AI in IoT Market - Growth, Trends, COVID-19 Impact, and Forecasts (2023 - 2028)

AI in IoT Market - Growth, Trends, COVID-19 Impact, and Forecasts (2023 - 2028)

The global Artificial Intelligence (AI) in the IoT market is expected to grow at a CAGR of 27.86% during the forecast period. The need to efficiently process vast volumes of real-time data generated from IoT devices, the growing demand for performance management appliances, and the need to reduce downtime and maintenance costs are the primary factors driving the market's growth.

• IoT technology is essential for various organizations to digitally transform, thus, empowering them to upgrade the existing processes by creating and tracking new business models. More and more companies view IoT as an important element for business success, thus increasing its adoption. AI and IoT, both technologies, when combined, are creating intelligent machines that simulate rational behavior and support decision-making with little or no human interference. The growing emphasis on effective management of data generated from IoT devices to gain valuable insights and real-time monitoring to curate an enhanced customer experience are the key growth drivers for the market.
• The retail industry is leveraging cloud AI in IoT-based services to augment customer experience programs and generate more customer-oriented products. For instance, in a smart retail environment, a camera system outfitted with computer vision capabilities can use facial recognition to recognize customers when they walk through the door. Suppose the system detects most customers walking into the store are Millennials. In that case, it can push out product advertisements or in-store specials that appeal to that demographic, therefore driving sales.​
• Furthermore, most companies are shifting to the cloud from on-premise AI, owing to faster delivery time with low latency and real-time tracking, likely to foster the studied market growth during the forecast period​. For instance, Amazon Echo Amazon has introduced Web Services IoT, a managed cloud platform and lets devices connect securely to cloud applications and other devices. In February 2021, IBM and Red Hat announced a new collaboration to use a hybrid cloud designed to deliver an open, flexible, and more secure solution for manufacturers and plant operators that will drive real-time value from operations data from industrial IoT.
• However, the lack of a skilled workforce and growing concerns regarding data security are some major factors restraining the studied market growth. It is crucial to ensure that the data is secure and in safe hands because AI and IOT collect sensitive and essential data from their users or clients. But since users have no idea when someone would attempt to access our private and sensitive data, security is always a concern with technology and restricting the market growth.
• During the spread of Coronavirus, the ability for organizations to access scalable, dependable, and highly secure computing power, whether for vital healthcare work, to help students continue learning, or to keep unprecedented numbers of employees online and productive from home are some of the critical factors owing to the growth of the market in this situation. Hospital networks, pharmaceutical companies, and research labs are using AI-enabled IoT devices to care for patients, explore treatments, and mitigate the impacts of COVID-19 in many other ways. All of the above factors have accelerated the market's growth rate in the short run and are expected to augment it further in the long term.

• Manufacturers are increasingly taking steps to achieve 100% automated data management systems. AI-enabled IoT applications for manufacturing can also efficiently deal with operations such as monitoring and optimizing equipment performance, production quality control, and human-to-machine interaction. Faster and more efficient manufacturing and supply chain operations significantly reduce product cycle time.
• In May 2021, Bosch launched a new AIoT platform that provides real-time data on energy consumption at manufacturing sites. The Phantom Edge platform delivers manufacturing efficiency, real-time alerts, and notifications for timely, actionable insights. It also automates data capture and measures accurate downtimes by providing timely, bias-free, and precise data that form the basis for managers to set targets, track performance, analyze, and improve continuously.
• Moreover, With the high rate of adoption of sensors and connected devices and the enabling of M2M communication, there has been a massive increase in the data points generated in the manufacturing industry. These data points could be of various kinds, ranging from a metric describing the time taken for a material to pass through one process cycle to a more advanced one, such as calculating the material stress capability in the automotive industry.​
• Various vendors in the market are also offering professional services specific to the manufacturing industry. IBM offers its IoT professional services under Watson, including consulting, and boasts prominent clients in the manufacturing space. For example, Mahindra & Mahindra Ltd, an automobile manufacturer in India, has adopted connected engineering solutions from IBM. ​
• Further, an India-based start-up, Lincode Labs, utilizes AI and Industrial IoT solutions to increase the profitability of manufacturers. The company helps manufacturers automate visual inspection and improve overall equipment effectiveness (OEE) by identifying product defects using computer vision and artificial intelligence with the help of deep learning. Combined, these factors are expected to drive the market's growth during the forecast period.

• The growth in the North American AI in the IoT market is associated with an increase in the number of early adopters of the technology. Modern manufacturing facilities in the United States rely on new technologies and innovations to produce higher quality products at a significant rate with lower costs. The emerging technologies that are expected to emerge out of the existing technologies, transforming manufacturing in the United States, are expected to include the convergence of AI and IoT, with companies, like SAS Software touting IoT as the next wave for IoT based on AI.
• Additionally, awareness about IoT solutions in industries is significantly higher in the region compared to others. According to a study by Mendix in March 2021, 78% of the US manufacturing workers welcome digitalization, and eight in ten manufacturing workers are interested in learning new digital skills.
• Other factors influencing the market's growth are the presence of several significant players in the region. The higher cloud adoption rate among end-users drives investment in the studied market. The market players in the area are observing strategic partnerships and collaborations among various significant players, making a profitable path toward market expansion.
• The adoption of intelligent robots across several end-user industries is driving the growth of the market studied. North America is among the advanced innovators and pioneers in adopting robotics and is one of the largest markets. The fundamental reason for the market's growth is the increasing adoption of robots across numerous industries. The region also homes several robotics manufacturers and companies that provide AI for robot manufacturers.
• Furthermore, the region is also witnessing increasing investment in the market, which is expected to be one of the key driving factors for market growth during the forecast period. For instance, in February 2021, Advantech, an industrial IoT solutions provider, partnered with Momenta Ventures to launch the AI and IoT Ecosystem Fund, with a target of USD 50 million capital focused on AI and IoT innovators in North America.

The AI in IoT Market is highly competitive owing to the presence of a large number of players in the market operating in domestic and international markets. The market appears to be fragmented. Due to the increase in the applications of AI in the IoT market, major players are adopting strategies like product innovation, partnerships, mergers, and acquisitions. Some of the key developments are:

• May 2021 - Google Cloud announced the general availability of Vertex AI, a managed machine learning (ML) platform that allows companies to accelerate the deployment and maintenance of artificial intelligence (AI) models and IoT. Vertex AI requires nearly 80% fewer lines of code to train a model versus competitive platforms. It enables data scientists and ML engineers across all levels of expertise to implement Machine Learning Operations (MLOps) to efficiently build and manage ML and IoT projects throughout the entire development lifecycle.
• March 2021 - IOTech, the edge software company, announced the launch of Edge XRT, its time-critical edge platform for Microsoft Azure Sphere. Designed and optimized for resource-constrained environments, Edge XRT delivers device connectivity and edge intelligence for microcontroller units (MCUs), gateways, and smart sensors at the IoT edge.
• February 2021 - Oracle has launched a range of solutions for the construction industry, using artificial intelligence (AI) to analyze project data. This suite of applications is designed to help users detect risks and make more informed project decisions.

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