Reports / Industry Updates
AI technology in planning and procurement in 2024
Driving the Supply Chain 4.0 transformation
Introduction
The supply chain industry is at the cusp of transformation, with the biggest opportunity lying in the implementation of AI-powered automations. While EDI (Electronic Data Interchange) has provided some level of automation, it is limited, and many companies have yet to fully leverage modern APIs due to high implementation and maintenance costs. AI solutions, including GenAI (Generative AI), are now poised to revolutionize supply chain operations, offering the potential to drive down costs and automate much of the manual labor currently involved in planning and procurement.
GenAI (Generative AI), is a subset of AI that excels at human language and reasoning tasks. GenAI is powered by Large Language Models (LLMs) - same technology that powers ChatGPT. The latest models are natively multi-modal, supporting not only text, but also voice, images and video within the same AI model.
AI opportunities in supply chain
- Demand forecasting: AI analyzes vast datasets to create dynamic demand models, considering historical sales, market trends, and external factors. This enables businesses to optimize inventory levels and distribution plans, ensuring efficient fulfillment of customer demands.
- Production planning: Advanced AI algorithms optimize production schedules by factoring in customer changes, resource availability, and order priorities. This results in streamlined operations, minimized bottlenecks, and enhanced overall production efficiency.
- Risk management: AI-powered systems assess potential supply chain risks by analyzing diverse data sources, including market conditions and geopolitical events. On-demand risk assessments and mitigation strategies enable proactive decision-making and improved supply chain resilience.
- Purchasing: AI streamlines the procurement process by automating quotes, purchase orders, and negotiations. This technology enhances decision-making through data-driven insights on supplier performance, market trends, and cost optimization opportunities.
- Supplier management: AI-driven systems analyze supplier communications and performance data to identify potential issues and opportunities. By providing actionable insights, these tools help maintain strong supplier relationships and drive continuous improvement.
- Sourcing: AI algorithms evaluate a wide range of supplier data, including performance history, capabilities, and risk profiles. This comprehensive analysis supports informed decision-making in supplier selection and helps optimize the sourcing process.
- Contracts: AI-powered contract analysis extracts key information and generates valuable insights from complex agreements. These systems assist in reviewing terms, identifying potential risks, and ensuring compliance, while also providing data-driven recommendations for negotiations and renewals.
GenAI offers a unique opportunity to leapfrog the API stage entirely. LLMs can follow existing human workflows with minimal setup costs, reducing or bypassing the standard implementation hurdles. LLMs can already do tasks that require decision-making and communication, such as emails, phone calls, and data entry, and the intelligence of the models is improving rapidly.
Case Study: Generative AI for Automated Supplier Negotiation
Walmart uses an automated supplier negotiation solution with a text-based interface that negotiates with verified suppliers on Walmart's behalf. The system can read contracts, understand the priorities of both parties, integrate instructions, and negotiate via a chatbot. It negotiates based on Walmart's budgets, discount, and payment term requirements, considering historical trends, commodity values, and competitor costs.
Walmart first piloted the tool in Canada, focusing on shopping carts, fleet services, and other store essentials. In the pilot, 64% of tail-end supplier contracts were successfully negotiated within an average of 11 days, resulting in 1.5% average savings and extending payment terms by 35 days. The chatbot can handle 2,000 negotiations simultaneously, boosting procurement productivity.
After the pilot's success, Walmart's business owners helped create negotiation use cases and scenarios, setting specific trade-offs for improved terms. The legal team vetted the chatbot script to ensure compliance with Walmart's contracting standards. Successful pilots led to extended rollouts in the U.S., Chile, South Africa, Mexico, Central America, and China, with expanded categories.
Walmart used an AI supplier negotiation system to improve efficiency, cost savings, and payment terms
Current state of adoption
According to a 2023 survey of over 150 manufacturing CEOs and decision-makers, there is a notable trend of AI being deployed across various sectors, with supply chain management and procurement leading the way in real-world adoption.
- Deployment Areas: AI is being deployed in supply chain management (76%), procurement (71%), quality control (47%), and automation (37%).
- Strong ROI: 70% of manufacturing CEOs report a "strong ROI" from AI.
- Future Role: Nearly all CEOs anticipate AI playing a significant role in their companies within the next one to two years.
AI and Reshoring
The rise in AI adoption coincides with accelerating reshoring efforts. 75% of CEOs have reshored some or all of their overseas facilities, emphasizing the role of AI in creating resilient local supply chains. As reshoring continues, AI is being used to simplify procurement and streamline operations, reinforcing American manufacturing as a high-tech industry.
AI and Reshoring
Since the release of ChatGPT in November 2022, the adoption of GenAI has accelerated rapidly. By 2024, 40% of supply chain organizations had already invested in this technology.
40% of supply chain organizations are investing in GenAI
Case Study: Generative AI-powered scoping and vendor selection
BT Group leveraged GenAI technology to introduce autonomous sourcing across various service categories such as consulting, marketing, IT, HR, and legal. The Generative AI-powered scoping facilitated the definition of complex project requirements and the discovery of new suppliers alongside BT's existing suppliers.
This approach significantly freed up the procurement team's bandwidth for more value-adding activities, as the AI tool guides users through a step-by-step process to automatically generate the statement of work, which can be directly sent to suppliers.
Key benefits included higher efficiency, cost optimization, improved quality, and the advancement of BT's ESG strategy. The implementation was swift, taking less than 6 months, and deployment of the technology has realized double-digit savings for the company.
BT Group achieved double-digit savings by deploying a GenAI autonomous sourcing tool
Future trends
- AI adoption to accelerate Supply Chain 4.0 transformation: AI is poised to accelerate Supply Chain 4.0 transformation globally. GenAI can directly replace human labor in repetitive, manual tasks while adapting to various forms of communication— whether it's email, phone, EDI or API.
- Human-AI Collaboration: As AI automates more kinds of work, human workers will shift their focus to more fulfilling roles such as advanced problem-solving and strategic planning. The transition to AI-driven kinds of work, human workers will shift their focus to more fulfilling roles such as advanced problem-solving and strategic planning. The transition to AI-driven planning and procurement can also help grow the industry by making supply chains more adaptable and responsive.
- Rapid Technological Evolution: AI is evolving much faster than previous technologies like EDI or API. The rapid pace of AI advancements means that the timeline for industry-wide adoption could be significantly shorter compared to past technological shifts.
How Dialtone can help
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