In a short time, procurement is going through a monumental change—the largest change since the digitization revolution began. Artificial intelligence has been projected to completely change how procurement is done by the year 2026; AI will not only assist procurement but will re-engineer how a buyer develops tenders, how a supplier identifies opportunities, how contracts are negotiated and executed, etc. The vast majority (94%) of procurement executives now use generative AI weekly, compared to just over half (50%) of procurement executives in 2023. With many countries (including India) adopting AI-powered chatbots, we are beginning to see the development of AI-native procurement systems where the combined efforts of AI and human expertise result in producing results that are not possible without both working together.
The magnitude of this transformation is apparent from the numbers alone: The greatest reduction in time to complete procurement tasks (up to 80%) was seen in Oracle's recent research. Gartner has projected that organizations with AI-driven procurement strategies should achieve cost savings of 20% above organizations using traditional procurement methods by the year 2026. McKinsey reports that procurement teams using AI-driven decision-making have already reduced their operational costs by 10% and accelerated the supplier selection process by 30%. For suppliers trying to navigate the Rs 13.60 lakh crore ecosystem of GeM, or Global Procurement Networks, understanding how AI is transforming the way tenders are processed is no longer optional but necessary for competitive survival.
GeMAI: India's First Public Sector Generative AI Chatbot
In May 2025, GeM launched GeMAI as the first generative AI-enhanced chatbot implemented by an Indian government department to assist with public sector purchasing. Designed for use on the Amazon Bedrock platform and built specifically for GeM's purpose, GeMAI uses carefully aggregated data only relating to GeM's offerings to show how AI can enhance the user experience while still preserving the high levels of reliability and security that governments require.
Compared to its predecessor GemMy, which used a fixed set of responses based on a menu system, GeMAI provides a much more robust user experience by interpreting the input from the user as natural language and responding in ways that are relevant to them based on the context of the user's question(s). Users can ask detailed questions regarding procedures for tenders, bids, documents, and navigation using whatever language they prefer rather than being restricted to a predefined set of options found on the menus. Furthermore, responses are generated based on knowledge from GeM-approved sources only; thus, irrelevant information regarding political issues or other non-procurement matters is filtered out from the results.
Through the provision of both text and voice interactivity via 10 Indian languages—English, Hindi, Bengali, Telugu, Marathi, Tamil, Gujarati, Kannada, Malayalam, and Punjabi—GeMAI has drastically expanded the accessibility of government procurement opportunities to sellers operating outside of traditional English-speaking markets. For example, a rural Gujarat micro-entrepreneur can submit queries to the GeMAI system concerning EMD requirements in Gujarati, while a women-led enterprise located in Tamil Nadu can receive notification on tenders in Tamil. The implementation of multiple languages on GeMAI has removed language as a barrier for competent suppliers to gain access to government procurement opportunities, which would have previously excluded them.
GeMAI's underlying technical architecture is designed for maximum reliability and to mitigate the occurrence of AI hallucinations that are prevalent in generative models. It implements input verification for questions that could create political controversy, as well as for questions that do not pertain to GeMAI; in response, both types of inquiries receive a standard rejection response from GeMAI. Moreover, GeMAI has employed an output validation process to validate whether the generated output produced via the GeMAI system is aligned with GeM's official policies and procedures. Since its introduction into the marketplace, GeMAI has experienced a significant increase in user adoption, averaging between 200,000 and 300,000 tokens per day with nearly 1,000 user queries being processed. However, given the current number of registered sellers on GeM (80 lakh), this user adoption continues to represent only a very small portion of the overall potential user base for GeMAI.
The strategic vision for the ongoing development of GeMAI includes the further development of voice interactions, expanding the number of languages supported through existing multilingual partnerships, the ability for users to upload screenshots in order to facilitate the resolution of issues visually, automated ticketing with tracking numbers to facilitate the reporting and tracking of issues, and the integration of GeMAI with existing transactional workflows allowing users to perform transactions and execute related tasks through conversational commands as opposed to navigating complex user interfaces.
How AI Transforms Tender Creation for Government Buyers
AI reduces the time taken from several days to complete workflows of tender preparation by allowing procurement officers to prepare tenders with a higher quality specification and more competitive results.
The greatest impact of AI on procurement workflow is in automating the creation of RFx documents. Procurement officials define their requirements in easy-to-understand language, such as "500 laptops with 16GB of RAM, 512GB of SSD storage, 14" displays, and delivery to 50 sites across three different states," and using natural language input, AI creates a complete Tender Document with all of the required elements, including technical specifications, eligibility criteria, evaluation parameters, delivery terms, and payment schedules. These documents are created using a combination of standardized language that has been previously used successfully on similar tenders, regulatory compliance requirements from applicable laws and regulations, and the use of historical data on procurement prices to establish realistic pricing for the prospective bidders.
The specification optimization function offered by AI allows buyers to create specifications while utilizing market intelligence to identify trends in the number of competitors that respond with bids, to identify typical pricing for products and/or services, and to identify common clarification requests that suppliers tend to ask about the specifications. By using this information, buyers can improve specifications to attract greater competition and create tenders that maximize value and provide adequate supplier participation to ensure that the buyer has multiple suppliers to choose from when making a purchasing decision.
The predictive analysis offered by predictive spend analytics provides support for allocating funding to a budget. Predictive analysis uses historical pricing information from previous similar procurements along with current market conditions and commodity pricing changes to create a forecast of likely pricing outcomes prior to the release of tenders. Additionally, predictive analysis is able to identify seasonal demand fluctuations on the supply side to assist in estimating the amount of funding necessary to conduct a tender. Predictive analysis allows buyers to avoid the embarrassment of having tenders with no bids due to setting the budget too low, as well as overspending due to inaccurately estimating the amount of funding required based on the actual marketplace situation.
Compliance checking refers to verifying that the requirements of a tender document meet the applicable regulations. Compliance checking is performed using AI to automatically validate the draft tender against the necessary procurement regulations and policies, identify missing 'must-have' clauses such as those relating to MSME preferences or requirements created under the Make in India Policy, validate that the evaluation criteria meet the provisions of the GFR, and validate that the delivery and payment terms comply with standard marketplace practices. Using an automated compliance checking process reduces the risk of legal action and eliminates the cancellation of tenders as a result of procedural errors.
AI-Powered Supplier Discovery and Bid Preparation
AI technology is transforming the relationship between suppliers and the way they source relevant tenders, determine their chances of winning a bid, and create a competitive response.
Artificial Intelligence (AI) tender matching algorithms have greater potential than simple keyword searches. Instead of having to continually check hundreds of new tender notifications every day, suppliers will be able to create alerts for suitable tender opportunities that have been identified through the supplier's capabilities, past performance, certifications, and strategic priorities. Tender matching algorithms consider not just the product categories but also the order values generally fulfilled, the geographic delivery capabilities demonstrated, the technical complexities related to the supplier's capabilities, and the buyer's preferences based on ratings/reviews.
The ability to assess the likelihood of winning a tender allows suppliers to channel their resources into those tenders they have the best chance of winning. By analyzing the tender requirements with the suppliers' profile, AI will calculate a probability score based upon the supplier's certification against the tender's requirements, whether the supplier's past delivery times match the tender's expected delivery schedule, whether the supplier's past pricing history falls within the tender's budget, and how the supplier's overall rating compares to the likely competition's. This information provides intelligence to suppliers to eliminate wasted resources on bids that have a low probability of success and will identify the highest potential tender opportunities to which the supplier should apply the greatest effort.
AI-powered document automation helps automate the time-consuming and repetitive process of developing Technical and Commercial Proposals (T/C Proposals). Suppliers enter basic information about an individual tender into the system, and the system automatically populates T/C proposal templates with the necessary certification information from your digital vault, technical specifications that align with your product catalog, past performance evidence that demonstrates capability, delivery timelines that reflect your logistics capabilities, and compliance declarations required by the tender. The uniform structure of bids generated via the automated document generation process ensures consistency across all bids while enabling you to customize content specific to each individual business opportunity.
Competitive intelligence provides insights and information that allow suppliers to optimize their pricing strategies based on previous historical L1 pricing data for similar tenders and the likely price ranges within which most bidders will submit their bids. In addition to this price analysis, AI will also be able to calculate each bidder’s cost position in relation to the market price and provide the information necessary to model different scenarios demonstrating how various price points will influence win probabilities and margin generation. Competitive intelligence is intended to supplement rather than replace a supplier's knowledge and experience when determining optimal pricing for each tender.
Agentic AI: The Next Frontier Beyond Chatbots
As generative AI chatbots like GeMAI have made significant strides in their own right, the arrival of autonomous AI agents in 2026 will signal the next revolution of technology in this area—the ability for AI agents to operate with little to no human intervention.
Category Management Agents will show this on a large scale by employing AI Agents to observe purchasing patterns on an ongoing basis, monitoring when contracts are nearing expiration, whether or not current pricing positions are still competitive, when consumption patterns may indicate a reason to renegotiate a contract, and finally, creating a sourcing event based on an evaluation of the above factors. Procurement will have the ability to run "continuously optimized" by having automated AI agents always overseeing them and performing these types of analyses rather than annually.
Additionally, Supplier Risk Monitoring Agents will serve as alerts to identify and mitigate supply chain disruptions. The AI Agent will monitor real-time feed from a supplier's financial markets, in addition to news and social media channels, to find any signals that may indicate a supplier is in financial distress; monitor the supplier's delivery performance trend for any decline; assess the political and geographical/economic risk profile of the supplier and the country of origin; and notify procurement of a developing crisis prior to it occurring. This represents a major shift in procurement's value proposition from one of reactive crisis management to proactive risk mitigation.
Contract management agents provide tools to deliver automation capabilities for many of the manual tasks associated with gathering and managing contract lifecycles. Contract agents also provide a mechanism to continuously monitor the performance of contracts and detect when contracts that contain similar provisions but with different pricing have been executed on multiple occasions. According to McKinsey, the use of fully autonomous category management agents will deliver a range of improvements (efficiencies) to companies, from automating all types of low-value, non-value-added activities in a typical company's contract management process to ultimately automating the entire category management lifecycle.
Support agents for contract negotiations provide information during the clarification and negotiation phases of the life cycle for an individual project. These support agents provide the historical data showing how successful negotiations have taken place within an industry, the tactics that worked and did not work, and generally have information about how much dollar value should be expected from negotiations based on current transactional activity. AI will provide a more intelligent negotiating position, allowing greater amounts of money to be negotiated through a more informed decision-making process.
The Human-AI Collaboration Model Emerging in 2026
While automating procurement processes may not be the future of AI in procurement, the future will be a blend of autonomous agents working collaboratively alongside human experts.
Artificial intelligence is very good at processing large amounts of data, as with the ability to review thousands of tender documents, evaluate suppliers based on performance with hundreds of different contracts, evaluate global markets to determine market pricing for commodities, and identify patterns in spend data that humans may not see when manually analyzing spend. The human procurement professional's expertise comes from providing strategic judgement-based advice, which was previously limited by the amount of time spent on standard analysis (e.g., routine data gathering and classification activities).
On the other hand, humans provide vital relationship management capabilities—developing trusted partnerships with suppliers, negotiating complex contractual terms that require creative problem-solving, mediating supplier disputes that require the negotiation of emotional and political considerations, and exercising good judgement when faced with conflicting or ambiguous signals in data.
The collaboration framework for advanced procurement teams identifies and defines specific responsibilities based on capability. AI agent capabilities include continuous monitoring, detection of patterns, generating routine documentation, and performing extensive data analysis. Human capabilities include developing strategy, building relationships, solving problems creatively, and making decisions with substantial risk or uncertainty associated with them. Technology provides intelligence, whereas humans provide judgment.
Training and change management will be crucial factors in enabling procurement professionals to develop competencies related to interpreting AI-generated outputs, managing workflows that have been augmented by AI, integrating insights gained through AI into the larger business strategy, and overseeing the operations of their autonomous agents. Organizations that take a systematic approach to building capabilities to capture the value of AI technology will be more successful than organizations that treat AI as a plug-and-play type of technology.
Practical Implementation: What Suppliers Must Do Now
To successfully use AI-native procurement platforms, suppliers must get ready to take advantage of opportunities to compete effectively against those who are using AI.
The first step in this readiness is to optimize your digital presence in order to enhance your discovery by Artificial Intelligence (AI). This involves ensuring your Government eMarketplace (GeM) seller page, organizational website, and marketplace listings include structured data. Structured data allows AI agents to parse product specifications in a standardized way, select from easily categorized certification types, and access data regarding your company's past performance (used for determining win probability) that is machine-readable across different platforms, along with your organization's contact information consistently across all of these platforms. Having clear, structured information (user-friendly) in a profile on a procurement platform means it will be more likely to be available for the flow of opportunities through AI agents.
The next step in getting prepared is to develop an infrastructure that allows you to use AI tools for bid management. To accomplish this task, you should invest in tools that will allow you to monitor tender notifications on a variety of platforms (webinars), evaluate your opportunity wins likely based on matching capabilities, and create an initial draft of your response to tenders using templates and past submissions, as well as maintain digital libraries of certification and compliance documents that can be accessed immediately. These tools do not require costing thousands of dollars a month, as SMEs can find many affordable online Software as a Service (SaaS) options.
Create Knowledge Bases for your Products. Any structured knowledge base about your products (technical specs, compliance certifications, delivery capabilities, etc.) will enable AI to ingest and analyze this comprehensive digital content when sourcing suppliers. In addition to allowing your products to qualify more likely to be selected than competitors with less digital content, organized and comprehensive knowledge bases aid significantly in improving their chances of being selected as viable suppliers by Procurement AI Agents when they are seeking sources of supply.
Respect Your Performance Ratings. When recommending suppliers to their clients, procurement AI agents rely upon confirmed measures of a supplier's performance. For example, the agent will consider the provider's on-time performances, the overall customer satisfaction ratings provided by buyers who bought products from the provider, how often the provider has met quality compliance standards, and how quickly the provider responds to customer issues or inquiries. The data generated by procurement agents regarding their suppliers' performance are very valuable to them, and their supplier-selection algorithms are based on AI technology.
Leverage AI in Your Work. Use generative AI technologies to draft your initial tender responses, use AI analytics to analyze your pricing strategy, use automated tracking technologies to identify tenders in your product sectors, and consider using the new AI tools to help you analyze contracts prior to submitting a tender. Gaining an understanding of how AI-based technologies improve your business practices will ultimately enable you to leverage them to work with AI-based buyers.
The Global Context: India's Position in AI Procurement
Through an understanding of the GeM AI initiatives and the global procurement AI landscape, it will be possible to forecast the future direction of global procurement platforms and prepare for their analogous convergence.
Most global procurement platforms are transitioning to similar AI capabilities. Speaker: SAP Ariba's, Oracle's, and Coupa's large enterprise procurement suites now integrate AI into spend analysis, supplier risk monitoring, and contract intelligence capabilities. Large-scale implementations using AI meet public sector platforms such as those in South Korea, Singapore, and many European countries that implement chatbots for automating tender matching. The multidisciplinary implementation of the GeMAI, along with access to a large scale in the government of India, allows India to position itself as a leading innovator in AI for public sector-based adoption of procurement.
The progression toward systems with agentic functionality is currently the directed path for the procurement platform. The Gartner Hype Cycle for 2025 highlights where generative AI is currently located in the Trough of Disillusionment, meaning that generative AI did not run into any failures, but the technology lofted expectations that dwarfed what would be expected to be delivered realistically over the near-term future. On the other hand, some of the examples of text-to-process automation and the use of workflow agents that have materialized give an example of the effectiveness of the application of AI within these areas. This pattern demonstrates that focus on investments in AI applications should be aimed toward the automation of a few specific, higher-utility workflows, rather than the goal of comprehensive automation at the outset for each global procurement platform.
Organizations face challenges with data quality and integration, as this remains a universal barrier. According to research conducted by MIT, 95% of enterprise GenAI pilots do not result in a measurable ROI. This indicates that simply implementing technology does not equate to being successful. The ability of the organization to effectively utilize AI is dependent on having consistency in the quality of their data, the ability to integrate data from various sources, and developing a solution that integrates with existing systems.
AI adoption will ultimately be driven by regulatory developments. In the European Union (EU), the European Union's "AI Act," combined with new regulation in many other countries and sector-specific compliance, will govern how AI is used within procurement. This also reflects the precautionary principles taken by the GeM when adopting AI, in contrast to the private sector, recognizing that public sector AI will require far more stringent governance than that required by the private sector.
The Bottom Line: Preparing for AI-Native Procurement
By 2026, procurement systems throughout the globe, including GeM's Rs 13.60 lakh crore platform, will evolve to be AI-powered systems that will alter the entire structure of tendering; generative and agentic (AI) systems will create new methods of tendering. The fact that 94% of procurement executives currently utilize artificial intelligence on a weekly basis indicates AI has transitioned from an experiment to a form of daily operations.
As a supplier, in order to be successful, you must learn how to adopt AI in your discovery and evaluation processes. You must enhance your digital presence to ensure that you are optimized for the AI agents who are increasingly determining which suppliers will even be considered. In addition, suppliers should invest in AI tools to ensure that they are optimally competing against their competitors.
For buyers, artificial intelligence changes how procurement will operate from a tactical purchase to a strategic category management approach that incorporates an overall business strategy and cost structure into an actionable process. KPMG’s simulation predicts that automation will replace 50%-80% of procurement activity, allowing purchasing professionals to redirect the resources saved by automating to engage in higher-value activities like supplier development, collaboration on innovation, and risk management—however, for buyers to realize this value, there must be a systematic approach to implementing technology.
A new era in procurement is at hand, and it will be one where autonomous artificial intelligence, in partnership with human expertise (the two coming together), drives the procurement function. No longer will the two (humans and AI) be seen as replacements for one another; rather, the two will complement and enhance each other's capabilities. Humans will provide judgment and relationship management tools (e.g., human networks), while the AI will provide scale, the power of pattern recognition, and continuous monitoring capabilities. By working together, they can produce results that neither can achieve alone.
Through its launch and subsequent evolution, GeMAI gives insight into this future where carefully constructed AI-based goods and services significantly alter the user experience, make it easier to access, improve operational efficiencies, and provide appropriate levels of trust and oversight necessary for government procurement operations. As the technology matures during the next several years, suppliers who fully utilize the technological advantages of working with an AI-native procurement system will gain business, while competitors are still attempting to adjust to a world where procurement will be performed by humans through an AI-native procurement system.
The message is clear: AI-native procurement is now a reality. It would be wise to start preparing now, before watching your competitors gain an advantage through adopting AI-native procurement sooner than you.
