Agentic AI represents a once-in-a-generation opportunity for Indian enterprises to leapfrog legacy constraints and build adaptive, intelligence-driven organisations.
Every decade brings a technological shift that redefines how businesses compete. Today, that shift is agentic AI. It moves artificial intelligence from generating insights to executing outcomes at scale and with increasing autonomy.
Agentic AI is not just a tool; it is a teammate. Unlike earlier systems that respond to prompts or automate isolated tasks, agentic AI systems can act on intent. They plan, coordinate across systems, and execute workflows within defined guardrails. It enables enterprises to build cognitive digital brains, in other words intelligent systems that think, adapt, and act responsibly. In effect, it is a step change in how work gets done.
For India, this transition comes at a critical moment. The country’s ambition to become a $10-trillion economy depends on sustained gains in productivity, innovation, and speed to market. If used responsibly, generative AI alone could add $675 billion to the economy by 2038 as per research. Agentic AI will amplify this by creating new value chains, reinventing workflows, and enabling enterprises to scale decision-making across functions.
Encouragingly, Indian enterprises are already moving beyond experimentation. Over 40% of organisations are actively deploying AI agents across multiple functions, and nearly a quarter are redesigning end-to-end processes with AI at the coreas per Accenture’s Pulse of Change survey.
Early use cases across sectors are demonstrating tangible business impact. A leading Indian retailer’s finance function is leveraging autonomous agents to manage complex tasks, resulting in accurate and timely invoice payments, projected to deliver up to 35% cost savings and accelerate payment processing by 25–40%. A major Indian bank is using agentic AI to empower employees to query thousands of products, processes, and policy documents through a conversational interface, while a conversational portfolio management platform advises customers on risk profiles and investment strategies.
The shift is clear as AI has moved beyond pilots and is starting to reshape enterprise operating models. However, the path to scaling AI and agentic AI is not without challenges.
The biggest constraint is not the technology itself. Models and compute are advancing rapidly. The real barriers lie in data, operating models, and organisational readiness. Many enterprises in India continue to grapple with fragmented data, inconsistent governance, and legacy processes not designed for AI-driven execution. Without clean, connected, and trusted data, even the most advanced systems cannot deliver sustained value.
Talent is the second critical bottleneck. This gap between ambition and readiness underscores a simple truth that scaling AI and agentic AI requires enterprise-wide transformation, not just technology adoption.
To move from early success to sustained impact, organizations in India should focus on four priorities.
Anchor AI in business outcomes: Treat agentic AI as a strategic transformation, not a plug-and-play upgrade. Define clear business objectives whether it is faster time to market, improved customer experience, or new revenue streams, and align AI deployment with driving measurable growth.
Build a robust data foundation: Research shows that nearly 30% of India’s C-suite cite limitations in data or technology as the top obstacle. Agentic AI depends on a unified, governed data layer that allows both humans and machines to operate with a consistent view of the business. Moving from siloed data to interoperable, trusted systems is essential for scale.
Invest in talent at speed and scale: AI is reshaping work faster than skills are evolving. As per estimates, four in five technology engineers will need to continuously learn new skills as AI evolves. Organisations will also need new roles from agent architects to AI operations specialists as well as leaders who can guide AI-led reinvention. Learning must shift from episodic training to continuous capability building.
Build trust by design: Greater autonomy introduces new risks, including bias, opacity, and unintended outcomes. Enterprises need to embed responsible AI principles such as fairness, transparency, and accountability into systems from the outset. Trust will be a key differentiator in determining which organizations scale successfully.
Despite the challenges, the outlook remains strong. Nearly nine in 10 C-suite leaders in India plan to increase their AI investments in 2026, with 69% viewing AI as more beneficial for revenue growth than for cost reduction as per a survey.
Agentic AI represents a once-in-a-generation opportunity for Indian enterprises to leapfrog legacy constraints and build adaptive, intelligence-driven organisations. The companies that succeed will be those that combine bold ambition with disciplined execution, investing not just in technology, but equally in data, talent, and trust.
(The author is senior managing director & lead – India Business, Accenture. Views are personal.)