Leading analyst house Omdia has today released its latest report identifying the key areas for growth for AI-at-the-Edge. 'Connecting The Dots: AI at the Edge' has found that more compute is needed at edge locations to manage and support new and proliferating latency-sensitive IoT devices and software technologies that are analysing an increasing amount of data. This demand for greater data collection and analysis is creating a major challenge for network bandwidth and a pressing need for greater security options. IoT is one of the main drivers for the need for AI at the Edge, however the requirement is being driven by a number of different applications across multiple vertical markets. The latest 'Connecting The Dots' report focuses on the five key factors which will shape the AI-at-the-Edge opportunity over the coming years, as well as a short term and long term outlook of practical uses for AI-at-the-Edge across key markets. Five factors that will shape AI-at-the-Edge: - New and emerging edge use cases. While smartphones may have been the tip of the spear for AI-at-the-edge devices, emerging use cases from enterprise and industrial will be what drives future growth. - Diverse, cost-effective silicon solutions. AI has been a key driver for silicon growth in the high-end processor market for the past several years, but what will enable AI to proliferate at the edge will be a diverse portfolio of processors that can address a range of use cases. - New compute ecosystem from cloud to edge. Distributed computing technologies such as Kubernetes have made hybrid and distributed cloud infrastructures more manageable and operationally agile. The server market is already seeing the impact of this trend. - CSPs utilize AI at the edge to optimize for AI at the edge. In order to offer compelling AI services at the edge, CSPs are also adopting AI at the edge to achieve low latency for new services, improve customer experience, and reduce costs. - Broad range of industry verticals with specific requirements. Video surveillance is just one area where on-device AI is enabling a fundamental shift in the industry. Other industries, from fast food to oil & gas, are also seeing the benefits of deploying on-device AI. Bill Morelli, Vice President for Enterprise at Omdia, commented: "Over the past few years, AI has moved from the experimental phase to commercialisation stage. AI in the cloud is now a reasonably established technology being implemented by a variety of business processes. As a result of this, there are now a number of compelling use cases within AI that require Edge technologies." "To meet this demand and requirement, a diverse range of silicon products have emerged. Capability has finally caught up with the need for AI at the Edge solutions. This marrying of requirement and technology will drive the space for many years to come across multiple sectors to provide better business outcomes and solutions." The AI-at-the-Edge report also identifies a short- and long-term outlook across five key areas including manufacturing, healthcare, smart buildings, utilities and video surveillance. Short Term Outlook for AI-at-the-Edge across vertical markets (2020): - Manufacturing: With limited edge expertise and edge products new to market, applications (bar vision) will continue with threshold analytics rather than "true AI" machine learning. - Healthcare: The COVID-19 pandemic has accelerated AI software development, especially in AI-based drug and vaccine research, medical imaging, and machine learning tools for patient screening, triage, and monitoring. - Smart Buildings: Facilities have connected hardware but are not analyzing/maximising the power of their data. - Utilities: Increasing spend on software and analytics, but typically as modular, "add-on" pieces. - Video Surveillance: Controversy will remain around the use of analytics for personal analysis such as facial recognition. However, little legislation is expected to have an impact. Long Term Outlook for AI-at-the-Edge across vertical markets (2021 and beyond): - Manufacturing: Edge compute and control devices from IT companies will shift strategic relationships from cooperation to competition with incumbent OT vendors for control level products. - Healthcare: The lack of regulatory approval (e.g., FDA) will be a barrier to deployment of self-learning algorithms. However, this will not hinder deep learning analytics. - Smart Buildings: Increased spending on both centralised building management software and on AI-enabled hardware at the edge. - Utilities: In the next five years, companies without a strong AI-driven software and services business will see a significant drop in hardware sales. - Video Surveillance: Technology will be used to offset against ASP decline within the hardware market. The 'Connecting the Dots: AI-at-the-Edge' report is available for free download. About Omdia Omdia is a global technology research powerhouse, established following the merger of the research division of Informa Tech (Ovum, Heavy Reading and Tractica) and the acquired IHS Markit technology research portfolio*. We combine the expertise of over 400 analysts across the entire technology spectrum, analyzing 150 markets publishing 3,000 research solutions, reaching over 14,000 subscribers, and covering thousands of technology, media & telecommunications companies. Our exhaustive intelligence and deep technology expertise allow us to uncover actionable insights that help our customers connect the dots in today's constantly evolving technology environment and empower them to improve their businesses – today and tomorrow. Omdia is a registered trademark of Informa PLC and/or its affiliates. All other company and product names may be trademarks of their respective owners. Informa PLC registered in England & Wales with number 8860726, registered office and head office 5 Howick Place, London, SW1P 1WG, UK. Copyright © 2020 Omdia. All rights reserved. *The majority of IHS Markit technology research products and solutions were acquired by Informa in August 2019 and are now part of Omdia. SOURCE: Omdia