“What was your return on investment in supply chain planning technology this year?” As 2025 comes to a close, many supply chain leaders are taking stock of their efforts to transform supply chain planning for their businesses. Unfortunately for some, this year’s strategic projects are falling short of expectations. Substantial budget and resources were allocated to deploy new advanced planning systems and AI solutions to improve decision-making. While progress was made, many of these investments yielded less than was expected. We can do better. Industry leaders are achieving breakthrough productivity gains by focusing on the right use cases, applying AI smartly, assessing the promised capabilities accurately and driving adoption of new planning solutions. By taking an agentic approach to supplement out-of-the-box APS functionality, these leaders are achieving the measurable business impact hoped for when they embarked on their digital transformations. Join Supply Chain Now hosts Scott Luton and Karin Bursa as they welcome special guests Caglar Ozdag and Jim Lee from ZS to discuss how supply chain leaders are getting it right. By sharing tangible examples from across industries, Caglar and Jim will articulate how leaders are achieving superior ROI on supply chain planning investments. They will propose a new…

In this Agentic Age, Supply chain leaders are racing to adopt AI—but isolated solutions and disconnected systems often limit real impact. The true promise of AI emerges only when we reimagine the supply chain as a fully connected enterprise, breaking down decades-old silos across planning, logistics, materials, finance, and sustainability. In this session, Manik Sharma, Head of Supply Chain GTM AI at Celonis—magic quadrant leader, recognized globally and ranked #3 on the Fortune 50 Most Promising Companies list—will unpack how a modern AI-enabled tech stack can unify fragmented data, systems, and processes through a connected semantic layer that digitizes the physical value chain. Once established, this semantic layer becomes a dynamic foundation for intelligent, data-driven operations by infusing it with enterprise context—from rules, constraints, and parameters to policies and proven models—unlocking true end-to-end enterprise intelligence. This intelligence can then be democratized across the organization to power self-serve analytics, build composable AI solutions, and orchestrate workflows, collaboration, agents, and actions at scale. We’ll explore how companies are using this approach to unlock self-serve analytics, accelerate development of composable AI applications, and orchestrate autonomous workflows and agents at scale. This is not a future vision but a proven path for organizations that…