SOCIETE GENERALE & ARTEFACT at AI for Finance by Artefact – AI Strategy for Société Générale

The AI strategy of Société Générale, led by Christophe, focuses on two main convictions: AI is seen as the missing piece for unlocking the value in digitalized processes, particularly in handling unstructured data like emails. The bank has been digital for decades, but many processes remain manual, highlighting the need for AI-driven solutions. AI’s ability to handle large-scale unstructured communication, such as emails and external messages, offers transformative potential.

The second key conviction is that the true value of AI is not solely found in the most advanced, cutting-edge technologies but in how AI is combined with other tools such as traditional machine learning and basic digitalization to re-engineer existing business processes. Société Générale’s strategy is not about chasing the latest AI trends or creating isolated use cases. Instead, the focus is on leveraging AI across the organization to generate meaningful, scalable impact. By integrating AI with established technologies, the bank seeks to create deep, transformative changes in how it operates. This approach ensures that AI is embedded into the fabric of the bank’s operations, contributing to lasting improvements in business processes and customer experience.

This AI-driven transformation aligns closely with Société Générale’s overarching strategy of operational efficiency and risk management. The bank has identified six key areas to focus on, such as Know Your Customer (KYC), handling client inquiries, and automating back-office processes. These areas offer immediate opportunities for AI to streamline workflows and reduce manual tasks, leading to improved productivity and enhanced risk management capabilities.

The bank’s portfolio already contains around 300 use cases, but they aim to deepen their efforts in a few specific areas, especially automating client-facing and internal processes. AI co-pilots and assistants are being tested to support call centers and branch advisors, while back-office processes in wholesale and retail banking are being re-engineered. Additionally, AI tools for developers, data management, and risk control automation are also areas of focus.

In terms of return on investment, Société Générale expects substantial gains from these AI-driven transformations. The bank projects to surpass its previous goal of €500 million by 2026. Early pilots show promising results, with double-digit productivity improvements and faster development timelines, allowing for more efficient scaling of AI applications.

Scaling AI across the organization is a top priority, and Société Générale is restructuring its execution capacity with a central team of around 400 professionals, including data scientists, engineers, and process experts. The bank is also standardizing its technology stack and embracing a public cloud-first approach to ensure consistency in AI and data-driven efforts across all business units.

Finally, while AI adoption presents challenges, particularly in terms of regulation and workforce management, Christophe emphasized the importance of viewing AI as an opportunity. Effective change management, including training and reskilling employees, is key to ensuring a smooth transition as AI reshapes the way Société Générale operates, driving further digitalization and operational excellence.