Beyond Generative: What Is Agentic AI?
Most people are now familiar with generative AI, like the large language models (LLMs) that can write text or create images based on a prompt. Agentic AI is the next step. Instead of just reacting to a prompt and creating a single output, agentic AI is designed
to be proactive and autonomous. It can be given a complex goal, break that goal down into multiple steps, use different tools and systems, and execute a complete workflow with minimal human intervention. Think of it as the difference between an AI that can write a marketing email and an AI that can write the email, send it, track open rates, and then adjust the next email campaign based on performance, all on its own. It doesn't just generate content; it takes action to achieve an outcome.
The BCG View: A Market in Transition
According to BCG's analysis, while some traditional IT service tasks will be automated away, the rise of agentic AI will ultimately expand the market. The consulting group projects that AI-led services could contribute $300-400 billion in industry growth by 2030. Even after accounting for the loss of existing revenue to automation, this represents a net new opportunity of $100-200 billion for technology services firms. The demand is already building, with BCG's surveys revealing that about a third of enterprises are already scaling agentic AI deployments and look to service providers to help them build and implement these complex systems. This marks a significant shift from a few years ago when most companies reported getting minimal value from their AI experiments.
From Taking Orders to Orchestrating Outcomes
The new work created by agentic AI will look different from traditional IT outsourcing. Instead of simply providing manpower for coding or system maintenance, tech services firms will be called upon for more strategic tasks. The key opportunities lie in designing, building, deploying, and running these agentic solutions. This includes everything from initial use case design and agent workflow engineering to integrating the AI agents with core enterprise systems like ERP and CRM platforms. In essence, the role of the service provider evolves from an executor of tasks to an orchestrator of autonomous systems, managing fleets of AI agents to achieve business goals for their clients.
New Job Titles for a New Era
This evolution will naturally reshape the workforce, creating a host of new roles that didn't exist a few years ago. BCG's report notes that the challenge isn't a lack of talent, but a need to redeploy and reskill existing employees. The firm identified 40 distinct 'Applied AI' roles that current tech professionals can transition into. A data scientist might become a 'forward-deployed engineer' who embeds with a client to build custom AI workflows, while a DevOps engineer could evolve into an 'AI Ops engineer' responsible for the reliability of AI systems. Other new titles emerging across the industry include 'AI Agent Architect', 'AI Orchestrator', and 'Agent Supervisor', who manages AI agents much like a human team lead. The focus is shifting from pure technical skill to a blend of systems thinking, business acumen, and governance.
The Challenge and Opportunity for Indian IT
For India's massive technology services sector, this represents both a disruption and a significant opportunity. While agentic AI will automate certain lower-level tasks, it opens the door to higher-value, outcome-based work that clients are increasingly willing to pay for. The report from BCG highlights that the talent to deliver this work largely already exists within these firms. The key to capturing this new market will be strategic reskilling and a shift in business models. Firms that proactively build capabilities in agentic workflow design, AI governance, and multi-agent systems will be best positioned to lead the next wave of growth. Those that wait risk being left behind as their clients push ahead with adopting autonomous systems.
