The IoT Market and its Future with AI

Making home life easier, cities smarter, or industrial facilities more energy-efficient is in large part due to the Internet of Things (IoT). IoT is an ecosystem of devices that are connected through the internet and are typically designed with sensors that collect data. The IoT market surpassed $1 trillion last year1, with no signs of slowing down.

The IoT market1, which encompasses the hardware, platforms, connectivity, and services involved in making the “things” smart, but does not include the market price of the “things” themselves, is projected to close 2024 around $1.39 trillion and surpass $2 trillion in 20271.

The automotive IoT1 segment is currently leading the industry, a hold it is expected to maintain for many years. Industrial IoT also holds a significant share of the market and includes devices that automate and optimize factories, agriculture, supply chains, and the like1. The IoT market has an anticipated 17% CAGR2 by 2030.

Several key factors across the tech space are influencing the rapid growth of IoT. Supply chain issues during the COVID-19 pandemic sparked stronger efforts to expand the chip supply chain3 by investing in semiconductor manufacturing around the world. The proliferation of 4G and 5G networks3 will also accelerate the IoT industry as they bring faster and more reliable processing speeds to more locations. Vast improvements in enabling technologies3 like data processing capacity, power, storage, and speed will also support continued IoT growth while reducing costs.

Recently, the rise of AI has proven to be a huge tailwind2 for the IoT market, not a disruptor or substitute. AI feeds on data, so the integration of data-gathering IoT devices and AI is a natural fit and a boon for both industries. Many are looking at the healthcare sector for some of the most intriguing and impactful examples of the merging of IoT and AI, specifically through AI-enabled wearables.

As IoT grows (alongside AI), so too will the enabling technologies that make it possible. These IoT technologies4 include sensors and actuators, connectivity technologies, big data analytics, cybersecurity, and cloud computing (all data collected by IoT devices are stored, processed, and analyzed in the cloud).

One of the biggest challenges facing the IoT market is privacy and security5 because many IoT devices are constantly gathering very personal data, from an individual’s location while driving6 to live video footage of a person’s home. This challenge can also be seen as an opportunity for cybersecurity companies to provide backend services for a growing IoT market.

TrueMark offers an ETF with broad exposure to the IoT market. The TrueShares Technology, AI & Deep Learning ETF (LRNZ) holds 20-30 positions representing companies that are significantly involved in AI integration. Some, like Samsara focus directly on AI. Others, like Nvidia, lead in enabling technologies like chips while others specialize in cloud computing, data processing, or cybersecurity. This concentrated portfolio is also diversified across sectors, with several healthcare and biotech companies that emphasize AI and IoT. All told, LRNZ can be a strong entry point for investors interested in capturing IoT growth via the many factors that are driving and being driven by its success.


The TrueShares AI & Deep Learning ETF (AI ETF) is also subject to the following risks: Artificial Intelligence, Machine Learning and Deep Learning Investment Risk – the extent of such technologies’ versatility has not yet been fully explored. There is no guarantee that these products or services will be successful and the securities of such companies, especially smaller, start-up companies, are typically more volatile than those of companies that do not rely heavily on technology. Foreign Securities Risk -The Fund invests in foreign securities which involves certain risks such as currency volatility, political and social instability and reduced market liquidity. Growth Investing Risk – The risk of investing in growth stocks that may be more volatile than other stocks because they are more sensitive to investor perceptions of the issuing company’s growth potential. IPO Risk – The Fund may invest in companies that have recently completed an initial public offering that are unseasoned equities lacking a trading history, a track record of reporting to investors, and widely available research coverage. IPOs are thus often subject to extreme price volatility and speculative trading. New Issuer Risk – Investments in shares of new issuers involve greater risks than investments in shares of companies that have traded publicly on an exchange for extended periods of time. Non-Diversification Risk – The Fund is non-diversified which means it may be invested in a limited number of issuers and susceptible to any economic, political and regulatory events than a more diversified fund.