Agentic AI: India's Endeavor in Autonomous Intelligence

Context

Microsoft Chairman and CEO Satya Nadella recently stated that the deployment of Artificial Intelligence (AI) and the applications of Agentic AI are accelerating rapidly in India.

What is Agentic AI ?

• Agentic AI is an advanced form of artificial intelligence that focuses on autonomous decision-making and execution.
• It involves AI agents—machine learning models—that mimic human decision-making processes to solve problems in real time.
• While traditional AI primarily reacts to commands or analyzes data, Agentic AI, with minimal human intervention:
• Can set goals
• Can plan
• Can execute tasks
• The term 'Agentic' refers to 'agency,' meaning these systems have the ability to act independently in a goal-oriented manner.

Key Components of Agentic AI

• Perception: Agentic AI begins by perceiving its environment and gathering information from various sources, such as sensors, databases, and user interfaces.
• Reasoning: Using Large Language Models (LLMs), Agentic AI analyzes the collected data to understand the context, identify relevant information, and generate potential solutions.
• Planning: Agentic AI then uses the gathered information (data) for planning, which includes setting goals, breaking them down into smaller steps, and finding the best way to achieve them. 
• Action: Based on its plan, the agentic AI takes action, which may involve completing tasks, making decisions, or interacting with other systems.
• Reflection: After taking action, the AI ​​learns from the results. It evaluates the success or failure of its actions and uses this feedback to adjust its plans and actions in the future.

Key Differences Between Agentic AI and Generative AI

• Agentic AI is built upon Generative AI (GenAI) technology, utilizing Large Language Models (LLMs) to operate in dynamic environments.
• While generative models focus on creating content (text, images, or code) based on learned patterns, agentic AI extends this capability by applying generative output to specific, goal-oriented tasks and autonomously completing complex tasks.
• For example, generative AI models like OpenAI's ChatGPT can create text, images, or code, but an agentic AI system uses these to autonomously complete specific tasks and make decisions with the help of external tools, allowing machines to actively interact with their environment.

Conclusion

Agentic AI is paving new paths for autonomous intelligence in India. While generative AI focuses on creation and generation, agentic AI transforms this into autonomous decision-making and task execution. This technology has the potential to deliver efficient, faster, and goal-oriented solutions across industries, finance, healthcare, and everyday processes.