Beyond the Hype: Real-World AI Strategies Panel

Most companies are stuck in the 'crazy phase' of AI. Learn how leaders at SAP and Mercedes-Benz are moving beyond the hype to deliver real-world value.

#1about 4 minutes

How SAP integrates generative AI into enterprise software

SAP embeds generative AI across its platform with a multi-model approach and develops its own foundation model for complex tabular data.

#2about 3 minutes

Using AI to boost developer productivity at Mercedes-Benz

Mercedes-Benz leverages both on-premise and partner AI models, achieving significant productivity gains by deploying tools like GitHub Copilot to its developers.

#3about 3 minutes

Common patterns and challenges in enterprise AI adoption

Accenture observes that while companies are actively experimenting with enterprise GPTs and knowledge management, scaling these AI initiatives remains a significant challenge.

#4about 5 minutes

Implementing responsible AI with governance and sandboxing

Companies like SAP and Mercedes-Benz enable developer experimentation in sandboxed labs while enforcing strict governance and certification for high-risk AI use cases.

#5about 5 minutes

Balancing AI's energy consumption with its efficiency gains

While generative AI consumes significant energy, it can also drive major efficiency gains in areas like manufacturing, necessitating a focus on frugal and carbon-aware computing.

#6about 3 minutes

Why curiosity and continuous learning are key for developers

The future for developers in the age of AI requires a "learn-it-all" mentality, as the core work shifts more towards reasoning and architecture rather than just writing code.