About Fireside Chat: The Future of Supply Chain with Agentic AI

Description

SCPC successfully hosted a virtual fireside chat under the theme “The Future of Supply Chain with Agentic AI.” The event highlighted the evolution of supply chain operations through the lens of intelligent, autonomous systems — emphasizing how agentic AI can move beyond insights to independently make and act on decisions across complex supply chain functions.

The event began with a Welcome Note by Dr. Rakesh Sinha, Committee Member and Founder-CEO of Reflexive Supply Chain Solutions, setting the stage for a forward-looking dialogue on AI’s growing impact in enterprise supply chains. This was followed by a dynamic conversation led by two expert speakers:

• • Speaker 1: Mr. Arjun Khurana, AI Technology Innovator, Dell
  • Speaker 2: Mr. Saurabh Bansal, Partner & Practice Leader, IBM

Together, the speakers explored the foundations, business value, and real-world applications of Agentic AI.

Core Themes Explored

The discussion was framed around the evolving definition and scope of Agentic AI, highlighting how it differs from conventional AI agents. Specific focus areas included:

• Defining Agentic AI:
  Introducing Agentic AI as a new paradigm where intelligent systems demonstrate autonomy, context awareness, and the ability to take initiative.
• Autonomous Decision-Making:
  Exploring how these agents go beyond programmed responses to make independent decisions in real time.
• From Insights to Action:
  Highlighting the evolution from traditional analytics to fully autonomous operations powered by reasoning and execution engines.
• Role of Large Language Models (LLMs):
  Discussing how LLMs are being used for coordination, planning, and reasoning across multi-agent systems.
• Agentic AI vs. AI Agents:
  Clarifying the key distinctions, particularly around scalability, decision complexity, and collaboration between agents.

Strategic Value Drivers 

The session also highlighted the strategic impact of Agentic AI across the supply chain, emphasizing its potential to deliver measurable business value. Key drivers include:

• Revenue Growth Enablement:
  Through faster decisions, proactive demand response, and smarter sourcing strategies.
• Creation of a Virtual Workforce:
  Automating high-cognition tasks such as supplier selection, negotiation, and logistics planning — augmenting human teams.
• LLM Coordination Across Functions:
  Allowing for seamless orchestration between different processes, data sources, and decision layers.

Real-World Use Cases Discussed

A central part of the session featured practical use cases where Agentic AI is already delivering value in supply chain environments:

• Autonomous Procurement:
  Systems that identify demand, find suppliers, evaluate options, and place orders with minimal intervention.
• Dynamic Inventory Optimization:
  Continuously analysing and adjusting inventory levels based on real-time conditions and forecasts.
• Intelligent Inventory Reallocation:
  Redirecting stock across facilities or regions to match shifting demand patterns.
• Smart Raw Material Sourcing:
  Evaluating raw material needs and identifying optimal sources dynamically.
• Intelligent RfX Management:
  Streamlining the creation, distribution, and evaluation of RFPs, RFQs, and RFIs.
• AI-Powered Negotiation:
  Using autonomous agents to conduct pricing or contract negotiations based on defined objectives and market data.
• Real-Time Logistics Optimization:
  Continuously optimizing transportation routes, loads, and delivery schedules to improve efficiency and reduce costs.

The fireside chat emphasized that Agentic AI is not a future ambition ,it is an emerging reality. As these technologies continue to evolve, organizations that embrace autonomous decision systems stand to gain in agility, responsiveness, and competitive edge.

As supply chains face increasing complexity and volatility, Agentic AI offers a scalable, intelligent path forward.