithms suggest resources, adapt difficulty levels, and reinforce weak areas—an approach increasingly seen across digital learning ecosystems.

Beyond theory, Infosys encourages applied learning. Employees participate in hackathons, innovation challenges, and live projects to test their skills in real-world settings. “It’s not just about learning AI,” Arohi says, “it’s about learning with AI.” That distinction reflects a growing belief that AI should be both subject and enabler in corporate learning.

Infosys’ approach also accounts for varied levels of readiness. The organisation structures its AI training across three stages: awareness, builder, and mastery. Rather than assuming technical fluency, it allows employees to progress based on need and function.

“Our platforms like Lex and Wingspan offer curated, role-specific journeys,” says Arohi. Sales professionals, for instance, might study AI through customer insight use cases, while HR staff are exposed to predictive analytics in hiring. The strategy aims to make AI relevant across functions, not just within technical teams.

Keeping Pace with a Shifting Landscape

Given the fast pace of AI development, Infosys has adopted what it calls a ‘living curriculum’—constantly updated to reflect emerging tools and trends. This is governed by a Skill Governance Council under a framework termed ‘Skills Horizon.’

“Generative AI, prompt engineering, ethical AI—these aren’t just buzzwords for us,” Arohi notes. These themes are embedded into training programmes and refreshed periodically. AI assistants like Navi and Zoe guide learners to context-specific resources, enabling a more on-demand model of learning.

While many companies are still adjusting to the idea of continuous learning, Infosys appears to be doubling down. Learning is positioned as a fluid, daily experience integrated with work routines, rather than a formal or scheduled activity.

The firm’s partnerships with AWS, Microsoft, and Google add another dimension. These alliances provide AI and cloud training across levels, including for senior leaders through programmes co-developed with the Infosys Leadership Institute and academic collaborators like Kellogg. The company has also introduced InfyVerse, a metaverse-based immersive learning platform, allowing geographically dispersed teams to engage in collaborative simulations and projects.

Such initiatives align with broader efforts across the industry to merge academic insight with enterprise application. By co-creating content with universities, Infosys is looking to close the gap between educational curricula and real-world AI deployment.

Strategic Shifts in L&D

As AI begins to redefine roles and business models, the Learning and Development (L&D) function is also experiencing a shift—from being a support unit to becoming a strategic enabler.

“AI-powered platforms enhance learning experiences by identifying skill gaps and offering real-time feedback,” says Arohi. He argues that L&D must now sit closer to business objectives and be equipped with cross-functional skills, including ethical reasoning and data literacy.

For HR leaders, this means driving a culture of continuous learning and aligning learning outcomes with business imperatives. But challenges remain: ensuring responsible AI use, managing change fatigue, and maintaining trust in algorithmic decision-making are hurdles many enterprises are still navigating.

Arohi envisions a future where L&D becomes a key lever for sustainable growth. Organisations that embed AI in their talent strategy, he believes, will be better positioned to retain talent and adapt to shifting market demands.

Yet he also acknowledges that the cultural piece is critical. Embedding AI into how people think and work requires transparency and trust. Infosys is addressing this by promoting explainable AI and encouraging iterative learning behaviours—where experimentation, failure, and collaboration are seen as valuable steps in the learning process.