From Data to Decisions: Operationalizing AI in Manufacturing IT/OT Ecosystems

In today’s manufacturing landscape, organizations are generating vast amounts of data across both Information Technology (IT) and Operational Technology (OT) environments. However, the real challenge lies in transforming this data into actionable intelligence that drives timely and effective decision-making at scale.

This highly interactive 3-hour workshop, led by Shuvdeep Bhattacharya, IT Director – Seating Engineering at Lear Corporation, is designed to go beyond theory and actively engage participants in the journey of operationalizing Artificial Intelligence (AI) within manufacturing ecosystems. Drawing from real-world transformation experiences at Lear, the session will combine strategic insights with collaborative, hands-on learning.

The workshop will begin with a concise overview of IT/OT convergence and the foundational elements required for Industrial AI—such as data readiness, architecture, integration, and governance. This will set the stage for deeper exploration into how AI can be embedded into engineering systems and shop-floor operations to enable predictive, data-driven decision-making.

A key differentiator of this session is its participatory format. Attendees will be organized into small groups for table-top discussions, where they will work through realistic scenarios inspired by challenges commonly faced in manufacturing environments—such as breaking down data silos, scaling AI beyond pilots, or integrating legacy OT systems with modern AI platforms. Each group will collaborate to define approaches, prioritize use cases, and outline solution strategies.

These discussions will culminate in team presentations, where participants will share their perspectives, approaches, and key insights. This peer-driven exchange fosters cross-industry learning and enables attendees to gain diverse viewpoints on tackling similar challenges.

Complementing these activities, Shuvdeep will share real-life examples from Lear’s AI and digital transformation journey, including use cases such as predictive analytics in manufacturing operations, anomaly detection for quality improvement, and AI-enabled engineering workflows. These examples will provide practical context on what it takes to move from experimentation to enterprise-scale deployment, including key lessons learned and success factors.

The session will also highlight how emerging technologies—such as cloud platforms, edge computing, and digital twins—are enabling scalable AI adoption across IT/OT ecosystems.

By the end of the workshop, participants will:

• Understand how to operationalize AI in manufacturing IT/OT environments

  
  

  Learn how to move from data collection and pilots to scalable, production-grade AI solutions.

• Gain a practical framework for IT/OT convergence

  
  

  Understand how to connect enterprise systems with shop-floor operations for seamless data flow and intelligent decision-making.

• Learn from real-world applications at Lear

  
  

  Explore practical AI use cases, including predictive analytics, anomaly detection, and intelligent engineering systems.

• Develop hands-on strategies through group collaboration

  
  

  Participate in table-top exercises to solve realistic challenges and co-create actionable approaches.

• Benefit from peer learning and diverse perspectives

  
  

  Engage in team presentations to exchange ideas, validate approaches, and learn from other participants’ experiences.

• Identify common challenges and success factors

  
  

  Gain insight into data readiness, integration complexity, governance, and organizational alignment.

• Build a roadmap for AI adoption

  
  

  Leave with actionable next steps to assess maturity, prioritize use cases, and scale AI initiatives in their organizations.