In an era marked by geopolitical turmoil, natural disasters, pandemics, and supply chain disruptions, procurement teams are struggling to adapt swiftly. Traditional methods—manual supplier evaluation, fixed contracts, and spreadsheet-based spend analysis—are proving insufficient. A new wave of artificial intelligence (AI) tools now offers real-time flexibility: automating supplier searches, assessing contract risks, predicting demand, and even signaling geopolitical shifts, often within minutes instead of weeks.
Supplier discovery on an enormous scale
Historically, sourcing reliable alternative suppliers could take months. McKinsey cited a fitness equipment manufacturer that identified 90 potential suppliers, many from previously overlooked fields, in just three days due to AI technologies. Another vendor reported reducing supplier search times from approximately 90 days to mere hours.
Spend visibility: evolving from reports to strategic recommendations
It’s not merely about speed—it’s about insight at scale. Generative AI tools now analyze spending data and automatically highlight savings and compliance issues. Research from AI at Wharton indicates that weekly usage of generative AI in procurement surged by 44 points from 2023 to 2024, reaching 94% adoption among procurement executives.
Real-time risk assessment
Procurement risks now encompass more than just supplier financial health. They include labor violations, environmental infractions, abrupt policy shifts, and logistical failures. AI tools now combine multi-channel data, credit assessments, customs holdups, and brand sentiment to issue early alerts.
Demand forecasting and adaptable contracts
The days of procurement relying on last year’s statistics are over. AI-integrated forecasting draws on market signals, demand fluctuations, and inventory depletion rates to foresee shortages or surpluses. This enables dynamic contracting, locking in volumes and prices based on predictions, with automated triggers for renegotiation.
Unilever reportedly reduced supplier search durations by 90% while enhancing supplier diversity through AI tools. McKinsey observes an average 20% reduction in procurement costs and halved cycle times with AI implementation. Users of Spendflo report cost cuts of up to 40%, threefold improvements in compliance monitoring, and a shift in employee focus toward strategic tasks. EY/Wharton found that weekly generative AI application among procurement leaders escalated to 94%. The adoption of generative AI in Indian enterprises stands around 36%, with an additional 46% planning to implement it within the next 18 months.
India’s emerging momentum
Indian enterprises are hastening their efforts to catch up or take the lead. A CII‑Protiviti survey shows that 51% of Indian companies are accelerating AI adoption, with another 32% planning a gradual rollout. IBM reported that 59% of Indian firms have deployed AI, the highest percentage among the countries surveyed. Qlik reports that 79% of Indian enterprises are aware of AI, with 57% recognizing AI as central to their strategies, surpassing global figures. Financial institutions and tech giants are investing ₹2,000 crore into AI hubs like Infibeam in Gujarat.
Nevertheless, execution remains challenging. Infosys warns that costs and data readiness issues are delaying implementations, while Qlik emphasizes that talent shortages and governance challenges continue to impede scaling efforts.
India’s public procurement portal, Government e-Marketplace (GeM), provides a compelling example. By utilizing machine learning and data analytics, GeM achieved a median price savings of 9.75% across orders totaling ₹13.6 lakh crore by May 2025; it also received a national award for its AI application in public services.
The road ahead: Transitioning from mere tools to comprehensive transformation
Research and industry publications are unanimous: simply purchasing AI software is not enough. Procurement teams must reassess their strategies.
EY & Wharton recommend:
1. Identify pain points like contract delays or supplier risks.
2. Develop robust data infrastructures to enable analytics.
3. Design AI tools with user-friendliness in mind; procurement professionals should be eager to utilize them.
Deloitte underscores the importance of governance and bias mitigation. AI pilot projects must be constructed to identify biased outcomes, insecure data management, or misdirected sourcing decisions.
EY/Protiviti/Qlik all stress the need for upskilling procurement teams to enhance their understanding of data and AI tools, enabling staff to oversee automated systems and respond strategically.
Areas of promise and caution
Promise:
Early adopters are experiencing cost reductions of 20-40%, halved cycle times, and significant compliance enhancements. In India, collaborative efforts between public and private sectors (e.g., GeM’s success) illustrate how AI-driven procurement can save taxpayer money and promote equity. Advancements in vernacular LLMs (like JioBrain, Sarvam) are expected to bring these tools to local supply networks.
Caution:
Data barriers and low-quality information continue to hinder many companies. Governance frameworks are developing slowly; only about 23% of Indian firms have established AI ethics safeguards. High initial costs and unproven ROI are causing hesitancy among CFOs and procurement leaders worldwide.
What a successful transformation entails
In organizations pursuing smart procurement, several distinct characteristics emerge:
- Cross-disciplinary teams that combine procurement, IT, and legal expertise to pilot AI tools with well-defined goals.
- Clear data lakes that amalgamate ERP systems, contract archives, external risk feeds, and payment histories, all precisely tagging suppliers and contracts.
- Governed deployments that incorporate oversight on model performance, privacy, bias, and audit trails.
- Change management initiatives that train procurement users to interpret alerts, override automations, and maintain communication with suppliers.
The strategic benefits
When executed thoughtfully, AI procurement delivers more than just internal efficiency:
- Strategic agility, allowing for swift supplier adjustments in the face of disruptions
- Cost resilience, through identification of savings and enhanced negotiation tactics
- Reputation management by monitoring ESG and compliance, thus avoiding scandals
- Economic impact: GeM’s savings nearing ₹1 lakh crore benefit public finances.
Conclusion
Procurement is no longer just about purchasing goods. In today’s fragmented global context, it represents a pivotal strategic function. When deployed effectively, AI can transform procurement from a reactive, transactional operation into a proactive, foresight-driven process capable of identifying risks, uncovering savings, and gaining competitive sourcing advantages.
However, this transformation will demand more than technology alone. Indian organizations must invest in data infrastructure, team expertise, governance standards, and strong leadership. Those who succeed won’t merely refine their processes—they will redefine how decisively they operate. In terms of supply chains, such decisiveness can make all the difference.
The author is Gaurav Baheti, Founder & CEO, Procol.
Disclaimer: The opinions expressed are solely those of the author, and ETCIO does not necessarily endorse them. ETCIO shall not be liable for any damage caused to any individual or organization, directly or indirectly.
