Manuel del Val, Managing Director at Green Mowers (Civil Engineer)

Burgos, February 11, 2025.- Agentic AI is a sophisticated class of artificial intelligence systems designed to act autonomously, make decisions, and perform complex tasks without direct human intervention. Unlike traditional AI models that follow predefined rules or generative AI that focuses on content creation, agentic AI emphasizes goal-oriented behavior and adaptive decision-making

Key Features of Agentic AI

1. Autonomy: Agentic AI systems can set goals, make decisions, and act independently

2. Adaptability: These systems learn from experiences and feedback, refining their performance over time

3. Reasoning: Advanced algorithms and language models guide the AI in understanding tasks and crafting solutions

4. Collaboration: Multi-agent systems can work together to solve complex problems more effectively

Impact on Work

Agentic AI is poised to transform various industries and work processes:

1. Automation of Complex Tasks: Agentic AI can handle intricate, multi-step processes, potentially reducing the need for human involvement in certain roles.

2. Enhanced Efficiency: By automating repetitive tasks and optimizing workflows, agentic AI allows teams to focus on more strategic initiatives

3. Transformation of Customer Service: AI agents can proactively identify issues, understand customer intent, and resolve problems without human intervention

4. Reshaping of Management Roles: Middle management functions like overseeing workflows and resource allocation may be increasingly handled by AI systems

5. Impact on Job Market: While agentic AI may displace some roles, it also creates new opportunities in AI development, oversight, and strategic planning

6. Improved Decision-Making: In fields like finance and healthcare, agentic AI can analyze vast datasets and make decisions with high precision.

As agentic AI continues to evolve, it promises to drive innovation and efficiency across industries. However, its implementation also raises important ethical considerations and challenges related to workforce adaptation and the changing nature of human-AI collaboration in the workplace.