Top 5 AI Procurement Software ['25] by Use Cases & Tools

Organizations face inefficiencies in managing spend, supplier relationships, and time-consuming manual tasks. AI-based procurement software offers a solution by leveraging advanced machine learning, robotic process automation, and AI-driven insights to streamline these processes.

There are 2 ways to incorporate AI in your procurement flows. See:

• Full-featured procurement suites with AI powered features
• AI tools that can support procurement professionals (e.g. in automatically reviewing contracts)

Explore also use cases of them and comparison with the traditional procurement software:

Top 5 AI-powered procurement software

Table 1. Features

Key Features of AI Procurement Software

AI is helping make procurement tools more efficient and easier to manage. Here are three important features you’ll often find:

• Inventory management: AI can track inventory in real time. It helps teams know what’s in stock, what’s running low, and when to reorder. This reduces waste and avoids delays.
• Contract management: These tools help store, review, and monitor contracts. AI can highlight key terms, flag risks, and send alerts before contracts expire. This saves time and improves compliance.
• AP automation: AP automation uses AI to process invoices faster. It can match invoices with purchase orders, check for errors, and route them for approval. This reduces manual work and speeds up payments.

Table 2. Market presence

* Based on data from B2B review platforms.

** Based on data from LinkedIn

Inclusion criteria: Only AI-based procurement software solutions with at least 20 reviews across B2B review platforms are considered.

Ranking: Products are ranked based on the number of reviews across B2B review platforms.

Coupa

Coupa’s AI procurement software provides unique capabilities like AI-driven insights for complete spend visibility and automated workflows that improve margins and compliance. The platform’s strengths include identifying potential savings, mitigating risk, and offering easy adoption for users and suppliers. However, its reliance on high-quality data for AI insights may pose challenges for companies with inconsistent data management practices.

User reviews

✅ The application can be customized based on business needs, allowing users to tailor the system to achieve desired outcomes.

Figure 6. A user review on Coupa

❌ The courier list for shipment tracking is not always updated, leading to disputes over invoices due to a lack of proof of delivery.¹

Tipalti

Tipalti’s AI procurement software, GEP SMART, offers capabilities such as intelligent invoice management through Auto Coding, which streamlines invoice and purchase order processing by predicting correct codes and enhancing spend visibility. Additionally, its AI-powered chat feature provides instant financial insights and spend analytics.

User reviews

✅ Tipalti provides a comprehensive dashboard that enables users to track payments, review transaction details, and generate detailed reports, aiding in financial management.

Figure 5. A user review on Tipalti

❌ Tipalti’s pricing structure may be expensive for smaller businesses with lower transaction volumes, making it less accessible for these users.²

JAGGAER

Figure 1. JAGGAER ONE wheel of the procurement process

Source: JAGGAER³

Jaggaer’s AI procurement software aims to optimize procurement processes through advanced AI technologies such as machine learning, generative AI, and natural language processing. It automates repetitive tasks like purchase order matching and spend analysis, enabling procurement teams to focus on strategic activities and gain real-time insights for informed decision-making.⁴ However, while its capabilities in contract management and supplier risk management are robust, the system’s effectiveness may be limited by the quality and structure of the input data.

User reviews

✅ The automation of procurement processes, including requisition to PO and invoice processing, reduces manual work and streamlines approval structures.⁵

Figure 2. A user review on Jaggaer

❌ Reliance on a third-party public cloud for data storage raises concerns over data security, which can be a significant issue for organizations.

Sievo

Sievo’s AI-based procurement software stands out for its advanced capabilities in data analytics and automation. It claims to offer a high classification accuracy of 94% and can uncover hidden savings opportunities while mitigating supply chain risks through continuous AI-powered insights.⁶

Unique features include a self-service GenAI Assistant for advanced analytics and automated negotiations with a single click. However, it may face limitations in handling the dynamic nature of rapidly changing supplier information and market conditions.

User reviews

✅ The user interface and dashboards offer multiple options to slice the data, providing flexibility in how users can view and analyze the information.⁷

❌ Sievo lacks integration capabilities, with no API support and limited inbound file integration confined to spend analytics. This can hinder seamless data flow between Sievo and other systems.

GEP Smart

Figure 3. GEP Smart procurement software diagram

Source: GEP Smart⁸

GEP’s AI procurement software, GEP SMART, is a unified source-to-pay platform that excels in streamlining procurement processes through AI-powered spend analysis, contract management, and supplier risk management. Its unique capabilities include mobile-native design, advanced data analytics, and seamless integration with existing ERP systems. A potential deficiency is the complexity of its comprehensive toolset, which may pose a learning curve for new users.

User reviews

✅ GEP Smart is noted for its strong customer support, including responsiveness to product enhancement feedback. This ensures a positive partnership experience throughout the product lifecycle, from evaluation to deployment and ongoing support.

❌ There is a lack of robust update and product release processes, which may hinder the stability and evolution of the platform over time.

Figure 4. A user review on GEP Smart

Top 5 AI tools for procurement

Artificial Intelligence (AI) is revolutionizing the procurement sector, enhancing efficiency, and unlocking valuable data insights. Here are five AI platforms that procurement managers can leverage to refine and streamline their business processes:

1. DocuSign Insight

Contracts are vital in procurement, defining business relationships, and ensuring compliance with terms and conditions. DocuSign Insight is an artificial intelligence platform that simplifies the contract formulation and review process.

Figure 7. DocuSign Insight is an AI platform used for procurement processes

Applications:

• Contract search and review: Utilizes Natural language processing (NLP) to speed up contract searches and reviews.
• Risk reduction: Reduces risks of non-compliance and negative outcomes.
• Data visualization and reporting: Facilitates the identification of trends in procurement through internal data visualization.

2. TealBook

Collecting and analyzing supplier data is crucial in procurement. TealBook is an AI application designed to obtain and manage comprehensive supplier data efficiently.

Figure 8. TealBook platform diagram

Applications:

• Supplier data management: Provides detailed supplier data and insights on supplier spending, diversity, and more.
• Machine learning insights: Enhances decision-making and strengthens supplier relations through updated and accurate information.

3. Stampli

Stampli focuses on the purchase and payments aspect of procurement. With investments of $61 million, Stampli aims to transform accounting processes into seamless operations.⁹

Applications:

• Automation in payments: Reduces service disruptions caused by late payments or delays.
• Comprehensive dashboard: Offers a 360° view of payment breakdowns and purchases to optimize resource allocation.
• Data visibility: Consolidates financial data, fostering productive business collaborations.

4. Keelvar

Keelvar is a sourcing optimization platform that uses NLP and machine learning to enable automated sourcing through competitive bidding.

Figure 9. Keelvar sourcing optimizer

Applications:

• Automated sourcing: From generating RFQs to analyzing supplier responses, Keelvar significantly reduces the time spent by procurement professionals.
• e-Sourcing bots: These bots provide a complete analysis of previous spending patterns and audit trails for optimal financial resource utilization.

5. ChatGPT

ChatGPT, developed by OpenAI, is one of the most recognized artificial intelligence tools today. With over 100 million weekly users and 1.6 billion visits in December 2023 alone,¹⁰ it is widely accessible and user-friendly. While ChatGPT is utilized across various industries, it is increasingly being adopted in the procurement sector.

Applications:

• Contract renewal guidance: Procurement professionals can prompt ChatGPT for advice on renewing contracts.
• Custom contract structuring: The AI can help structure contract terms and conditions based on specific requirements.
• Quotation templates: ChatGPT can generate and customize quotation templates to meet procurement needs.
• Negotiation strategies: This aids in identifying effective negotiation tactics.

Despite its capabilities, users should note that the reliability of ChatGPT is not always 100% accurate, as it relies on existing data inputs, which may not always be current.

Use cases of AI in procurement software

1. Demand forecasting

AI procurement software leverages machine learning algorithms to generate accurate demand forecasts. By analyzing procurement data, market data, and supply chain management information, these systems predict future needs with greater precision than human estimates. This optimization minimizes disconnects and enhances supply chain management.

2. Contract management

Contract management is critical yet time-consuming. AI in the procurement process automates contract management by using natural language processing (NLP) to review agreements, flag important clauses, and compile summary documents. This process reduces manual effort and ensures that procurement professionals can focus on strategic sourcing and supplier relationship management.

3. Invoice and payment anomalies detection

AI-powered procurement systems use advanced analytics to detect anomalies in invoice processing and payments. By analyzing spend data and procurement-related data, these systems identify discrepancies and potential fraud, enabling procurement and finance professionals to address issues proactively and maintain data quality.

4. Supplier risk management

Supplier relationship management is enhanced through AI-driven risk assessment. AI procurement software scrapes procurement data, market data, and public records to uncover early supplier risk warnings. These systems provide procurement teams with actionable insights to suggest risk mitigation strategies and ensure robust risk management.

5. Analyzing purchase patterns

AI procurement software analyzes purchase order processing and spend data to identify patterns and procurement cost-saving opportunities. By understanding human behavior and procurement context, these systems offer strategic insights that streamline processes and improve procurement operations. Procurement intelligence derived from AI helps key stakeholders make informed decisions that drive cost savings and operational efficiency.

6. Generating procurement-related documents

Generative AI, a subfield of AI, automates the creation of written content to match human-quality prose. In the procurement context, generative AI can instantly produce essential documents such as supplier scorecards, contract briefings, and RFP responses.¹¹ This capability reduces manual tasks and accelerates procurement processes, allowing procurement professionals to focus on high-value activities.

Traditional vs AI procurement processes

Limitations of traditional procurement software

Limitations of traditional procurement tools rooted in traditional forecasting methods are highlighted in various studies.¹²

1. Lack of flexibility

Traditional procurement models depend on historical data and assumptions that may not accurately reflect future conditions. This makes them less adaptable to sudden market changes, impacting the responsiveness and agility of the procurement process.

2. Inability to handle complex relationships

Traditional software often relies on linear regression techniques, which overlook intricate interdependencies among variables. This can lead to inaccurate predictions and suboptimal procurement decisions.

3. Ignoring external factors

Traditional models tend to assume constant external factors, neglecting the impact of market trends, competition, and economic conditions on procurement activities. This limits the ability to generate accurate demand forecasts and identify strategic sourcing opportunities.

4. Limited data availability

Traditional procurement tools require extensive historical data, which may not always be available, especially for new products or emerging industries. This data dependency can hinder the effectiveness of procurement software.

5. Difficulty in handling seasonality and trends

Traditional models struggle to accurately capture cyclical patterns or evolving consumer preferences, resulting in inaccuracies in demand forecasting and procurement planning.

How AI procurement software solves these challenges

AI procurement software leverages robotic process automation (RPA), advanced machine learning algorithms, and artificial intelligence to analyze vast datasets and uncover patterns and trends that traditional methods might miss. Here’s how AI addresses the deficiencies of traditional procurement software:

1. Enhanced flexibility

AI models continuously learn and adapt from new data, providing more flexible and accurate predictions even in volatile markets. This adaptability is crucial for businesses facing rapid changes in demand or supply chain disruptions.

Real-life example:

AI-driven spend analysis helps organizations like Carlsberg Group gain real-time insights into their procurement spend, allowing them to adapt to market changes swiftly and effectively.¹³

2. Handling complex relationships

AI can analyze complex, non-linear relationships between variables, providing deeper insights and more accurate forecasts. Machine learning algorithms can process multi-dimensional data and detect subtle patterns that traditional methods overlook.

Real-life example:

An AI-powered platform uses predictive analytics to anticipate procurement risks and opportunities, helping companies like Johnson & Johnson make proactive decisions.¹⁴

3. Incorporating external factors

AI models consider a wide range of external factors, including market trends, economic indicators, and competitive actions, providing a comprehensive view of potential impacts on procurement.

Real-life example:

Procurement software with AI capabilities integrates external market data with internal spend data to deliver more accurate and comprehensive procurement insights.¹⁵

4. Dealing with limited data

AI can work effectively with limited historical data by using synthetic data generation and transfer learning techniques. This is particularly beneficial for new products or markets where historical data is scarce.

Real-life example:

AI procurement software solutions help companies match with the best suppliers globally, resulting in a 15% cost savings, 66% faster speed to market, and 70% efficiency gains by autonomously sourcing high-quality suppliers and integrating seamlessly with existing procurement systems.¹⁶

5. Managing seasonality and trends

AI excels at recognizing and predicting seasonal patterns and evolving consumer preferences. Advanced algorithms can differentiate between noise and genuine trends, providing more reliable forecasts.¹⁷

Real-life example:

AI procurement software enables companies to manage inventory by analyzing and predicting seasonality and trends, leading to optimized supply chains and significant efficiency gains, as demonstrated by Odyssey Logistics & Technology’s ability to navigate COVID-19 challenges and deliver actionable insights to clients.¹⁸

FAQs

Further Reading

• Top 10 Procurement Software Features & Prices Analyzed
• 10 AI Procurement Use Cases & Case Studies
• Non-profit procurement: Checklist & Challenges
• Healthcare Procurement Challenges & Effective Solutions

If you need further help in finding a vendor or have any questions, feel free to contact us:

External Links

• 1. A user review on Coupa. Capterra. Accessed:7/August/2024.
• 2. A user review on Tipalti. JAGGAER. Accessed:7/August/2024.
• 3. Procurement Efficiency | Enhance with JAGGAER AI Solutions. JAGGAER
• 4. Leverage the Benefits of Al in Procurement. JAGGAER. Accessed:6/August/2024.
• 5. Review from a K-12 Perspective | TrustRadius. TrustRadius
• 6. Next-Gen Insights. Powered by AI.
• 7. Sievo Spend Analytics review in Strategic Sourcing Application Suites.
• 8. Intelligent Procurement Management Software That Drives Superior Results. GEP Smart. Accessed:7/August/2024.
• 9. Deutscher, M. Stampli reels in $61M for its AI-powered accounting platform. SliconANGLE. Accessed: 1/August/2024
• 10. Exclusive: ChatGPT traffic slips again for third month in a row | Reuters. Reuters
• 11. 5 Real-World Use Cases for AI in Procurement. GEP. Accessed: 6/August/2024
• 12. Hansun, S., Charles, V., Gherman, T., & Varadarajan, V. (2022). Hull-Wema: A novel zeroLAG approach in the moving average family, with an application to COVID-19. International Journal of Management and Decision Making, 21(1), 92–112.
• 13. Case Studies | Sievo.
• 14. Digital Prescription for the Pharma Supply Chain: A Shot in the Arm to Boost Innovation and Value | GEP.
• 15. Everest Group Procurement Peak Matrix for Procurement Outsourcing Service Provider 2022. Everest Group. Accessed: 2/August/2024.
• 16. Globality | Customers.
• 17. Ajiga, D. I., Ndubuisi, N. L., Asuzu, O. F., Owolabi, O. R., Tubokirifuruar, T. S., & Adeleye, R. A. (2024). AI-driven predictive analytics in retail: a review of emerging trends and customer engagement strategies. International Journal of Management & Entrepreneurship Research, 6(2), 307-321.
• 18. Odyssey Logistics & Technology uses Coupa to operationalize outcomes for customers and build more resilient and sustainable supply chains. Coupa. Accessed: 5/August/2024.