Edge Artificial Intelligence (AI) Market is Slated to Expand at a Stellar 31.7% CAGR through 2031 On the Back of the Rising Use of Edge Computing

June 18 17:50 2024
Edge Artificial Intelligence (AI) Market is Slated to Expand at a Stellar 31.7% CAGR through 2031 On the Back of the Rising Use of Edge Computing
Skyquest Technology
Edge Artificial Intelligence (AI) Market Size, Share, Growth Analysis, By Component(Hardware (Device [Smartphone, Surveillance Cameras, Robots, Wearables), By End Use Industry(Consumer Electronics Device (Smartphones, Wearables, Entertainment Robots), Smart Homes Device (Smart Speakers), By Region – Industry Forecast 2024-2031

Edge Artificial Intelligence (AI) Market size was valued at USD 15.60 Billion in 2022 and is projected to grow from USD 20.55 Billion in 2023 to reach USD 185.95 Billion by 2031, growing at a CAGR of 31.7% in the forecast period (2024-2031). 

The growing adoption of edge technologies and edge computing is setting the tone for edge artificial intelligence (AI) demand. Deployment of AI algorithms on edge platforms and devices is known as edge artificial intelligence. Better data security and high scalability are key benefits of edge AI solutions that promote market growth.

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The integration of two novel technologies is not a new thing but a crucial trend in the development of advanced digital solutions. Companies can focus on the development of new hardware as well as software solutions to promote the adoption of edge AI over the coming years. Rising penetration of Internet of Things (IoT) technologies and devices is also forecasted to change the tide in favor of edge artificial intelligence (AI) companies going forward. The growing use of connected devices for automation and advancements in connectivity technologies will also create new business scope for market players.

New Edge AI Platforms and Hardware to Remain Central for Global Edge Artificial Intelligence (AI) Market Players

Development of edge AI-specific hardware is a key trend that new as well as established companies should focus on going forward. Rapidly growing connected infrastructure and high adoption of edge computing are also major trends that provide new opportunities for edge artificial intelligence (AI) companies. Advancements in AI technology is also something that edge AI companies should keep a close eye out for going forward. Established edge artificial intelligence (AI) companies should target the launch of new edge AI chipsets, servers, and platforms to maximize their revenue generation potential across the forecast period and beyond. Partnering and collaborating with different companies to bring expertise of both technologies together could also be a good move for edge artificial intelligence (AI) providers in the future.

  • A leading name in full stack AI business known as  Kneron, launched its new AI-based offerings in June 2024. AI-embedded PC and Edge AI servers were launched by the company and the KNEO 330 server can reduce around 30% to 40% costs of small businesses.
  • A Japanese company calledEdgeCortix Inc. Focused on the development of unique AI solutions, announced the launch of its new accelerator to support generative AI applications at Edge in June 2024. SAKURA-II Edge AI accelerator when combined with EdgeCortix’s dynamic neural accelerator (DNA) becomes a unified solution for edge AI users.
  • In May 2024, SourceCode, a company focusing on the development of intelligent infrastructure along with GigaIO launched a new edge AI system. Gryf is a mobile AI platform designed specifically for edge environments to quickly convert huge volumes of data into meaningful insights.
  • AIR-520 Edge AI Server was launched by Advantech to capitalize on the rising use of generative AI around the world in June 2024, and it featured aiDAPTIV+ technology from Phison.

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Edge artificial intelligence (AI) companies have many opportunities to choose from due to this technology’s nascent nature. New edge AI providers should target the development of novel software platforms to support the adoption of edge artificial intelligence whereas established companies should invest in infrastructure and hardware development.

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