The AI Interview: Kaynaz Behdin

2026-06-12 · Source: AI Magazine · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management, Project & Product Management · Depth: Intermediate, medium

Summary

Kaynaz Behdin, SVP of Digital, Data & AI at Stellantis, outlines the automotive giant's strategy for transforming AI initiatives into measurable business performance, moving beyond mere experimentation. Her global remit encompasses data, AI, cloud infrastructure, and enterprise platforms, emphasizing governance, operating models, and adoption alongside technology. Stellantis employs a three-layered distributed AI strategy, embedding AI and Data Business Hubs into functions and leveraging global platforms for industrial-scale delivery across its entire value chain, from sales to manufacturing. Prioritization is guided by a value framework focusing on business ownership, scalability across plants and regions, and strict safety and compliance. The company addresses organizational and human barriers through an AI Academy and is actively deploying agentic AI solutions like an Agent Gateway and Metabot, with governance designed as an accelerator for innovation and adherence to regulations like the EU AI Act.

Key takeaway

For Directors of AI/ML or VPs of Engineering tasked with scaling AI across a large enterprise, your focus must shift from experimentation to disciplined, measurable business performance. Prioritize initiatives with clear business ownership and cross-functional scalability, ensuring robust governance acts as an accelerator, not a barrier. Invest in an AI Academy to address human and organizational adoption challenges, and deploy secure agentic AI infrastructure to integrate intelligent systems into daily workflows, aligning with regulations like the EU AI Act from day one.

Key insights

Stellantis drives AI for measurable business performance, integrating it deeply across operations with robust governance.

Principles

• AI must be an enterprise capability, not just experimentation.
• Prioritize AI use cases based on business ownership and scalability.
• Governance should accelerate innovation, not impede it.

Method

Stellantis' AI strategy involves a three-layered distributed operating model: leadership priorities into execution, embedded AI/Data Business Hubs, and global platforms for industrial delivery.

In practice

• Implement an AI Academy for workforce upskilling and role evolution.
• Deploy an Agent Gateway for secure AI agent interaction with enterprise platforms.
• Build risk assessment and auditability into the data-to-AI lifecycle.

Topics

• Enterprise AI Strategy
• AI Governance
• Agentic AI
• Automotive AI Applications
• Digital Transformation
• Workforce Development

Best for: Executive, Director of AI/ML, VP of Engineering/Data, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Magazine.