Majority of Enterprises have Dedicated AI Budgets with 62% Experimenting with Agentic AI: Nasscom Nearly 62 per cent of global enterprises are currently experimenting with such AI agents, ranging from proof-of-concepts to scaled pilots.

88 per cent of enterprises now have dedicated AI budgets, with two-thirds of them allocating over 15 per cent of their tech budgets specifically toward AI initiatives, according to Nasscom's latest report titled 'Enterprise Experiments with AI Agents – 2025 Global Trends.'

At a time when AI is shifting from passive analytics to active agents of execution, the report captures the foundational shifts underway within the enterprise ecosystem. The study draws on responses from over 100 global enterprises across 8 -9 major regions and over 10 industries, offering a landscape view into how businesses are transitioning from early-stage Generative AI applications toward more goal-oriented, human-plus-AI agentic systems.

This shift is reflected in the emergence of specialized AI teams, greater focus on GenAI platforms and tooling, and infrastructure readiness. However, while awareness of GenAI is high, actual use of advanced models remains limited. Only about half of surveyed enterprises are fine-tuning large language models (LLMs) or foundation models for their own applications.

Crucially, the move toward agentic AI is gaining traction. Nearly 62 per cent of global enterprises are currently experimenting with such AI agents, ranging from proof-of-concepts to scaled pilots. However, the nature of these experiments is still largely internal, focused on task-level automation with human oversight, with 76 per cent of enterprises positioning their own IT operations as "client zero." External-facing use cases, such as customer service, are still limited, with only 31 per cent of companies indicating active usage in those areas.

Sangeeta Gupta, Senior Vice President and Chief Strategy Officer at Nasscom, said, "We are at the tipping point of the AI maturity curve where enterprises are no longer just experimenting with AI, but actively reimagining their architecture, workflows, and teams to build agentic systems. AI agents represent the next evolution of enterprise AI one that requires philosophical shifts in how we view work, intelligence, and autonomy. But to scale responsibly, trust, data readiness, and human oversight will be non-negotiable."

Despite growing confidence, the study reveals that deployment remains largely incremental. A significant 77 per cent of enterprises are adopting agentic AI systems with a "human-in-the-loop" design, reflecting an awareness of the need for constant oversight, adaptability, and contextual judgment.

While 46 per cent report experimenting with autonomous agents, IT operations, customer service, and internal HR and finance functions are leading experimentation grounds. Manufacturing enterprises are moving faster than services in adoption, with AI-powered robotics, quality control, and process agents showing strong traction.

The business case for agentic AI appears strongest in real-time decision-making and operational agility. More than half the enterprises see such systems as critical enablers for translating information into intelligence and rapidly responding to shifting market dynamics. Only 39 per cent believe that agentic systems will meaningfully free up human bandwidth for higher-order work, suggesting that, at present, these systems may augment rather than replace existing workflows.

Data remains the cornerstone of AI efficacy. With 68 per cent of companies focusing on strengthening data governance and management, and 62 per cent working on integrating structured and unstructured data flows, enterprises are laying the groundwork for scalable, reliable agentic solutions.

However, the path forward is marked by both technical and structural headwinds. Data privacy, risks of self-learning systems, and the absence of cohesive regulatory frameworks continue to be cited as top adoption barriers.