Supercharging your Gen AI Applications within the Automotive Industry
The automotive industry is undergoing a digital transformation, with data emerging as one of its most valuable assets.
However, the challenge lies in how to collect, structure, and utilize this data effectively. Automotive Data Lakes present a powerful solution, but organizations must determine what data sources to include, how to integrate them seamlessly, and which AI-driven use cases will generate tangible value. Additionally, both automotive dealers and part suppliers must navigate the complexities of data security, disparate legacy systems, operational efficiency, and strategic implementation to maximize AI’s potential.
To fully realize the value of Automotive Data Lakes, companies must transition from viewing data as a by-product to treating it as a core strategic asset. By leveraging Generative AI (GenAI), organizations can extract meaningful insights, improve customer experiences, and optimize supply chains. This requires a shift towards a data-first approach, ensuring scalability, security, and interoperability between legacy systems and modern AI frameworks.
A successful Automotive Data Lake strategy should focus on streamlining data migration, integrating AI-driven automation, and unlocking new strategic models. As such, our morning sessions will be dedicated to exploring these themes through interactive presentations and discussions led by a dedicated team of experts and thought leaders from AWS.
Agenda
Discussion topics
What defines an Automotive Data Lake and what data sources should be included?
What are some of the GenAI use cases that are derived from having an Auto Data Lake?
What are the key developments that will support the creation and leveraging of Automotive Data Lakes?
What type of customers benefit from Gen AI in the Automotive space, (both dealers and parts markets)?
About GDS
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