Enterprise AI is becoming increasingly popular among businesses, prompting them to reevaluate their architecture for integrating the technology. The initial hype surrounding AI in the public cloud has shifted towards greater investment in open ecosystems and the use of smaller models that can run at the edge of a business’s network. These edge applications range from chatbots stored on laptops for offline use to AI managing data from sensors in smart manufacturing.
As customers demand more AI at the edge, businesses are reassessing their understanding of AI architecture compared to previous years. In an interview with Dermot O’Connell, senior vice president for EMEA services at Dell Technologies, recorded live at Dell Technologies World 2024, Rory delves into the changing landscape of enterprise AI adoption and strategies for businesses to prepare themselves for it.
O’Connell highlights the importance of running applications at the edge and using containers to support modern applications in a modular way at the location where data, sensors, or cameras are situated. This approach minimizes latency by avoiding constant data transfer back and forth, enabling real-time operations. Despite being in its early stages of deployment, many businesses are starting with projects such as avatars, chatbots, and coding engines, reflecting a relatively basic level of engagement with the technology.
In preparing for AI adoption, O’Connell emphasizes taking small, manageable steps that do not compromise data privacy or security. He suggests considering entry points for AI for employees and customers as a way to gradually introduce the technology into the business ecosystem. By focusing on manageable chunks and identifying non-sensitive data, businesses can initiate discussions on data governance and gradually expand their AI initiatives.
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