SCTS 2026

SUPPLY CHAIN TECHNOLOGY SUMMIT 2026

From Automation to Autonomy – AI, Physical Intelligence & the Next-Generation Supply Chain

14^th October 2026, Wednesday
Bengaluru | 1000Hrs - 1700Hrs

India is entering a new phase of supply chain digitisation. The first wave established foundational platforms—ERP, WMS, TMS, IoT, cloud, analytics and control towers. The next wave is increasingly about intelligence in action: systems that can sense changes in demand and supply, reason through trade-offs, coordinate across functions and partners, and trigger or execute decisions within defined guardrails.

This shift is being accelerated by the convergence of agentic AI, advanced analytics, edge computing, computer vision, digital twins and increasingly capable robotics. In parallel, Physical AI is beginning to change the nature of automation. Instead of rigid, single-task machinery designed for stable environments, supply chains can increasingly deploy adaptive machines that perceive their surroundings, learn from data, collaborate with people and other machines, and respond to changing conditions in real time.

The opportunity is particularly relevant for India. The National Logistics Policy and digital platforms such as ULIP are building the connective tissue for more integrated logistics, while manufacturers, retailers, e-commerce players and logistics providers are investing in automation, visibility and data-led decision making.

Globally, the signal is equally clear. AI and robotics are moving from isolated use cases toward integrated operating models. Control towers are evolving from dashboards into decision and orchestration layers. AI is moving from prediction and recommendation toward guided execution. Robotics is moving from fixed automation toward flexible, sensor-rich and increasingly adaptive systems.

The Supply Chain Technology Summit 2026 will bring together industry leaders, logistics operators, technology innovators and policymakers to explore what it takes to move from digital supply chains to intelligent and increasingly autonomous supply chains. The agenda will focus not on technology for its own sake, but on the operating models, data foundations, governance and business cases required to convert emerging technology into measurable improvements in service, cost, resilience, productivity and sustainability.

The agenda will focus not on technology for its own sake, but on the operating models, data foundations, governance and business cases required to convert emerging technology into measurable improvements in service, cost, resilience, productivity and sustainability.

Report on

Agentic AI layerd on APS transformations

Supply chain planning organizations have spent the last decade investing in APS platforms such as Blue Yonder, o9, Kinaxis, SAP IBP, and Oracle to improve forecasting, inventory positioning, supply planning, and cross-functional alignment. Those systems have materially improved mathematical planning quality, but they still leave large amounts of work to planners: interpreting exceptions, coordinating trade-offs, explaining recommendations, collecting context from fragmented systems, and converting approved plans into downstream execution.

This report examines the next layer on top of APS: agentic AI. In this context, agentic AI refers to LLM-based systems and specialized AI agents that can interpret APS outputs, plan multi-step workflows, retrieve enterprise context, coordinate actions across teams and systems, and in bounded cases execute approved decisions. The report is written for enterprise transformation leaders, planning center-of-excellence heads, digital supply chain leaders, and technology decision-makers evaluating how APS transformations should evolve into AI-enabled planning operating models.

Download

Concept Note

Agenda

SESSION 1

BUILDING THE AUTONOMOUS SUPPLY CHAIN: FROM AI COPILOTS TO MULTI-AGENT DECISION NETWORKS

The traditional control tower is rapidly evolving from a visibility layer into an intelligence and action layer. AI agents are increasingly capable of monitoring signals, assessing constraints, simulating alternatives, collaborating across business functions, and initiating actions within defined governance frameworks.

The next frontier is multi-agent orchestration, where planning, procurement, sourcing, inventory, manufacturing, logistics, and customer-service agents work together to optimize outcomes across the value chain. As organizations move beyond experimentation and isolated AI use cases, the focus is shifting toward enterprise-scale deployment, governance, trust, and measurable value creation.

Agentic AI in supply chain planning and execution
Multi-agent systems across procurement, sourcing, planning, manufacturing, warehousing, and transportation
Control Towers 2.0 and closed-loop decision-making
AI-enabled procurement and supplier collaboration ecosystems
Supplier risk intelligence and predictive sourcing
AI governance, security, auditability, and responsible AI
Building AI-ready data foundations through APIs, master data, knowledge graphs, and semantic architectures

SESSION 2

PHYSICAL AI & ADAPTIVE AUTOMATION: THE WAREHOUSE BECOMES A LEARNING SYSTEM

Warehousing and fulfilment operations are entering a new era where physical assets increasingly possess the ability to perceive, learn, adapt, and collaborate. Traditional automation designed around predictable workflows is giving way to intelligent systems capable of operating effectively in dynamic environments.

Physical AI combines sensing technologies, computer vision, machine learning, robotics, spatial intelligence, and edge computing to create adaptive ecosystems where people, machines, and software work together seamlessly. From robotics and autonomous material handling to real-time optimization and digital simulations, organizations are exploring new opportunities to improve productivity, flexibility, safety, and operational performance.

Physical AI applications in warehouses and fulfillment centers
Adaptive robotics, AMRs, drones, and autonomous material handling systems
Flexible automation ecosystems and brownfield integrationCommentHighlight
Digital twins for warehouse design and operations optimization
Workforce transformation, human-machine collaboration, and future skills
ROI frameworks and scaling intelligent automation

SESSION 3

INTELLIGENT LOGISTICS NETWORKS: CONNECTING ASSETS, DATA & DECISIONS IN REAL TIME

The future of logistics lies in creating connected, intelligent networks that seamlessly link the physical movement of goods with the digital flow of information and decision-making. As supply chains become more complex and distributed, organizations require greater visibility, agility, and responsiveness across transportation, distribution, and partner ecosystems.

Advances in IoT, telematics, computer vision, AI, digital twins, and intelligent transportation platforms are enabling real-time visibility and dynamic optimization across logistics networks. These capabilities can help organizations improve asset utilization, reduce costs, enhance customer service, increase resilience, and advance sustainability objectives.