I need use cases related to Procurement where we can use Agentic AI in UiPath. So, give me some real-life processes that we can implement in UiPath — but only provide use cases related to manufacturing.
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Supplier Invoice Processing:
This process involves automating the extraction of data from supplier invoices using AI-powered OCR and natural language processing. The system can validate the extracted data against purchase orders and goods receipt notes to ensure accuracy. Any discrepancies can be flagged automatically for review, reducing manual errors, speeding up the invoice-to-pay cycle, and ensuring timely payments. This not only improves efficiency but also enhances financial accuracy and vendor relationships. -
Purchase Order (PO) Management:
AI can analyze historical purchasing data, supplier performance, pricing trends, and lead times to predict the best suppliers for specific products. It can also automate the creation of POs based on demand forecasts and inventory levels. Additionally, AI can streamline the approval workflow by routing POs to the appropriate stakeholders, reducing delays and improving procurement cycle times. This results in better supplier management, cost savings, and improved procurement planning. -
Inventory Replenishment:
AI-driven forecasting models can analyze historical sales data, production schedules, and current inventory levels to predict future demand accurately. This allows for automated inventory replenishment, ensuring that manufacturing operations are not disrupted due to stockouts. The system can also optimize order quantities, reducing excess inventory and minimizing holding costs while maintaining adequate supply levels to meet production needs. -
Contract Review and Compliance:
Contract management can be complex, especially when dealing with numerous suppliers. AI can extract key clauses, terms, and conditions from supplier contracts, flagging potential compliance risks or deviations from standard agreements. It can also monitor contract performance, ensuring suppliers adhere to agreed-upon terms, such as delivery schedules, pricing, and quality standards. This reduces legal risks, ensures regulatory compliance, and simplifies contract audits. -
Vendor Risk Assessment:
AI can continuously monitor and analyze data from multiple sources, such as financial reports, news outlets, and compliance databases, to assess supplier risks. It can identify red flags like financial instability, geopolitical risks, or violations of regulatory requirements. This proactive risk management approach allows procurement teams to make informed decisions, mitigate potential disruptions in the supply chain, and maintain a resilient vendor ecosystem.
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