Procurement is a crucial business function that involves acquiring goods, services, and works from external suppliers. With the exponential growth in data in recent years, procurement teams now have access to more information than ever before to help optimize purchasing decisions. This is where artificial intelligence comes in as a game-changer, providing next-level insights that simply weren‘t possible manually.
In this blog post, we‘ll explore how AI is transforming procurement through concrete applications and use cases. By the end, you‘ll have a clear understanding of why AI matters for procurement and how leading companies are benefiting from its implementation.
What is Procurement and Why is AI a Good Fit?
Procurement refers to the process of finding, agreeing terms, and acquiring required goods, services, or works from external sources, often through a tendering or competitive bidding process. It involves making the best purchase decisions under conditions of scarcity and uncertainty.
Some key procurement activities include:
- Demand management
- Vendor selection
- Negotiation
- Category management
- Monitoring orders and payments
- Managing supplier relationships
- Analyzing spending
With the deluge of data from multiple sources like invoices, contracts, market information, and supplier records, AI is the perfect solution to make sense of it all. AI techniques like machine learning and natural language processing can automate repetitive and mundane tasks while also revealing actionable insights.
According to Deloitte‘s 2019 Global Chief Procurement Officer Survey, 51% of CPOs reported using advanced analytics while 25% had implemented or were piloting an AI solution.
The adoption is being driven by the multitude of benefits AI offers to procurement teams. Let‘s look at some of these top applications and use cases.
Key Applications of AI in Procurement
AI is making inroads across the procurement function through a diverse range of high-impact applications.
Analytics
AI-driven analytics is helping procurement teams gain strategic insights to make smarter decisions.
Strategic Sourcing
Strategic sourcing refers to the process of identifying the best suppliers and negotiating the most favorable terms. AI tools can analyze factors like pricing, quality, lead time, and supplier risk to recommend optimal vendors and contracts. Natural language processing can also extract useful insights from vendor documents and market information online.
For example, a consumer goods company used AI to analyze factors like cost, compliance, and supplier risk to select optimal suppliers and obtained $100 million in savings.
Spend Analytics
Analyzing procurement spend is crucial for identifying cost-saving opportunities and managing supplier relationships. AI tools can automatically classify spends into different categories using machine learning algorithms. This enriched data enables better analysis and benchmarks.
According to Deloitte, AI-powered spend classification has achieved ~97% accuracy – far more than possible manually. Companies can leverage these insights to optimize costs and rationalize their supplier base.
Contract Management
Managing contracts with suppliers and customers is a complex, document-intensive process. NLP techniques can extract key terms and insights from contracts in seconds as opposed to hours spent in manual review. This allows faster turnaround on contract modifications, renewals, and compressing the contracting cycle.
Tools like Sievo leverage AI to automate contract management end-to-end – from digitization to abstracting, storing, and analyzing contract data. This reduces the burden on procurement teams significantly.
Anomaly Detection
AI algorithms can automatically monitor procurement data to detect anomalies and risks such as fraud, non-compliant purchases, price changes, and delivery delays. Alerts on such exceptions allow procurement teams to take corrective actions swiftly.
For instance, a global bank used an AI-based anomaly detection system to identify several fraud attempts worth over $7 million in the procurement process.
Automation of Manual Tasks
Procurement teams spend countless hours on repetitive, manual tasks like invoice processing, status updates, and purchase order creation. AI automation provides huge time savings by taking over these mundane chores.
A prime example is invoice processing which used to take over 25 days manually but can now be completed in hours using AI. From scanning invoices to extracting line items and approving for payment, AI handles it all.
This improves efficiency, reduces errors, and allows procurement professionals to focus on high-value responsibilities.
Chatbots
AI-powered chatbots act as virtual assistants to support internal teams and suppliers for procurement-related queries. Chatbots can provide 24/7 support and instantly respond to common questions on order status, product availability, invoices, payments and more.
Chatbots can also proactively send alerts for pending approvals and actions required by procurement team members. This ensures issues are addressed promptly versus getting lost in inboxes.
As chatbots handle the routine inquiries, procurement staff can dedicate their time to critical thinking and decision making.
Comparing Rules-Based Automation vs. AI
While traditional rules-based automation has helped streamline procurement processes, AI takes it to the next level with its ability to learn continuously.
| Rules-Based Automation | AI-Based Automation |
|---|---|
| Follows predefined rules and logic | Learns patterns from data |
| Limited flexibility | Continuously evolves and improves |
| Prone to breaking when rules change | Adapts seamlessly to new scenarios |
| Requires developer effort for modifications | Requires minimal supervision |
For instance, an AI-based invoice processing system can understand different invoice layouts and extract information without needing to code explicit rules. As new supplier invoices get processed, the AI model keeps getting better. This level of flexibility and autonomous improvement sets AI apart.
Best Practices for AI Implementation
Here are some tips for procurement teams looking to successfully leverage AI:
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Start small: Focus on high-impact areas like automating invoice processing or analyzing a specific spending category. Don‘t try to boil the ocean early on.
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Get executive buy-in: Educate leadership on the benefits of AI and have their support for any changes to processes.
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Evaluate AI tools: Assess different vendors based on factors like ease of use, ROI, and integration with existing systems. Shortlist tools that allow customization to your requirements.
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Clean your data: AI algorithms perform best with clean, standardized data. Invest time in data wrangling.
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Phase implementation: Roll out AI in phases starting with a pilot. Gradually expand based on results and user feedback.
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Train your team: Provide adequate training to your staff to work alongside AI tools comfortably.
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Encourage adoption: Incentivize employees to adopt AI through bonuses and recognition programs linked to objectives.
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Continuous improvement: Keep refining AI models through monitoring, testing, and user input to maximize value.
The Future of AI in Procurement
AI is no longer a nice-to-have but a must-have for procurement teams looking to optimize value. We can expect AI to become pervasive across the source-to-pay process in the coming years.
According to Gartner, AI augmentation will create $2.9 trillion of business value and recover 6.2 billion hours of worker productivity in 2021. The applications explored in this article are just the tip of the iceberg when it comes to AI‘s potential in procurement.
In my view as an industry expert, the rapid pace of AI innovation will enable procurement teams to operate with unprecedented agility, insight, and efficiency within the next 5 years. As AI solutions mature, we will see them tackle more complex tasks, provide holistic insights across the supply chain, and integrate more tightly with existing workflows. The future presents tremendous opportunities for early adopters to get ahead.
Conclusion
This brings us to the end of our comprehensive overview of how AI is revolutionizing procurement. The diverse use cases and quantifiable benefits highlighted above make it evident that AI implementation is vital for any procurement team aiming to maximize value.
I hope this article provided you with detailed information and unique perspectives to help build your understanding of AI applications in procurement. The business case for AI adoption is stronger than ever. What are your thoughts on the future possibilities we will see as these intelligent technologies evolve further? Let me know in the comments!