In the midst of all the technological advancements happening today, one term has taken over almost every discourse about technology: artificial intelligence (AI). Once a thrilling notion for Sci-Fi movies, AI is now an indisputable reality, and it has taken multiple industries by storm. From Large Language Models (LLMs) enabling fantastic chatbots like ChatGPT to Internet-of-Things (IoT) devices bringing about Industry 4.0, AI has found applications and use cases across almost every modern industry. While the majority of AI implementations have taken place centrally on cloud servers, there has been a strong pursuit for intelligence to be deployed locally at the edge.

Artificial intelligence at the edge is referred to as Edge AI, and it is the convergence of AI model deployment with edge computing. By bringing computational power closer to the data source, Edge AI offers real-time data processing on edge devices with reduced latency, higher bandwidth efficiency, enhanced reliability, and more robust security and privacy. This has the potential to propel AI capabilities beyond its current centralized, cloud-based structure. As the adoption of Edge AI continues to grow almost exponentially, we will witness a paradigm shift in how businesses deploy and utilize AI, especially with edge computing decentralizing data processing.

Industries that require real-time data processing capabilities are the primary industries in Edge AI’s scope of impact and are expected to experience a radical transformation as a result. Embracing this dramatic shift is essential for businesses that seek to stay ahead of the competition and leverage the benefits of real-time, context-aware decision-making. But knowing that Edge AI impacts every industry differently, how can a business in a specific industry embrace this technology to ensure it keeps pace with its rapid evolution?

Accordingly, Wevolver has partnered with several major companies and thought leaders in this space to produce this holistic report on the state of Edge AI in 2024 and its applications in every relevant industry, from healthcare to industrial IoT and manufacturing, smart cities, retail, energy, agriculture, and automotive. Each industry is covered by a dedicated chapter that provides industry-specific insights, descriptions, and examples, complemented by featured sections of real-world case studies. The report also provides a peek into the exciting generative AI technology and its convergence with edge computing before delving into the challenges still hindering Edge AI today. Finally, it gives a glimpse into the future of Edge AI and how it will develop in the years to come.

Report Highlights:

• #1: Industry-specific insights– Each industry is covered by a dedicated chapter that provides industry-specific insights, descriptions, and examples. ,

• #2: Real-life case studies – Get comprehensive insights from featured sections of real-world case studies.

• #3: A look into the future – The report also provides a peek into the exciting generative AI technology and its convergence with edge computing before delving into the challenges still hindering Edge AI today.