EP 10 — Novelis's Pushpal Jagdale on AI Business Cases That Operations Will Approve

Novelis's IT BRM of Manufacturing & Operations Pushpal Jagdale’s approach to manufacturing transformation challenges the technology-first mentality that derails most digitization efforts. His experience scaling connected systems across hundreds of machines at Honeywell, then transitioning to safety-critical AI applications at Novelis, illustrates why business alignment trumps technical sophistication in successful deployments.

Pushpal shares his methodology for cataloguing legacy assets before attempting any connectivity projects, explaining how understanding which machines can actually integrate with enterprise networks prevents expensive pilot failures. The conversation with Jennifer and Andrew also explores how safety-focused AI applications create the strongest business cases in heavy manufacturing environments. 

  

Topics discussed:

• Asset cataloguing methodologies for legacy system integration before attempting digital transformation initiatives across global manufacturing operations.
• The strategic approach to AI business case development that starts with personal productivity applications like meeting transcription before advancing to factory-specific implementations.
• Safety-first AI deployment strategies using autonomous inspection robots in hazardous environments to eliminate operator exposure risks.
• Global scaling frameworks for digital transformation that account for non-standardized assets, processes, and product portfolios across international facilities.
• IT-OT alignment strategies that transform traditional client-vendor relationships into true partnerships through shared vision and collaborative execution models.
• Data strategy fundamentals as the foundation for successful AI deployment, including quality requirements and contextualization of legacy equipment outputs.
• Predictive maintenance applications using sensor-mounted machine learning models that integrate vibration, temperature, and torque data with product and process information.
• The evolution from discrete electronics manufacturing to metals processing and how core operational objectives remain consistent across different manufacturing environments.
• Knowledge management AI systems that convert SOPs and training materials into searchable troubleshooting resources for new engineers working with legacy equipment.

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