AI agents take the wheel as NIIT launches hands-on Agentic AI course

NIIT has unveiled a new upskilling initiative aimed at engineers and software developers: a 25-week program titled Building Agentic AI Systems. The curriculum is tailored to meet the rising demand for talent capable of building autonomous, goal-driven AI agents, systems that do not just assist humans, but act on their own to execute tasks.

As businesses globally gear up to adopt more intelligent and autonomous solutions, NIIT’s program lands at a critical juncture. The course promises a project-heavy, mentor-led learning path, targeting professionals fluent in programming languages like Python, Java, JavaScript, or .NET.

“Agentic AI represents a new frontier in enterprise transformation, where software doesn’t just assist, it acts,” said Pankaj Jathar, CEO of NIIT Limited. “As organizations adopt autonomous systems across domains, the need for professionals who can design and operate these systems safely and effectively is critical.”

Beyond chatbots: Why Agentic AI matters

The move from static machine learning models to agent-based architectures signals a shift in how artificial intelligence will impact industries. Where traditional AI systems focus on narrow tasks, like predicting churn or classifying images, agentic systems can reason, plan, and operate independently, interacting with tools, APIs, and real-world systems.

Industry forecasts reinforce this urgency:

• McKinsey pegs the value addition of generative AI at up to USD 4.4 trillion, with agentic AI expected to claim a substantial slice of that pie.

• Deloitte expects that by 2025, a quarter of GenAI-using companies will pilot agentic systems, rising to half by 2027.

• Capgemini suggests only 15% of business processes are currently semi- to fully autonomous, but this could hit 25% by 2028.

These figures indicate not just an opportunity, but a skills gap. NIIT aims to plug that gap.

From learning to doing: Inside the 25-week AI journey

NIIT’s program stands out by sidestepping passive learning formats. Instead, it adopts a “learning by doing” methodology. Over 60% of the course involves hands-on project work, where learners build real-world systems and work on complex AI scenarios.

The core curriculum covers:

• Python for AI-embedded applications

• Building conversational agents

• RAG (Retrieval-Augmented Generation) systems

• Autonomous multi-agent workflows

• Capstone project on enterprise-grade Agentic AI systems

Participants also get exposure to leading-edge AI stacks like LangChain, LlamaIndex, LangGraph, Langfuse, Guardrails AI, Azure AI Foundry, and more. This gives them the technical fluency needed to deploy systems that not only respond to queries but make decisions, plan workflows, and perform tasks autonomously.

By the end of the program, graduates will have a deployable portfolio featuring applications like compliance agents, financial analysts, or virtual event planners—demonstrating their readiness for enterprise-scale deployment.

Skilling up for India's AI ambitions

This initiative aligns with India’s national goal to become a global artificial intelligence hub. NIIT’s structured learning path doesn’t just focus on technical skill-building—it also integrates core aspects of AI governance, orchestration, and ethical design.

With sectors like finance, IT, manufacturing, and customer support pushing for automation at scale, there’s rising demand for engineers who can think beyond code and factor in real-world constraints like safety, scalability, and enterprise integration.

“Through this program, NIIT is creating a skilled talent pool ready to meet that challenge,” Jathar emphasized.

Enrollment opens for digital learners

The Building Agentic AI Systems program is available on NIIT’s digital learning platform from 7 November 2025. Enrolled engineers will exit the course not just with new knowledge, but with project experience, technical credentials, and industry-ready portfolios to support their transition into AI-driven roles.

For developers eager to work on systems that do more than just predict, this could be their on-ramp to the future.