Agentic AI in the Enterprise Training in India

This course introduces participants to Agentic AI – AI systems capable of autonomous reasoning, planning, and acting with external tools – and how they can be strategically applied in enterprise contexts. It covers enterprise workflows, automation, decision-making, and knowledge management, enabling participants to build and deploy AI agents that enhance productivity, reduce costs, and drive innovation. The course blends strategic perspectives with hands-on technical labs to provide a holistic understanding.

Welcome to the official Agentic AI in the Enterprise Training certification program. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge in in India. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 14 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

• Basic understanding of AI/LLM concepts.

• Familiarity with enterprise workflows (finance, HR, operations, IT, or customer service).

• Programming knowledge (Python, APIs, databases) is beneficial but not mandatory.

• Designing autonomous workflows for enterprise tasks.

• Building AI agents that integrate with tools (databases, APIs, enterprise apps).

• Workflow automation using agent frameworks (LangChain Agents, LangGraph, AutoGPT, crewAI).

• Enterprise AI governance and compliance understanding.

• Applied knowledge of AI-driven digital transformation.

By the end of the course, participants will be able to:

1. Explain the fundamentals of agentic AI and its enterprise relevance.

2. Identify high-impact enterprise use cases for AI agents.

3. Design agentic AI workflows that interact with enterprise systems (ERP, CRM, databases, APIs).

4. Integrate multi-agent systems for collaborative decision-making.

5. Apply governance, compliance, and risk management in deploying AI agents at scale.