Rajiv Jayaraman, CEO & Co-founder, KNOLSKAPE
Across industries, job boundaries are being redrawn in real time, making organisations rethink how Agentic AI is structured and how skills are built. Employees today want more than a paycheck; they want growth, purpose, and ownership of their careers. Organisations are investing in employee-led learning signals, which is a decisive shift, as we’re moving from top-down training calendars to systems where employees and AI co-create their own growth paths. For organisations, the real question is not if we adopt this approach, but how fast we can build learning systems that empower employees to leverage AI and keep pace with the skill demands of today’s rewired job market. Digital Readiness ranks as the top L&D priority of organisations, and today, employees are demanding more than just a catalog for courses. The challenge isn’t simply reskilling at scale, but it actually is redesigning roles so that human judgment becomes the differentiator. For organisations, the real question is not if we adopt this approach, but how fast we can build learning systems that empower employees in leverage AI and keep pace with the skill demands of today’s rewired job market.
Here’s the hard truth, treating upskilling as a once-a-year event or a static library won’t cut it. The companies winning today are building agentic learning ecosystems: modular, measurable, and embedded directly into the flow of work. Routine approvals, pattern recognition, and scripted responses are already getting automated. However, organisations must focus on upskilling to ensure that leadership decisions, which involve synthesising inputs across teams, resolving stakeholder tensions, balancing risk with incomplete data, and creating novel solutions under pressure, are made effectively.
The response, therefore, cannot be broad retraining. It must be targeted empowerment. As leaders, we must be surgical and design outcome-aligned learning units that AI agents can surface exactly when needed. This will help them to run continuous, lightweight diagnostics to keep role-skill maps current, and deploy suggestive systems that connect those diagnostics to on-the-job practice. The starting point is simple but powerful, mapping three to five critical decision points for every role, tagging your learning assets to those decisions, and instrument L&D diagnostics so you can measure competence gains where they matter most.
To make learning truly work in the modern world, we have to stop thinking in terms of one-off training programs. Episodic workshops won’t prepare teams for the rapid pace at which roles are shifting. What we need instead is a living, breathing learning ecosystem, one that runs continuously and adapts as roles evolve. It’s not a mere checklist; it’s an approach that transforms learning into sustained performance through continuous reinforcement.
One of the end-to-end approaches that are simple yet powerfully autonomous can be Evaluating skills at scale through AI-driven diagnostics, so organisations always know where the skill gaps are. Then, we educate employees through highly curated and contextualised learning, ensuring they access only what’s relevant. The next step is to create immersive Experiences using AI powered simulations, where teams work through real-world scenarios to strengthen their judgment giving them a safe space to practice. Finally, we focus on enabling application by combining AI-powered coaching and just-in-time nudges that drive learning retention and reinforce behaviour change in real-world contexts. While traditional classrooms still hold value, without these continuous loops of learning, application, and reflection embedded within the flow of work organisations risk falling behind. In the age of Agentic AI, preparing people for decisions that AI cannot make is not optional it’s mission critical.
Winning in the age of Agentic AI becomes can be possible for organisations when they build systems where human judgment and AI intelligence would continuously and measurably elevate each other. Here are five strategies that will transform over 10 million jobs in India by 2030, and the leadership team must act on:
- Personalisation of L&D: Customisable learning journeys to enhance role, competence, and career goals instead of pushing generic courses. This relevance shortens time to competence and drives higher engagement. Organisations like Genpact and TCS are already using AI-driven recommendation engines to deliver role- and behaviour-based content, improving productivity and retention while boosting ROI on L&D spend.
- Hyper- Personalised Learning Paths: Break content into 5–15 minute micro-modules and make them accessible. This lets employees learn just-in-time, in the flow of work, reducing downtime from lengthy workshops. Companies adopting flexibility report higher adoption and faster application of new skills.
- Technology Integration: Organisations are now prioritising combining analytics, simulations, and recommender systems to scale personalisation and measure impact. Simulation-based learning enables risk-free practice for high-stakes decisions, accelerating behaviour change that aligns well with L&D efforts directly to business KPIs.
- Contextualised Content: Off-the-shelf content rarely delivers impact. Using AI-powered simulation builders and no-code design tools like Genie Kreator, organisations can co-create role-specific, market-relevant scenarios with SMEs. These immersive experiences drive real-world application and behaviour change where it matters most.
- Employee-Driven Programs: KNOLSKAPE Survey states that 60% of organisations are investing in systems that allow employees to curate and steer their own learning paths. Autonomy builds intrinsic motivation and creates a culture of self-reskilling, reducing external hiring needs and increasing internal mobility.
Organisations that embrace everyday learning, foster open dialogue around AI, and invest in human-centered leadership will lead in the age of transformation. But it’s Agentic AI that will set future-ready organisations apart by enabling systems that learn, adapt, and guide in real time. For employees, this unlocks a new era of growth where roles become more dynamic, more empowered, and ultimately, more human.