Mike Butcher, Jürgen Müller, Katrin Lehmann & Tobias Regenfuss
Beyond the Hype: Real-World AI Strategies Panel
#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.
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Rapid-fire thoughts on the future of work
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