A new Nasscom report predicts that so‑called “agentic AI spending” will create hybrid work teams and open massive revenue streams for India’s tech services industry.
The term “agentic AI” may sound like jargon, but it could soon become a buzzword in boardrooms. A fresh study by India’s tech lobby Nasscom and consulting firm McKinsey argues that intelligent, self‑governing AI agents will open up new pools of corporate spending worth between $300 billion and $500 billion. By taking on complex tasks—coordinating workflows, reasoning through problems and learning from experience—these systems could transform how businesses operate. Agentic AI spending refers to the investments companies will make to build, deploy and manage these autonomous systems. The potential windfall is particularly significant for India, which has a large base of tech talent and companies eager to sell AI‑powered services worldwide.
What is agentic AI?
Unlike traditional AI tools that handle discrete tasks (translation, image recognition, etc.), agentic AI refers to systems that can plan, adapt and collaborate autonomously. They don’t just execute commands; they set goals, break them into sub‑tasks and adjust based on feedback. Imagine a virtual project manager that can assemble a team, assign tasks, monitor progress and adjust deadlines—all with minimal human input. Agentic AI spending will grow as companies integrate these agents into their workflows. Nasscom’s report says these agents could function as “digital employees” embedded in software, working alongside human colleagues.
Key findings of the report
The “Future of Technology Services: Leading with AI” study outlines several projections:
New spending pools: Agentic AI spending could unlock $300–$500 billion in additional enterprise technology spending, especially in India’s outsourced tech services sector.
Hybrid teams: The combination of AI agents and human workers will become the norm. AI handles routine and coordination tasks while humans focus on creativity and oversight.
Productivity boost: Companies adopting agentic AI will see significant productivity gains, letting them cut costs while expanding service offerings.
Talent upskilling: To capitalize on the opportunity, India must invest heavily in training its workforce to design, deploy and monitor agentic systems.
Nasscom and McKinsey argue that agentic AI spending will not replace existing IT services; instead, it will create new categories. For example, clients might hire firms to implement “AI managers” that oversee supply chains or manage marketing campaigns. These engagements could be more lucrative than traditional staff augmentation, as they involve licensing intellectual property and ongoing support. The report also notes that early adopters may see disproportionate benefits, reinforcing the importance of moving quickly.
How agentic AI differs from current AI tools
Today’s AI products are often narrow. They excel at classification, prediction or generation but struggle to orchestrate multi‑step processes. Agentic AI aims to bridge that gap by integrating reasoning modules, planning algorithms and reinforcement learning.
For example, an AI assistant might not only draft a marketing plan but also schedule meetings, delegate tasks to content creators and manage the budget. This level of autonomy requires robust safeguards to ensure agents align with human goals and don’t make ethically questionable choices. As we’ve noted in our deep dive on ChatGPT’s new AI Agent, companies like OpenAI are already experimenting with this new generation of agents. Agentic AI spending therefore includes investment in ethics, security and governance frameworks.
Implications for businesses
Companies that adopt agentic AI could reduce reliance on mid‑level project managers and coordinators. However, they must overhaul workflows to integrate digital agents effectively. The Nasscom report notes that businesses should focus on:
Investing in R&D: Developing proprietary AI intellectual property to differentiate services.
Rethinking service offerings: Embedding agentic capabilities into existing products and designing new solutions around them.
Upskilling talent: Training employees to work alongside AI and transition into roles that require judgment and domain expertise.
Governance: Creating policies to guide how agents make decisions, handle sensitive data and interact with external systems.
Why India could lead in agentic AI spending
India’s IT services industry already powers the back offices of global corporations. Its large pool of engineers and lower labor costs give it an edge in building and deploying agentic AI. The report suggests that India could become a hub for hybrid AI‑human work models. Government support may be needed to create standards and funding for research. If successful, agentic AI spending could propel India’s tech sector to the forefront of global innovation. India’s focus on English language skills also positions it well to build agents that interface with Western clients.
Challenges and cautionary notes
Ethics and accountability: Autonomous agents must be designed with guardrails to prevent misuse and bias.
Regulation: Governments will need to address liability when AI makes decisions that affect people.
Workforce impact: As with other forms of automation, some jobs may vanish while new ones emerge.
Interoperability: Different agent systems must communicate and coordinate, necessitating standards.
How businesses can capitalize on agentic AI spending
To tap into this opportunity, companies should begin experimenting with pilot projects. Start with internal processes like expense approvals or meeting coordination. Measure productivity gains and employee satisfaction. Then scale up to customer‑facing tasks. Partner with universities or startups to develop proof‑of‑concept agents. Keep an eye on emerging standards—joining industry consortia can shape regulations and ensure interoperability. Finally, invest in continuous learning. As agentic AI evolves, so will the skills needed to manage it.
