As 2023 progresses, demand for AI-powered devices continues growing, driving new opportunities and challenges for businesses and developers. Technology advancements will make it possible to run more AI models on edge devices, delivering real-time results without cloud reliance. Edge AI technology has proven its value and we can expect to see further widespread adoption in 2023 and beyond. Companies will continue to invest in edge AI to improve their operations, enhance products (i.e., safer, additional features) and gain competitive advantages. AI's adoption will also be driven by innovative applications such as ChatGPT, generative AI models (e.g., avatars) and other state-of-the art AI models that will be used for applications in medtech, industrial safety and security.

As 2023 progresses, demand for AI-powered devices continues growing, driving new opportunities and challenges for businesses and developers. Technology advancements will make it possible to run more AI models on edge devices, delivering real-time results without cloud reliance. Edge AI technology has proven its value and we can expect to see further widespread adoption in 2023 and beyond. Companies will continue to invest in edge AI to improve their operations, enhance products (i.e., safer, additional features) and gain competitive advantages. AI's adoption will also be driven by innovative applications such as ChatGPT, generative AI models (e.g., avatars) and other state-of-the art AI models that will be used for applications in medtech, industrial safety and security.

In a study published by IBM in May, for example, 94 percent of surveyed executives said their organizations will implement edge computing in the next five years. From smart hospitals and cities to cashierless shops to self-driving cars, edge AI -- the combination of edge computing and AI -- is needed more than ever. Businesses have been slammed by logistical problems, worker shortages, inflation and uncertainty caused by the ongoing pandemic. Edge AI solutions can be used as a bridge between humans and machines, enabling improved forecasting, worker allocation, product design and logistics. While edge computing is rapidly becoming a must-have for many businesses, deployments remain in the early stages.