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Today, one of the most dynamic and promising sectors is the delivery of items by autonomous robots and drones. This industry is on the verge of breaking out as soon as the hardware is fully developed and regulations and traffic management systems are in place to allow the safe and reliable transport of goods with these technologies. Intensive R&D efforts by leading players are moving the industry forward through innovation and competition.

The dramatic growth projected for the global delivery robot market from 2019 to 2025 will provide rich opportunities for established companies and startups that produce robots, drones, related components, and services, as well as investors and researchers. As companies become aware of the growing importance of and uses for delivery robots, a gap remains in understanding exactly how they will work and the implications for their businesses. The outlook for delivery robots, delivery drones, and autonomous delivery vehicles will be driven by robust demand from e-commerce fulfillment, food & beverage sales, and logistics. The COVID-19 pandemic is expected to spur the development of favorable regulations and technologies and attract more investment to this industry. Omdia expects the overall delivery robot market to grow from $121.0m in 2019 to $2.2bn by 2025.

This Omdia Focus Report provides a concise examination of the market issues surrounding delivery robots and presents 6-year revenue forecasts. The report discusses the crucial market drivers, challenges, and industry applications, in addition to assessing the most important technology issues that will influence market development. Omdia profiles the top 20 industry players, organized by robot type. Global market forecasts, segmented by delivery robot type, market, and geographic region, extend through 2025.
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Table of Contents
1. Executive summary
2. Market issues
3. Key industry players
4. Market forecasts
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Key Market Forecasts
. Delivery robot market overview, world markets: 2019-25
. Delivery robot revenue by type, world markets: 2019-25
. Delivery robot revenue by market, world markets: 2019-25
. Delivery robot revenue by region, world markets: 2019-25
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The COVID-19 pandemic is causing changes in how people work and interact-and especially in how healthcare is provided. With embattled countries facing a health crisis of global proportions, thousands of robots and drones are being deployed in hospitals, on the streets, in public buildings, and in the skies around the world to combat the spread of the SARS-CoV-2 virus that causes the COVID-19 illness. Healthcare professionals and businesses are finding innovative ways to use robots and drones to help patients and those in quarantine.

The market for healthcare robots was already emerging, and now the pandemic is adding impetus to market growth. The stimulating effects are expected to boost development, demand, and investment in this industry. Robotics companies, integrators, and value-added suppliers have many opportunities to service this sector and gain market share and mindshare. The pandemic is also attracting investment for both existing companies and startups that want to take advantage of the current momentum in the healthcare robots market. All of this presents a chance for large companies to diversify and for small companies to identify and develop products and services for niche healthcare markets. Omdia expects the global healthcare robots market to grow from $1.9bn in 2019 to $5.4bn by 2025.

This Market Landscape report explores some of the ways robots are helping to combat the pandemic. Omdia examines how this health crisis will affect both the robotics industry and the healthcare industry now and in the future. The report provides a concise examination of the market issues surrounding healthcare robots and drones and presents a market outlook through 2025 that assesses the impact of the COVID-19 pandemic. It discusses crucial market dynamics and industry applications, in addition to providing recommendations for healthcare enterprises and vendors. Omdia also provides a categorized list of the top 24 industry players, organized by application.
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Table of Contents
1. Summary
2. Recommendations
3. Market Status
4. Market Dynamics
5. Market Outlook
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Key Market Forecasts
. COVID-19 impact on healthcare robots, world markets: 2019-25 world markets: 1Q20
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The global robotics market has shifted from an industrial focus toward non-industrial robots. New robot technologies have made new use cases possible in recent years. While some of this progress is due to improvements in hardware, many of these innovative use cases are made possible by advances in artificial intelligence (AI), machine vision, and machine learning. Emerging markets include consumer robots, commercial unmanned aerial vehicles (UAVs), autonomous vehicles (AVs), and delivery robots.

In 2020, the global COVID-19 pandemic has caused disruptions to the availability of components, production in factories, and demand from end users. This has resulted in an overall contraction in the industry during 2020 that will likely to extend into at least part of 2021. On the other hand, the need for business continuity related to production and logistics in the future is likely to fuel demand for robotic solutions once the global economy starts to recover. Despite setbacks, Omdia expects continued and expanded growth in the robotics industry, especially for non-industrial applications in logistics, smart manufacturing, and AVs. These emerging applications are expected to boost the market from $60bn in 2019 to $286bn by 2026.

This Omdia report provides a concise sizing of the robotics market with revenue and shipment forecasts and analysis. Global market forecasts, segmented by robot type, market, and geographic region, extend through 2026.
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Table of Contents
1. Executive summary
2. Definitions and scope
3. Market data highilights
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Key Market Forecasts
. Total industrial and non-industrial robotics revenue, world markets: 2019-26
. Total robotics revenue and shipments by application market (detailed), world markets: 2019-26
. Total robotics revenue and shipments by region, world markets: 2019-26
. Total robotics revenue and shipments by robot type, world markets: 2019-26
. Total robotics technology attach rates, world markets: 2019-26
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The artificial intelligence (AI) software market has experienced tremendous growth over the past several years. Many enterprises have discovered that AI software can help cut costs and generate new revenue streams. Yet, AI software remains a relatively small portion of overall software sales, with varying acceptance across industries. The AI software market has entered a new phase in which AI is a requirement for most enterprises to compete on a global level. Significant opportunity lies ahead for AI software market penetration despite short-term economic and market turbulence from the COVID-19 pandemic.

AI software employs several different technologies that give computers human-like abilities of perception, reasoning, planning, and decision-making. Most AI systems today are machine and deep learning (ML and DL) systems; other technologies include natural language processing (NLP), computer vision (CV), machine reasoning (MR), and strong AI. Omdia has built a taxonomy of 340 AI use cases across 23 industries that captures the software opportunity related to AI. A new breakout aggregates the 340 use cases to 14 horizontal markets. Under the moderate impact scenario, global AI software revenue is expected to grow at a 34.9% CAGR to reach nearly $100bn in 2025.

This Omdia report provides a quantitative assessment of the market opportunity for AI software. To assess the COVID-19 impact, Omdia outlines four forecast scenarios through 2025. The study includes market sizing, segmentation, and forecasts for 340 AI use cases, including more than 200 unique use cases. Global market forecasts, segmented by scenario, use case, industry, technology, geography, horizontal market, and meta category, extend through 2025.
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Table of Contents
1. Executive summary
2. Market definitions
3. Technology issues
4. Market forecasts
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Market Forecasts
. AI software revenue forecast scenarios, world markets: 2019-25
. AI software revenue by region, world markets: 2019-25
. AI software revenue by technology, world markets: 2019-25
. Cumulative AI software revenue by industry, world markets: 2019-25
. AI software revenue by industry: COVID-19 impact vs. 2019-25 CAGR
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Enterprise-focused high performance computing (HPC) systems aggregate or combine compute power so that the combined system can deliver much higher performance than a single large workstation. Common HPC tasks include conducting digital simulations, stress testing, and enabling extremely high speed, high frequency trading activities. By addressing these massive problems using parallel computing techniques, the time to complete a solution can be drastically reduced.

Increasingly, these workloads are focused on the use of analytics, machine learning (ML), deep learning (DL), computer vision (CV), and natural language processing (NLP)-the technology methods that power what is known as artificial intelligence (AI). Combined with high speed networking architecture and vast storage systems, enterprises can address a number of AI-based use cases via HPC clusters. As enterprises migrate from small, proof-of-concept programs to enterprise-wide rollouts, the need for a high performance compute and storage environment becomes clear. Omdia forecasts that global AI-focused enterprise software revenue will rise from $89.5m annually in 2020 to $626.6m in 2025.

This Omdia Market Report looks at the drivers, barriers, outlook, key players, and use cases for AI-focused HPC software in the enterprise. The report also addresses the impact of the global COVID-19 pandemic on the HPC market. Global AI-focused HPC software revenue forecasts, segmented by industry, geography, and use case, extend through 2025. Omdia identifies 30 AI use cases across 12 industries that will utilize HPC software resources between 2020 and 2025 and provides an in-depth analysis of the top 14 use cases in terms of cumulative revenue.
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Table of Contents
1. Executive summary
2. Market issues
3. Use Cases
4. Technology Issues
5. Key industry players
6. Market forecasts
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Key Market Forecasts
. AI-focused enterprise HPC software revenue by region, world markets: 2020-25
. AI-focused enterprise HPC software revenue by industry, world markets: 2020-25
. AI-focused enterprise HPC software market share by use case, world markets: 2025
. AI-focused enterprise HPC software revenue by industry, world markets: 2020-25
. Top 14 AI-focused enterprise HPC software use cases by revenue, world markets:  2020-25
. Enterprise HPC software revenue, traditional HPC use cases vs. AI use cases, world markets: 2020-25
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The intense competition for customers and business-combined with the impact of the COVID-19 pandemic-is helping to accelerate the timing of artificial intelligence (AI)-powered automation projects across customer-facing, backend, and fraud and security processes. Demand for self-service and always available access to new products and existing financial accounts has led to a growing utilization of AI and machine learning (ML) solutions. These solutions allow more robust engagement with customers, more efficient processes and operations, and a more streamlined approach to doing business.

The financial services industry has been an early adopter of analytics and big data for years. Banks, credit unions, investment firms, and fintech companies have been among the leaders in utilizing AI. But mindful of deployment costs, ROI, and regulatory concerns, AI is also being rolled out by enterprise financial services companies. The financial services industry is projected to incorporate AI technology over a number of use cases that are focused on process optimization, predictive analytics, customer interactions, anomaly detection, and customer experience. Omdia forecasts that AI software revenue for financial services use cases will grow from $2.0bn in 2020 to $9.1bn in 2025. 

This Omdia Focus Report looks at the following market issues surrounding AI applications within the financial services industry: drivers, barriers, revenue forecasts, key players, and use cases. Omdia identifies 24 use cases that will affect the industry between 2020 and 2025 and provides in-depth analysis of each use case, covering the applications, technologies, and metrics for success. The report and forecast also address the impact of the COVID-19 pandemic, which has spurred more demand for AI and automation, on the financial services market.
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Table of Contents
1. Executive summary
2. Market issues
3. Market ecosystem
4. Key industry players
4. Market forecasts
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Key Market Forecasts
. Total financial services AI software revenue by region, world markets: 2020-25
. Total financial services AI software revenue by use case, world markets: 2020-25
. Total financial services AI software revenue by subindustry, world markets: 2020-25
. Total financial services AI software revenue by subindustry, world markets: 2020-25
. Finance AI software revenue by use case, world markets: 2020-25
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The deployment of AI solutions is unlike traditional software, which is largely based around a volume-based sales model. In contrast, AI product capabilities may increase the output of employees, thus reducing the need for additional software license seats. Due to the collaborative and evolving nature of AI, several different business models have emerged. These range from a fully in-house, custom-built approach to a more modular approach using pre-built solutions and tools and a fully outsourced approach solely relying on third-party vendors.

The widespread availability of programming platforms and tools, as well as cloud-based infrastructure, has led to a major shift in the market. Enterprises do not need to lock into a single AI vendor; they can hire data science teams and engineers to develop, train, and run AI models from scratch. Yet, a significant portion of the enterprise market has neither the skill nor the budget to develop AI from scratch. As such, many vendors sell pre-built AI solutions or tools, and consultants and contractors can customize off-the-shelf AI. No single business model is going to be right for all enterprises looking to deploy AI. There will be room for many approaches and vendors-not only today, but for the foreseeable future. Omdia forecasts that annual AI software revenue will increase from $9.7bn worldwide in 2018 to $119.3bn in 2025.

This Omdia report provides a quantitative assessment of the market opportunity for the different business models used to develop and deploy AI applications. The study includes analyses of six business models in use globally and within five global regions and 28 industries. Discussion of strategies used by enterprises and vendors to consume, deliver, and pay for AI software is included. Omdia's analysis is based on insight gathered by speaking with AI enterprises and vendors active in the market.
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Table of Contents
1. Executive summary
2. Market issues
3. Market participants
4. Market forecasts
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Key Market Forecasts
. AI software revenue share by business model, world markets: 2025
. Annual AI software revenue by industry, world markets: 2018-2025
. AI software revenue share by industry, world markets: 2018
. AI software revenue share by industry, world markets: 2025
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(Please note: report documents have been updated)
The deployment of AI solutions is unlike traditional software, which is largely based around a volume-based sales model. In contrast, AI product capabilities may increase the output of employees, thus reducing the need for additional software license seats. Due to the collaborative and evolving nature of AI, several different business models have emerged. These range from a fully in-house, custom-built approach to a more modular approach using pre-built solutions and tools and a fully outsourced approach solely relying on third-party vendors.

The widespread availability of programming platforms and tools, as well as cloud-based infrastructure, has led to a major shift in the market. Enterprises do not need to lock into a single AI vendor; they can hire data science teams and engineers to develop, train, and run AI models from scratch. Yet, a significant portion of the enterprise market has neither the skill nor the budget to develop AI from scratch. As such, many vendors sell pre-built AI solutions or tools, and consultants and contractors can customize off-the-shelf AI. No single business model is going to be right for all enterprises looking to deploy AI. There will be room for many approaches and vendors-not only today, but for the foreseeable future. Omdia forecasts that annual AI software revenue will increase from $10.1bn worldwide in 2018 to $126.0bn in 2025.

This Omdia report provides a quantitative assessment of the market opportunity for the different business models used to develop and deploy AI applications. The study includes analyses of six business models in use globally and within five global regions and 28 industries. Discussion of strategies used by enterprises and vendors to consume, deliver, and pay for AI software is included. Omdia's analysis is based on insight gathered by speaking with AI enterprises and vendors active in the market.
Read More

Table of Contents
1. Executive summary
2. Market issues
3. Market participants
4. Market forecasts
View Full Table of Contents

Key Market Forecasts
. AI software revenue share by business model, world markets: 2025
. Annual AI software revenue by industry, world markets: 2018-2025
. AI software revenue share by industry, world markets: 2018
. AI software revenue share by industry, world markets: 2025
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This Omdia report provides a lens into recent and upcoming trends in the rapidly evolving RPA and intelligent automation space. RPA was already at a pivotal point, but COVID-19 has thrust automation to the forefront of enterprise IT discussions and investments as organizations try to do more with less and adapt to entirely virtual workforces and customer bases.

As more enterprises adopt RPA, vertical case studies and best practices are emerging, which have helped propel market and solution evolution. All signs point to continued acceleration of RPA adoption into 2021, particularly as enterprises value AI's positive impact on their businesses, driving demand for intelligent automation.
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Table of Contents
1. Omdia view
2. Recommendations
3. Signs point to continued acceleration
4. Enterprises value AI's positive impact on their businesses
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Figures and Tables
. RPA investment plans for 2020-21
. AI investment plans for 2020-21
. Value propositions of BPM and RPA
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Omdia's Enterprise AI Contracts Tracker provides a list of AI vendor-client contracts, announcements, and pilots. It offers a snapshot of enterprise AI industry activity and charts the progress of contracts across technologies, applications, regions, and industry verticals.

The tracker includes data on enterprise-grade AI contracts across various technology segments, including machine learning, deep learning, computer vision, natural language processing, and machine reasoning. It covers enterprise AI applications ranging from video surveillance and facial recognition to chatbots, customer analytics and support, process optimization, predictive maintenance, and quality monitoring, among others.

This edition is the third tracker in Omdia's Enterprise AI Contracts Tracker series. It is provided in an Excel spreadsheet that logs, classifies, and details publicly announced enterprise AI contracts, announcements, and pilots across a number of applications and industry verticals. Omdia has compiled information covering the period from October 2019 to June 2020. The data can be sorted by vendor/partner, client/partner, client industry vertical, geographic region, country, contract, and deployment type and date. Contracts can be further filtered by technology segment, application, meta category, delivery model, and service. This tracker also includes brief descriptions of the contract and product details, where possible. The Omdia Enterprise AI Contracts Tracker is published quarterly.
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Table of Contents
1. Notes
2. Enterprise AI Contracts Tracker
3. Tech & industry definitions
4. Use case definitions
5. Georgraphic listings
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Key Figures
. Number of enterprise AI deals by region, world markets: 4Q19-2Q20
. Number of enterprise AI deals by country, world markets: 4Q19-2Q20
. Number of enterprise AI deals by industry vertical, world markets: 4Q19-2Q20
. Number of enterprise AI deals by horizontal application, world markets: 4Q19-2Q20
. Number of enterprise AI deals by top 10 use cases, world markets: 4Q19-2Q20
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Global AI edge chipset revenue to reach $51.9bn by 2025, driven by the increasing need for AI inference at the edge

The need for artificial intelligence (AI) on edge devices has been realized and the race to design edge-optimized chipsets has begun. According to new research from Omdia, AI processing on the edge device circumvents privacy concerns while avoiding the bandwidth, latency, and cost concerns of cloud computing. Edge inference has emerged as a key workload in 2019-20, and many companies have introduced chipset solutions to accelerate AI workloads. Omdia has identified 10 device categories that will drive AI edge chipset demand including mobile phones, drones, HMDs, robots, smart speakers, PCs/Tablets, security cameras, automotive, edge servers and machine vision. Read More

Autonomous surface vehicles roaming our seas

Autonomous surface vehicles (ASVs) are unmanned vessels that float on the surface of water and operate without a crew onboard. They can autonomously carry out a mission and can be monitored and controlled remotely if necessary.This autonomous capability makes them very useful, less costly, safer, and more flexible than manned research vessels. The ability of ASVs to carry out a variety of tasks with little to no input from a pilot at sea, even under changing conditions, makes them immensely useful tools. They are much less resource-intensive and more flexible than the larger, fully manned research vessels. Read More

Demand for enterprise robots drives momentum in the robotic components market as automation and artificial intelligence propel revenue to $126.3 billion by 2025

The global robotics market is experiencing a strong growth trend in conjunction with the surge in automation, smart manufacturing, and e-commerce fulfillment especially in the enterprise and consumer segments. As a result, the market is experiencing significant demand for components ranging from robot arms to actuators, sensors, and controllers. Non-industrial robot use cases are rapidly expanding due to technological advances that enable easier robot setup and advanced artificial intelligence (AI), deep learning, and machine vision are allowing robots to take on more challenging tasks. Omdia expects the robotic components market to continue growing rapidly, reaching global revenue of $126.3bn by the end of 2025. Read More

Connecting the Dots: Key Strategic Opportunities in a Post-COVID-19 World

COVID-19 has already advanced the progress of several tech megatrends in an extremely short period of time. Understanding which technologies and services will underpin the post-pandemic digital economy will be critical to success. This report assesses the global post-COVID-19 landscape across telecoms and tech sectors and connects the dots across consumer, enterprise, industrial, device, component, and service provider markets. Read More

Artificial intelligence software is being deployed via a wide range of business models with annual revenue for hybrid solutions reaching $45.5 billion in 2025

Due to the collaborative and evolving nature of artificial intelligence (AI), several different business models are emerging, ranging from a fully in-house, custom-built approach to a more modular approach using pre-built solutions and tools. According to new research from Omdia, no single business model is going to be right for all enterprises looking to deploy AI and hybrid solutions will be most appealing as the market matures. Omdia forecasts that annual AI software revenue will increase from $10.1bn worldwide in 2018 to $126.0bn in 2025. Read More

Quantum computing is the utilization of the principles of quantum mechanics to perform calculations and solve problems. Using the unique phenomena of individual subatomic particles as compute elements, quantum computers have the potential to quickly solve problems that are impossible to calculate in timeframes that are useful to humans and eventually solve problems that classical computers cannot.

Omdia's research indicates that an increasing number of enterprises are experimenting with quantum computers. However, most of the revenue being generated is not through traditional hardware sales, but via services, such as general consulting services that are provided by vendors, professional services firms, and third-party industry consultants or via cloud-based access to quantum computers. Omdia projects that total quantum computing market revenue, including hardware, software, storage, and services, will reach $3.6bn annually by 2030. Services is expected to account for $2.5bn in annual revenue in 2030, followed by software, storage, and hardware.

This Omdia report examines the market trends and technology issues surrounding quantum computers used by enterprise organizations. It highlights quantum computing use cases within industry groups that are projected to increasingly experiment with and use quantum processing (healthcare, life sciences, finance, investment, and IT). Global market forecasts for quantum-related hardware, software, storage, and services revenue, segmented by region, product type, industry, and use case, extend through 2030.
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Table of Contents
1. Summary
2. Recommendations
3. Market trends
4. Technology overview
5. Market dynamics
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Key Market Forecasts
. Total enterprise quantum computing revenue by region, world markets: 2019-30
. Total enterprise quantum computing revenue by product type, world markets: 2019-30
. Total enterprise quantum computing revenue by industry, world markets: 2019-30
. Enterprise quantum computing software revenue by industry, world markets: 2019-30
. Enterprise quantum computing services revenue by industry, world markets: 2019-30
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Global AI software market set to rise sixfold to reach nearly $100 billion in 2025

The worldwide market for artificial intelligence software will expand to $98.8 billion by 2025, rising by a factor of six from $16.4 billion in 2019-despite the varying effects of the COVID-19 pandemic across different industries, according to Omdia. The artificial intelligence (AI) software market has experienced tremendous growth over the past several years. While the COVID-19 pandemic has dampened growth forecasts for the market, its impact is uneven across industry sectors. While some industries are retrenching-such as energy, oil, gas, & mining-a few markets, like healthcare, are accelerating AI adoption. Omdia has developed four market scenarios based on the duration of the pandemic and the severity of its economic effect. Read More

Qualcomm releases end-to-end 5G robotics platform with AI

Robotics development just got easier and more integrated. On June 17, 2020, Qualcomm announced the release of its RB5 robotics platform with artificial intelligence (AI) and 5G enabled. The comprehensive platform is designed to make it easier for developers and manufacturers to design and build AI-enabled robotics products targeted toward 5G connectivity. Qualcomm's RB5 platform includes a low power, high compute modular development kit designed for robots and drones-from toys to high end professional models. The kit allows developers to choose which components they want to include for their application. Qualcomm is working with more than 30 ecosystem players that are developing hardware and software to enable a number of robotics applications with RB5. Read More

The increased need for advanced robotic technologies will accelerate the global exoskeleton market, with revenues reaching $2.6 billion by 2025

Exoskeleton technology is being utilized in multiple sectors to improve productivity and employee health and in response to an aging population of workers. Industrial and enterprise use cases are increasing and numerous startups are selling and developing exoskeletons for rehabilitation and other healthcare uses. According to new research from Omdia, the outlook for exoskeletons is for strong sustained growth through 2025. The combination of new products, technology innovation, and ongoing governmental approvals will stimulate exoskeleton adoption. The healthcare sector presents the greatest opportunity for growth in the near term, while the military sector will likely be a lucrative market when militaries complete their exoskeleton pilot tests and begin to purchase numerous units for ground troops. Read More

COVID-19 impact on enterprise AI software market

Forecasting AI is never an easy task, even in the calmest economic times. Then came the COVID-19 pandemic, which upended everything. The effects on the global AI software market in 2020 and beyond are still difficult to measure but will correspond with the severity and duration of the pandemic and its economic effects. These impacts, however, vary widely by industry sector and use case, unexpectedly accelerating AI adoption in some fields. Read More

DeepMind Control Suite trains a (simulated) robot dog to run and fetch with reinforcement learning

Reinforcement learning enables autonomous robots to learn large sets of behavioral skills with minimal human intervention. In real physical systems, however, there is a tendency to engineer policies by hand to achieve faster training times. Deep reinforcement learning (RL) reduces the need for this manual input by including general-purpose neural network policies for a particular application. DeepMind's dm_control development package demonstrates the training of deep Q-functions that can scale to complex 3D manipulation tasks and can learn deep neural network policies efficiently enough to train real-world robots. Read More

Omdia's Enterprise AI Contracts Tracker provides a list of AI vendor-client contracts, announcements, and pilots. It offers a snapshot of enterprise AI industry activity and charts the progress of contracts across technologies, applications, regions, and industry verticals.

The tracker includes data on enterprise-grade AI contracts across various technology segments, including machine learning, deep learning, computer vision, natural language processing, and machine reasoning. It covers enterprise AI applications ranging from video surveillance and facial recognition to chatbots, customer analytics and support, process optimization, and predictive maintenance and quality monitoring, among others.

This edition is the second tracker in Omdia's Enterprise AI Contracts Tracker series. It is provided in an Excel spreadsheet that logs, classifies, and details approximately 100 publicly announced enterprise AI contracts, announcements, and pilots across a number of applications and industry verticals. Omdia has compiled information covering the period from January to March 2020. The data can be sorted by vendor/partner, client/partner, client industry vertical, geographic region, country, contract, and deployment type and date. Contracts can be further filtered by technology segment, application, platform type, meta category, delivery model, cloud type, and service. The tracker also includes brief descriptions of the contract and product details, where possible. The Omdia Enterprise AI Contracts Tracker is published quarterly.
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Table of Contents
1. Notes
2. Enterprise AI Contracts Tracker
3. Summary
4. Definitions
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Key Figures
. Number of enterprise AI deals by region, world markets: 1Q20
. Number of enterprise AI deals by country, world markets: 1Q20
. Number of enterprise AI deals by industry vertical, world markets: 1Q20
. Number of enterprise AI technologies across deals, world markets: 1Q20
. Number of enterprise AI deals by top 10 use cases, world markets 1Q20
. Number of enterprise AI deals by meta category, world markets: 1Q20
. Number of enterprise AI deals by deployment type, world markets: 1Q20
. Number of enterprise AI deals by announcement type, world markets: 1Q20
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AI chipsets appeared on the horizon in 2016 after the industry began to grasp the vast computing needs of neural network (NN) processing. Early artificial intelligence (AI) chipsets, led by general-purpose graphics processing units, focused on the enterprise market and training workloads. They provided high compute capacity and the ability to run state-of-the-art networks at the time. However, the need for AI on edge devices was realized soon after and the race to design edge-optimized chipsets began. Edge inference has emerged as a key workload in 2019-20, and many companies have introduced their chipsets.

Several different factors are driving AI processing to the edge device. Privacy, security, cost, latency, and bandwidth are all being considered when evaluating data center versus edge processing needs. Applications like autonomous driving and navigation have sub-millisecond latency requirements that make edge processing mandatory. Other applications such as speech recognition on smart speakers generate privacy concerns. Keeping AI processing on the edge device circumvents privacy concerns while avoiding the bandwidth, latency, and cost concerns of cloud computing. Omdia forecasts that global AI edge chipset revenue will grow from $7.7bn in 2019 to $51.9bn by 2025.

This Omdia report provides a quantitative and qualitative assessment of the opportunity for AI edge processing across several consumer and enterprise device markets. The device categories include automotive, consumer and enterprise robots, drones, head-mounted displays (HMDs), mobile phones, PCs/tablets, security cameras, smart speakers, machine vision, and edge servers. Global revenue and shipment forecasts, segmented by chipset architecture, power consumption, compute capacity, training versus inference, and application attach rate for each device category, extend through 2025.
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Table of Contents
1. Executive summary
2. Market issues
3. Technology issues
4. Key industry players
5. Market forecasts
View Full Table of Contents

Key Market Forecasts
. AI edge chipset revenue, world markets: 2019-25
. AI edge device attach rates, world markets: 2019-25
. AI edge chipset revenue by device category, world markets: 2019-25
. AI edge chipset shipments by device category, world markets: 2019-25
. AI edge chipset revenue by chipset type, world markets: 2019-25
. AI edge chipset revenue by power consumption, world markets: 2019-25
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