Building Dynamic Supply Chains: Generative AI’s Transformative Power



Authored By Praveen Pajiar, Managing Director and Vishal Barfiwala, Senior Director at Alvarez & Marsal – Business Transformation Services (L-R)

In this era of technological revolution, very few innovations have sparked as much excitement as generative artificial intelligence (AI), with interfaces such as ChatGPT having garnered over 100 million users within two months of launch. Most businesses have started realizing that Generative AI offers a remarkable opportunity to drive operational efficiencies and unlock unprecedented levels of agility and responsiveness in key functional areas of business. One such key function that stands to benefit significantly from the transformative potential of generative AI is supply chain. The global generative AI supply chain market is expected to grow to ~USD 10 Bn by 2032, at a CAGR of 45.3 per cent. The intricate nature of supply chain disruptions, stemming from factors such as supplier issues, unforeseen market changes, geopolitical events, pandemics, and natural disasters have been too complex for humans to pre-empt. Against this backdrop, generative AI emerges as a transformative tool, with its ability to analyze real-time big data, decipher complex patterns and offer proactive solutions.

The adoption of generative AI thus promises higher planning accuracy, streamlined operational efficiency, and enhanced compliance with Environmental, Social, and Governance (ESG) standards, which has not gone unnoticed by CXOs. A recent Gartner survey highlights that 50% of supply chain organizations are planning to implement Generative AI over the next 12 months, with 14% already in the implementation stages. Further, 65% of Chief Supply Chain Officers plan to hire dedicated experts, allocating 5.8% of functional budgets to this technology. This growth is underpinned by its multifaceted applications across the entire supply chain.

Planning – AI can significantly improve insights from demand sensing and forecasting by assimilating massive data-sets including historical sales, seasonal variations, market trends, social media sentiment, and external factors such as weather patterns and geopolitical issues. Replenishment signals in response to this advanced demand sensing will ensure optimal inventory levels and prevent stockouts.

Sourcing – Procurement and supplier management can be enhanced with AI by generating complex specifications, scenarios for automated supplier selection and automated contract evaluation and negotiating. It can also support contract management and ongoing supplier relationship management by analyzing past supplier interactions, contract terms and performance records.

Manufacturing – Generative AI can be integrated with inputs from shop floor machinery and equipment to analyze data, historical maintenance records, and equipment performance metrics to enable predictive maintenance and enhanced quality control.

Logistics – AI models can create optimized delivery routes, dynamically adjust schedules, and allocate resources efficiently by analyzing external factors such as weather conditions, traffic congestion, transport capacities and customer preferences. While Generative AI has significant and transformational benefits across the supply chain, it is an evolving technology, and challenges including inherent biases, misinformation and cyber security risks need to be addressed during implementation.

ROI-driven Approach Is Key – Generative AI implementation, like any other digital program, needs to be driven through a robust business case with attractive ROI, execution plan and change management, focusing on ‘bottom line’ results. It is also important for companies to evaluate where the technology can create most value, in context of their industry, operating model nuances and the digital maturity curve.

  1. Off-the-shelf Tools Can Be Leveraged to Minimize Time and Cost of Implementation

There are numerous Generative AI tools and solutions that have already been developed in a “plug-and-play” model with global ERP platforms, with the booming Indian startup ecosystem improving the availability of such solutions at a reasonable cost. Organizations may consider leveraging such solutions with necessary customization to fast-track implementation and minimize investments.

  • Checks and Balances Need to Be Established to Combat Risks

Organizations must establish necessary checks and balances to ensure deployment in a transparent, secure and responsible manner. Human oversight must be strategically introduced to monitor high-risk/ value processes and necessary boundaries must be created to prevent complete automation of such tasks.

Why Generative AI Is Here to Stay

The benefits offered by Generative AI in developing truly adaptive supply chains are too compelling to overlook. The opportunity only increases by the day, with the emergence of new targeted models for specialized applications and new plug-ins which can work with varied data sources. The future of adaptive and responsive supply chains lies in the hands of those who navigate this transformative journey with financial prudence, transparency and bottom-line focus to maximize value.