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Ambica Rajagopal, Group Chief Data and AI Officer, Michelin Group

Describe your career to date

I started my career as a data scientist and grew into my current role as Chief Data and AI Officer, as the technology itself grew into maturity. Business impact is always my aim and guiding companies through mindset change, probabilistic understanding of risk, trust deficit in new technologies are my passions and skills. I build high performance teams by putting technical depth, trust and customer empathy at the core of the team.

Under my leadership, machine learning and artificial intelligence (AI) technologies have been widely applied in manufacturing excellence, R&D, and sales and marketing, with several AI systems in production. This has resulted in efficiency gains, monetary savings, and deeper understanding of the processes.

I am active in global AI networks and industry forums guiding the development of AI as a technology, with a specific focus on manufacturing and industrial use cases.

How are you developing the data literacy of your organization, including the skills of your data teams and of your business stakeholders?  

Data literacy is a pillar of data transformation that is critical to us, and we have a team dedicated to it, to achieve upskilling and reskilling at enterprise scale. We have launched learning paths which are curated courses, webinars, and in-person sessions focused on building skills by persona. These learning paths are available for managers, factory workers, data engineers, data scientists, and executives. We have seen wide adoption and track it actively on a global scale. We also do many outreach events for individual departmental leadership teams, with in-depth onboarding on data topics.

What role do you play in building and delivering conventional artificial intelligence solutions, including machine learning models? Are you also involved in your organization’s adoption of generative AI? 

In my role as Chief AI Officer, my teams have driven an AI transformation over the last three years in the group, leading to over 100 million euro in business value. My focus has been to build a strong technical team, with deep expertise in AI as applied to Michelin business and processes. We have multiple large forecasting initiatives, image analysis for tires, social listening for customer, reinforcement learning for adaptive process control in deployment.

In response to the generative AI (genAI) disruption, we targeted specific four areas: individual productivity for knowledge workers, genAI for software development, knowledge assistants to break information silos and fluent customer interactions. We have explorations and deployments ongoing in all four, with many custom co-pilots deployed internally.

How are you preparing your organization for AI adoption and change management?

At Michelin, the utilization of AI to revolutionize processes and enhance efficiencies is actively underway. Today, over 100 AI proof of concepts are being driven by our robust research and discovery culture at Michelin.

Our primary challenge lies in expanding the adoption of AI to meet the high standards set for both our employees and customers. However, this challenge is not unique to us; across various industries, enterprises encounter hurdles in embracing AI technologies.

AI demands a comprehensive grasp of computing, mathematics, and statistics, coupled with domain expertise, all underpinned by a responsible deployment approach. At Michelin, we have cultivated strong internal and external partnerships, which are pivotal in accelerating our AI journey.


Ambica Rajagopal
has been included in:
  • 100 Brands 2023 (USA)
  • 100 Brands 2024 (USA)