Agentic AI is a significant advancement in artificial intelligence (AI) that transcends traditional content generation capabilities. It involves AI systems that can operate autonomously, making decisions and taking actions on behalf of users without requiring continuous human input. With the increasing demand for advanced AI applications, several job opportunities are emerging in this field. Against this backdrop, companies across sectors are seen posting jobs related to agentic AI, finds GlobalData, a leading data and analytics company.
Sherla Sriprada, Business Fundamentals Analyst at GlobalData, comments: “Agentic AI is at the forefront of GenAI innovation, poised to transform human-machine interactions and significantly enhance operational efficiencies. Organizations are increasingly prioritizing the integration of AI systems, actively seeking candidates with specialized expertise in AI agents to drive their initiatives forward.”
An analysis of GlobalData’s Job Analytics Database reveals an increase in job postings focused on agentic AI across sectors including technology, retail, automotive, and pharma.
Technology industry is looking at initiatives such as new AI Agent features, AI system optimisation, AI agents for dangerous capabilities like hacking or exploiting security vulnerabilities. Technology companies are looking at hiring professionals with experience in agentic workflows and retrieval-augmented generation (RAG) systems, AI-powered agents for applications such as virtual assistants, customer service bots.
Retail companies are hiring individuals with experience in deploying smart AI agents, optimizing LLM-based agents for tasks like knowledge grounding, multi-step reasoning, decision-making, and LLMs for AI agents unique social AI tasks and applications.
Automotive industry is looking to hire professionals with experience in developing generative and foundational AI-based agent systems for connected mobility applications.
Pharma companies are hiring individuals with experience in leveraging AI agents to automate tasks such as biomarker extraction from research papers, information gathering from internal and external documents, summarizing key research concepts. Furthermore, developing AI agents that autonomously plan, execute and optimize complex chemistry and biology workflows.
Sriprada concludes: “As agentic AI continues to evolve, its impact will extend far beyond automation. The future belongs to businesses that embrace AI not just as a tool, but as a strategic partner in driving transformation across technology, retail, automotive, and pharmaceutical sectors.”
