Generative AI in Procurement Market to be Worth USD 2,260 Million by 2032

Introduction

Generative AI in procurement market is poised for substantial growth, with market projections estimating its value to soar to USD 2,260 million by 2032, reflecting a robust compound annual growth rate (CAGR) of 33% over the forecast period. This surge is propelled by the integration of generative AI into procurement processes, revolutionizing how businesses manage their sourcing, contracts, and supplier relationships.

The demand for generative AI in procurement stems from its ability to automate decision-making, streamline operations, and optimize purchasing strategies. By leveraging advanced algorithms and machine learning, generative AI analyzes vast datasets to generate predictive insights, enhance inventory management, and tailor procurement strategies in real-time. This not only enhances efficiency but also mitigates risks and reduces costs for organizations.

A significant driver of this market growth is the increasing need for accurate demand forecasting and inventory optimization. Generative AI empowers organizations to understand customer demand patterns, anticipate future needs, and optimize inventory levels accordingly. This proactive approach not only improves customer satisfaction but also enhances cost efficiency by minimizing stockouts and excess inventory. However, the adoption of generative AI in procurement is not without its challenges. Organizations often face hurdles in integrating these advanced systems with existing infrastructures, leading to complexities and additional costs.

Additionally, ensuring the availability and quality of data remains a significant challenge, as AI systems require accurate and consistently formatted data to function effectively. Despite these challenges, the market presents compelling opportunities, particularly in proactive risk management and compliance. Generative AI enables organizations to predict potential risks, ensure regulatory compliance, and maintain ethical procurement practices. Moreover, ongoing advancements in AI technologies are driving innovation within procurement operations, offering new capabilities for enhanced decision-making and efficiency gains.

Generative AI in procurement offers several potential benefits and applications. One key area is in data augmentation, where generative AI can be used to generate synthetic data that expands the available dataset for training machine learning models. By generating additional data samples, generative AI can help improve the accuracy and robustness of predictive models used in procurement tasks, such as demand forecasting, supplier selection, and pricing optimization.

Another application of generative AI in procurement is in scenario testing and simulation. By generating synthetic data, organizations can simulate various procurement scenarios and assess the potential outcomes. This can help in evaluating procurement strategies, identifying potential risks, and optimizing decision-making processes.

Key Takeaways

• Market Growth Projection: The Generative AI in Procurement market is expected to reach a value of USD 2,260 million by 2032, with a robust compound annual growth rate (CAGR) of 33% during the forecast period.
• Direct Procurement Dominance: Direct procurement plays a pivotal role in the Generative AI in Procurement market, capturing over 37.5% of the market share in 2022. This segment is crucial for manufacturing and production industries, driving the adoption of AI technologies to optimize supply chain dynamics, reduce costs, and enhance operational efficiency.
• Supplier Identification Importance: Supplier identification is another critical application area for generative AI within procurement, accounting for more than 25% of the market share in 2022. The increasing complexity and globalization of supply chains necessitate sophisticated tools for identifying and vetting potential suppliers, making generative AI indispensable in this aspect.
• Market Dominance by Region: In 2022, North America held a dominant market position in the Generative AI in Procurement market, capturing more than a 45.8% share. This substantial market share can be primarily attributed to the region’s advanced technological infrastructure and early adoption of AI technologies by enterprises across various sectors.

Generative AI in Procurement Statistics

• The Global Artificial Intelligence Market size is set to rise from USD 177 billion in 2023 to about USD 2,745 billion by 2032. This growth represents an annual rate (CAGR) of 36.8% from 2024 to 2033.
• Similarly, the Global Generative AI Market is projected to grow from USD 13.5 billion in 2023 to USD 255.8 billion by 2033, with a CAGR of 34.2% during the same period.
• Focusing on Japan, the Generative AI Market there is expected to increase from USD 918 million in 2023 to around USD 22,995 million by 2033. This indicates a CAGR of 38% from 2024 to 2033.
• A global survey by KPMG, which included more than 400 leaders in procurement, identified the main challenges in the sector as effectively using textual data, managing supplier relationships, forming strong internal partnerships, hiring and keeping skilled workers, and delivering real value.
• The survey highlighted that 68% of procurement teams feel they play a minimal role in strategic decision-making.
• Research by Ardent Partners found that about 75% of companies face difficulties in using analytics effectively in procurement. Problems include poor quality data, a lack of analytical skills, and insufficient technology.
• The Oxford College of Procurement and Supply notes that AI could reduce the time spent on procurement activities by up to 60%, enhancing operational efficiency significantly. This allows continuous management of data analysis, supplier communication, and contract management, improving productivity and speeding up processes.
• Furthermore, a study by Capgemini pointed out the benefits of integrating ChatGPT into inventory planning. By decreasing instances of stock shortages by 3-5%, Generative AI helps maintain product availability and fosters a more reliable supply chain.

Emerging Trends

• Autonomous Supplier Negotiations: Leading retailers like Walmart are using generative AI for automated negotiations, which shows a significant shift towards AI-driven interactions in procurement​.
• Integration of Generative AI Across S2P Processes: Generative AI is being increasingly integrated into source-to-pay processes, enhancing proactive risk management, process automation, and decision-making​.
• Digital Transformation Focus: A large percentage of Chief Procurement Officers (CPOs) have made digital transformation a priority, leveraging AI to enhance operational efficiency and address challenges like inflation and supply chain disruptions​.
• Advancements in AI-driven Compliance and Strategy Development: Generative AI is employed to monitor compliance and develop procurement strategies by analyzing extensive data sets, which helps in managing risks and improving supplier selection processes​.
• Enhanced Data Analytics: Generative AI’s ability to process large volumes of data rapidly is leading to more informed decision-making and better management of supplier relationships and performance​.

Top Use Cases for Generative AI in Procurement

• Automating Document Creation: AI models are used to generate procurement documents like requests for proposals and contracts, reducing manual effort and improving accuracy​.
• Supplier Sourcing and Strategy Formulation: Generative AI facilitates robust supplier sourcing and category strategy development by synthesizing insights from multiple data sources​.
• Predictive Analytics for Risk Management: Predictive models built by AI can forecast risks and automate the evaluation of supplier performance and reliability​.
• Process Automation in Source-to-Pay: AI automates critical procurement tasks like creating purchase orders and managing invoices, significantly speeding up the procurement cycle​​.
• Interactive Engagement and Negotiation Support: AI-driven tools support procurement professionals with data-driven talking points and strategies for negotiations, enhancing interactions with suppliers​​.

Benefits of Using Gen AI in Procurement

• Efficiency: Gen AI can automate various aspects of the procurement process, streamlining tasks such as supplier selection, order processing, and invoice management. By automating routine tasks, procurement professionals can focus on strategic activities that add more value to the organization.
• Cost Savings: Through advanced analytics and predictive modeling, Gen AI can identify cost-saving opportunities within the procurement process. It can analyze historical data to negotiate better prices with suppliers, optimize inventory levels, and identify alternative sourcing options, ultimately reducing procurement costs.
• Enhanced Supplier Management: Gen AI can analyze vast amounts of supplier data to assess performance, reliability, and risk. By continuously monitoring supplier performance metrics and market conditions, organizations can proactively identify potential issues and optimize their supplier base for improved efficiency and resilience.
• Risk Mitigation: Gen AI can help mitigate various risks associated with procurement, such as supply chain disruptions, compliance breaches, and supplier fraud. By analyzing supplier data and market trends in real-time, organizations can identify and address potential risks before they escalate, ensuring business continuity and regulatory compliance.
• Predictive Insights: By leveraging machine learning algorithms, Gen AI can provide predictive insights into future demand, market trends, and supplier behavior. These insights enable organizations to anticipate changes in the market, optimize inventory levels, and make informed decisions that drive business growth and competitiveness.
• Customized Solutions: Gen AI can tailor procurement processes and strategies to meet the specific needs and objectives of the organization. By analyzing historical data and user preferences, Gen AI can recommend personalized procurement solutions that optimize efficiency, reduce costs, and enhance overall performance.
• Scalability: Gen AI offers scalability, allowing organizations to adapt and expand their procurement capabilities in response to changing business needs and market dynamics. Whether it’s scaling up to meet increased demand or diversifying supplier networks, Gen AI enables organizations to flexibly adjust their procurement strategies to support growth and innovation.

Recent Development

• GEP Worldwide’s Integration with OpenAI’s ChatGPT: In May 2023, GEP Worldwide launched a suite of solutions incorporating OpenAI’s ChatGPT technology via Microsoft Azure. This innovation aims to enhance GEP SOFTWARE’s capabilities, particularly in automating and optimizing procurement processes. By leveraging ChatGPT technology, GEP Worldwide seeks to provide more advanced AI-driven solutions to its clients, improving efficiency and effectiveness in procurement operations.
• SAP’s Launch of Joule: In September 2023, SAP announced the launch of Joule, a generative AI assistant embedded across its cloud enterprise portfolio. Joule provides proactive and contextualized insights to help businesses streamline operations. This new AI assistant is part of SAP’s broader strategy to integrate advanced AI capabilities into its suite of applications, including SAP SuccessFactors and SAP S/4HANA Cloud. Joule aims to empower businesses with AI-driven insights and recommendations, enhancing decision-making and operational efficiency in procurement and other areas.

Conclusion

In conclusion, generative AI has emerged as a powerful technology with significant potential in the field of procurement. By utilizing generative AI algorithms, organizations can benefit from data augmentation, scenario testing, and virtual supplier profiling, among other applications. These advancements can lead to improved accuracy in predictive models, enhanced decision-making processes, and more efficient supplier management. The Generative AI in Procurement market is still in its early stages but shows promising growth prospects. As organizations increasingly recognize the importance of data-driven insights and AI in procurement, the demand for generative AI solutions is expected to rise. However, challenges related to ethical considerations, biases in generated data, and implementation complexities need to be addressed for widespread adoption.

Discuss Your Needs With Our Analyst

Please share your requirements with more details so our analyst can check if they can solve your problem(s)

Request a Sample Download PDF