Artificial Intelligence (AI) and Generative AI (GenAI) can be a double-edged sword. On the one hand, this emerging tech holds transformative potential, rewriting the book on data analytics, automation and application design.
 
On the other hand, AI brings with it a dramatically increased demand for data processing and compute power. That means a larger carbon footprint that may conflict with your customers’ environmental, social, and governance (ESG) priorities.
 
Dell Technologies understands the importance of your customers’ sustainability goals. Together, you can offer your customers GenAI-powered platforms that help align their sustainability goals.
 
A growing issue
Demand for data processing is on the rise. If your customers want to leverage AI to derive insights from vast datasets, they must contend with a substantially increased demand for the energy and resources required to train and run large AI models.
 
Power-hungry AI models force your customers to address environmental concerns as they attempt to balance their AI adoption with their sustainability commitments. This presents an opportunity for you to help them deploy new, more sustainable technology, opening new revenue streams for your business.
 
AI-Powered PCs: innovative sustainability
Among the many solutions now in practice to improve sustainability efforts, AI-enabled PCs are fast becoming a staple of modern business fleets. Laptops and convertibles like the new Latitude AI PCs can play an important role in prototyping, developing, fine-tuning and inferencing GenAI models.
 
So-called “local computing” reduces demand at the core, shrinking your customers’ data center carbon footprint and energy usage. Running complex AI workloads locally on AI-enabled PCs also increases cost-effectiveness, improves security, and reduces latency.
 
Help your customers achieve their goals, sustainable
To learn more about how you and your customers can partner with Dell Technologies to leverage AI while advancing sustainability efforts, read the new Dell blog Addressing the Environmental Footprint while Optimizing the Handprint of AI.

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