By: Marc Sommerer and Praveen Krishnan
Last updated : November 12, 2025 8:24 am
India’s specialty chemicals industry accesses approximately $35 billion in raw materials annually, yet its procurement capabilities remain substantially behind global best practices
The specialty chemicals industry needs to use digital and analytics to sharpen its procurement and supply chain functions, gaining resilience and competitiveness.
India’s specialty chemicals industry accesses approximately $35 billion in raw materials annually, yet its procurement capabilities remain substantially behind global best practices. In a deeply technical sector with limited market data, this gap represents both a vulnerability and an untapped opportunity.
As the industry in India makes its way from $50 billion today to a projected $70 billion by 2030, it needs to sharpen the procurement and supply chain functions using digital and analytical capabilities. The economics are compelling: Global chemical leaders achieve 5 to 10 percent year-on-year savings through strategic procurement, supplier collaboration, and agentic AI enablement.
AI-driven rewiring of sourcing and supply chain functions can build resilience, open up a source of value creation, and enable companies to be more competitive in the future.
Key problems of procurement and supply chain functions
Foremost is a perception problem: Indian chemical companies still view procurements as a tactical executor rather than a strategic asset.
Further, given the technical nature of specialty chemicals, companies require a deep understanding of raw material markets, cost drivers, and suppliers to be able to distill actionable insights. Although more than three out of four procurement officers (CPOs) believe they can create additional value with the help of external intelligence, 80 percent of organizations lack the digital and analytics capabilities necessary to unearth such intelligence.
Data is also disjointed — for example, the transport management and enterprise resource planning systems are often not integrated, leading to value leakage.
This makes negotiations less fact-based, a particularly pressing problem amid global volatility, such as caused by heavy tariffs, and over-reliance on a few geographies — 80 percent of specialty chemicals in India are imported, with 36 percent coming from China alone.
In the AI era, procurement category managers need data and analytical fluency, which is lacking in traditional talent pools. Additionally, most Indian specialty chemical players face structural disadvantages in supplier negotiations, as over 70 percent generate revenues below Rs 3,000 crore, limiting their leverage on both raw material pricing and logistics costs.
Four ways agentic AI can tide over the problems
Specialty chemicals players must make procurement and supply chain functions a frontrunner in value creation.
The foundation for such a transformation lies in strengths that are deceptively simple yet difficult to build: The right organization structure, the ability to attract and retain top talent with deep category expertise, and a basic level of data hygiene. Once these core aspects are robust, Indian companies can take cues from best-in-class organizations and make four fundamental shifts.
Invest in integrated data systems: Driving a step change in procurements will begin with creating an integrated data lake and maintaining rigorous data discipline. This way, previously-disjointed sources are combined and real-time information becomes available.
Scale up agentic AI models: With robust data infrastructure in place, forward-thinking companies are deploying agentic AI systems capable of perceiving their environment, making decisions, and taking action across three critical domains.
First, agentic AI can help automate supplier discovery, analyze proposals, conduct negotiations, and draft contracts. One specialty chemical buyer developed a pricing intelligence engine by bringing together supplier cost models, competitor import-export data, and commodity indices. When paired with a generative AI coach that offered live prompts during negotiations, the system delivered 7 to 10 percent savings. Another player achieved 90 percent accuracy in price forecasting for acetic acid, generating 3 to 5 percent in additional savings.
Second, it aids in demand prediction and planning. AI-driven demand prediction models are achieving 80 percent-plus accuracy, fundamentally reshaping sales and operations planning. One Indian specialty chemical manufacturer was able to compress domestic delivery timelines to under eight hours.
Finally, agentic AI allows for inventory optimization and resilience. A consumer sector company in India used an agent to identify aged stock and automate decisions, such as whether to use, liquidate at a discount, or write off inventory.
Reduce risks in the supply chain: Data-led systems can flag supply chain vulnerabilities. For instance, a commodity chemicals producer employed an AI agent to spot single-source dependencies and list alternative suppliers. A leading Asian steel manufacturer combined satellite imagery, GPS data, and agentic AI to zero in on delivery bottlenecks and cut transportation time by over 40 percent.
Prioritize capability building and change management: Technology alone will not suffice, especially as procurement buyer and planning manager profiles evolve. Leading organizations are selecting high-potential individuals for intensive AI training and creating centers of excellence responsible for broader capability building. These certified professionals also serve as the organization’s radar for emerging technological developments.
Companies that shake up procurements — strengthening core operations and deploying agent-based AI where relevant — can create long-term advantages, such as cost efficiency, resilience, and faster response times. This can not only boost annual savings, but also help the industry in India keep pace with best-in-class organizations worldwide.
(Praveen Krishnan is a Partner in McKinsey & Company’s Bengaluru office, and Marc Sommerer is a Partner in the Munich office.)