Marco Hubig’s Post

Learn how AI in supply chain management will help enterprises become more resilient and sustainable and will transform cost structures. While it does have limitations, generative AI presents a multiplier in what humans and technology can achieve together in building efficient and resilient supply chains — whether in planning, sourcing, making or moving. Thanks to recent updates that make it simpler to use and more effective in realizing value, organizations are now forced to determine how these advances will impact their sector or risk disruption. Read more here: https://lnkd.in/dyYA8UnW

Artificial intelligence (AI) has become a buzzword in the supply chain domain, offering a #competitive edge through enhanced #customer experiences and #visibility. Corporations are increasingly embracing AI in supply chains for demand planning, #procurement, and beyond. #AI #SupplyChain #DemandPlanning #Procurement #LastMileDelivery #SustainabilityTracking #EYStudy #genAI #technology #generativeAI

Generative AI is making waves in supply chains, transforming how businesses operate. From automating processes to optimizing decision-making, this tech promises more efficient, resilient systems. But what does this mean for leaders? Here's a deeper insights on how it can bring value to your operations: https://lnkd.in/dyYA8UnW Have you started using AI in your supply chain? What are the biggest benefits or challenges you’ve seen? #generativeai #supplychain #innovation #businessvalue

Why #AI skepticism might be holding your company back from improving your bottom line: https://lnkd.in/dGixMePN. @SourceDay #manufacturing #technology #ML #supplychain #sustainability #manufacturinganddistribution

Are Organizations Truly Harnessing AI’s Power in Supply Chain, or Just Following the Hype? AI is the current buzz in supply chain conversations globally, but are organizations truly grasping its potential to transform their operations? Despite its allure, a significant value leakage persists as many businesses struggle to bridge the gap between hype and practical implementation. The real potential of AI in supply chain management (SCM) lies in operational enhancements like predictive demand forecasting, dynamic inventory management, and real-time logistics optimization. Companies like Amazon and Procter & Gamble have reaped benefits by using AI to forecast demand spikes and fine-tune supply chain responses during turbulent times. Yet, for many, adopting AI remains an intricate challenge involving substantial investments and technical complexities. One core issue is the misconception about AI as a plug-and-play solution. Implementing AI involves rigorous data quality checks, robust governance frameworks, and significant employee training. The effectiveness of AI models heavily relies on accurate data, domain expertise, and the ability to trust AI-generated insights. Without a comprehensive approach, AI solutions often fail to deliver the expected ROI, leading to fragmented or abandoned initiatives. Furthermore, biases embedded within AI algorithms, often overlooked, can lead to skewed predictions and decisions, which in turn impacts operational efficiency. This is where companies like BMW and UPS have leveraged advanced AI to maintain optimized stock levels and streamline delivery processes, respectively, showcasing the importance of careful, bias-aware implementation. In tackling these challenges, companies must prioritize strategic AI adoption roadmaps that align with business goals. From developing internal AI expertise to focusing on explainable AI, organizations can harness AI’s true potential while mitigating risks. Bridging this understanding gap will allow supply chains not only to survive but thrive in an increasingly complex, data-driven world. The future of AI in SCM is bright, promising innovations like edge computing and autonomous deliveries. But to reach that future, organizations must first solidify their foundational understanding of AI applications, ensuring their journey is not just trendy but transformational. #Lalji

Fairmarkit is helping major companies like BP, Snowflake, and Boeing adopt generative AI (Gen AI) for their procurement processes. By focusing on responsible AI usage, Fairmarkit educates leaders on integrating Gen AI to optimize procurement tasks like RFP creation, data analysis, and supplier management. This approach not only enhances efficiency but also ensures data security and drives strategic decision-making. Fairmarkit emphasizes a "jobs to be done" strategy, helping organizations achieve better outcomes. For more details, read the full article: https://lnkd.in/gxf_EZw2.

The Reality of AI in Supply Chain Management Martijn Lofvers, your article highlights the evolving role of AI in supply chain management, particularly the challenges of moving towards a fully autonomous "no-touch" supply chain. While AI offers significant potential, your insights into its current limitations are crucial. To complement your points, I’d like to share a comparison of human and AI strengths and weaknesses in supply chain tasks hereunder. This table illustrates that while AI excels in efficiency and data-driven tasks, human creativity, intuition, ethical judgment, authenticity and ownership/responsibility remain vital. AI can optimize processes particularly around volume data management and decision-making, but human oversight is essential, particularly in handling unpredictability and complex problem-solving. The Way Forward As you pointed out, a fully autonomous supply chain remains a distant goal. The best approach today is to integrate AI as a powerful tool that enhances, rather than replaces, human expertise. This hybrid model leverages the strengths of both, creating a more resilient and adaptive supply chain. Thank you for starting this important discussion. Balancing AI with human capabilities is key to navigating the future of supply chain management.

The future of supply chains is becoming increasingly data-driven, with AI playing a key role. Manufacturers are quickly finding that digital transformation is enabling greater levels of resilience than ever before. For example, every facet of the supply chain can start producing valuable data which can be automatically analysed with AI. This will result in 24/7 predictive maintenance, governance and forecasting. As global supply chains become increasingly turbulent, digital innovations such as these are a powerful way for businesses to become more resilient and face the future head-on.

Companies are jumping on the AI bandwagon to improve supply chains, handling everything from demand planning to sustainability tracking. Recently, generative AI (GenAI) like ChatGPT has been making waves, with 40% of supply chain organizations already investing in it. GenAI can generate new content and analyze data, helping with demand forecasting, production planning, and risk management. While it has its limitations—like needing high-quality data and proper governance—GenAI is already being used for real tasks like negotiating with vendors, predictive maintenance, and optimizing logistics. Please see the below article for more information. https://lnkd.in/g7-CAeCu

𝗧𝗵𝗲 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗼𝗳 𝗔𝗜 𝗶𝗻 𝗣𝗿𝗼𝗰𝘂𝗿𝗲𝗺𝗲𝗻𝘁 🤖 The rapid evolution of artificial intelligence (AI) is calling in a new era for procurement and supply chain management (SCM). Organizations are now harnessing AI-driven tools to refine operations, boost efficiency, and minimize risks. In this article, we will delve into the cutting-edge applications of AI within procurement and supply chains, share our insights on how it enhances contract management and ultimately offer our conclusion on this transformative technology. Our research highlights that the most significant advancements facilitated by AI in Supply Chain Management and Procurement are manifested in enhanced contract management and meticulous risk tracking. While other applications are captivating, they often rely on pre-existing internal data or external online information that can fall short of comprehensive needs. 𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 AI tools and specifically large language models (LLM) unlock transformative opportunities for refining contract management within procurement. Challenges such as tedious manual writing and reviewing, delayed contract executions, and potential supply chain disruptions can be addressed through automated contract assessment. AI tools scrutinize contracts for compliance, highlighting risks and unusual language, while also enhancing contract lifecycle management through improved visibility, automated renewals, and obligations tracking. 𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻 AI is revolutionizing procurement and supply chain management by providing tools to tackle inefficiencies, enhance transparency, and oversee risks. Although the potential of AI is vast, organizations must strategically prioritize high-impact domains like contract management and risk tracking to fully leverage its capabilities. Adopting a forward-thinking mindset, coupled with vigilant observation of technological progress, will be vital for maintaining competitiveness in an ever-evolving landscape. Yet, it is vital to acknowledge the irreplaceable essence of human intuition and sensitivity, particularly during critical times. We view AI not as a replacement, but as a powerful ally that amplifies human capabilities and fosters increased process efficiency, a partnership that is destined to redefine future landscapes. #AI #Procurement #ContractManagement