By Manoj Nagpal, Managing Director, OpenText India
Shipping containers might move across oceans, but today supply chains are judged by how quickly decisions move across systems. In India, exports reached $602.64 billion between April to December 2024. This means even minor delays can translate into missed opportunities, especially when a nation is aiming to position itself as a reliable global manufacturing hub. Supply chain leaders must recognize that it is not a matter of capacity at all. The actual concern is responsiveness.
Legacy infrastructure, lack of coordinated data, a siloed approach, and a chronic skills gap (talent shortage) have all contributed to decelerated decision-making at a time when agility is of utmost importance.
The recent trade restrictions have renewed the push towards the AtmaNirbhar Bharat mission. In the current climate, it is imperative that the manufacturing industry and the related supply chain develops at a much larger scale. The availability of skilled workforce will be at the center of this growth and new technologies such as Agentic AI can help bridge the skill gap through directed and focused onboarding of the workforce.
For example, a missed vessel in Chennai can disrupt stock levels and marketing cycles for retailers in Europe almost instantly. Instead of investing in large-scale IT overhauls leaders need to find a smarter way to bridge these gaps. Something that works with existing systems while keeping pace with global volatility. And here AI agents give a practical solution. By sitting atop legacy infrastructure, they bring decision-making speed, autonomy, and adaptability that traditional systems lack. This allows enterprises to stay ahead in an unpredictable supply chain space.
Case for AI agents in the supply chain
Traditional supply chain systems were built for stability. They could capture data but rarely act on it, leaving managers to manually firefight delays and shortages. Disruption management, in that sense, was reactive at best.
Agentic AI changes this equation through dynamic alerts and autonomous responses. Autonomous agents can predict the ripple effects of disruption and instantly reconfigure sourcing routes or delivery schedules, containing the impact before it spreads. Moreover, warehouses that typically operate on disconnected systems often end up with too much or too little stock. AI agents can just keep an optimum stock level in real time (just in time inventory), automate the replenishment and avoid human error, and get the supply level to parallel demand.
The same flexibility that AI can provide is seen within the manufacturing plant itself, where brittle production schedules typically come undone with the slightest hiccups. AI can adjust plans based on both the expected inflows of raw materials and the ultimately forecasted consumption. Acting as collaborative agents, these systems also enable smoother data sharing between businesses and suppliers, driving more accurate forecasts and coordinated responses across the chain. This shift from rigidity to adaptability explains why the AI in the supply chain market in India is projected to reach $ 3,277.4 million by 2030.
The human lens is equally important
For supply chain leaders, the real value of AI agents lies in their ability to amplify human judgment, not erase it. Firms are investing in these intelligent assistants to handle high-volume, repetitive tasks, allowing employees to focus on high-impact decisions. In India, this shift is greatly visible. According to a study, around 93% of firms are planning to use AI agents within the next year to enhance workforce productivity. This strong interest highlights a clear belief that these agents are meant to augment human efforts rather than replace them. AI aids in tasks such as translating delivery instructions and onboarding new employees, reducing errors, and preserving historical knowledge.
However, there is increased market demand for hybrid roles that can interpret data-led understanding and cross-functional decision-making. Jobs such as planners and schedulers are being expedited upward as well, configuring broad oversight to facilitate smooth continuity across procurement, production, logistics, and forecasting. Decision-making is also moving higher in organizations. Instead of independent experts, integrated judgment now exists with the Chief Operating Officer and team of business operations leaders. Companies are adopting a more human-centered approach to integrating technology into their operations, recognizing that while machines optimize scale and speed, judgment, creativity, and accountability are unique human attributes.
Seizing India’s supply chain moment
This moment is defining for India. Its size in manufacturing, changing digital infrastructure, government initiatives in AI, and digitization of supply chains present the country with a unique opportunity to lead. However, it will require more than simply adopting these technologies. It will include developing interoperable platforms, establishing clear data-sharing protocols across sectors, and training a skilled workforce that has both domain knowledge and expertise in new-age technologies. Ultimately, generative capabilities in supply ecosystems will result in predictive coordination, where every disruption becomes a data point from which the ecosystem learns. This means creating a space that brings together startups, enterprises, and regulators to set standards that promote flexibility and responsible scale.