How Cloud Migration is Creating a Tech Inflection Point

The buzzwords that have graced headlines in the tech world over the past year — Artificial Intelligence, generative AI, machine learning — are all made possible by another mega-trend happening almost behind the scenes. Though more than a decade in the making, cloud migration is creating a technology inflection point1

Cloud migration refers to the transfer of applications, data, security, and infrastructure from on-site (or on-premise) servers to a cloud computing environment. Its proliferation stands to accelerate growth and other technological advancements for everything from chatbots to Internet of Things (IoT). 

Before the cloud2, companies relied on on-premise data storage and computing mainframes, but only the largest companies with excess capital could afford such infrastructure. By the 1960s2, computing systems were leased out to hundreds of companies who couldn’t afford their own in-house systems. Eventually, however, computing infrastructure became affordable enough for more companies to invest in their own.

Salesforce is said to have created the first Software as a Service (SaaS)3 cloud application with its customer relationship management (CRM) system in 1999. The government and finance industries were the first adopters of cloud computing, which took the form of a shared resource model for file storage, CRM systems, and accounting. In the first decade of the 21st century, large companies like Amazon, Google, Microsoft, and even NASA, deployed their own cloud computing systems2. Then in 2020, the COVID-19 pandemic urged many companies to accelerate their migration to the cloud to accommodate remote and hybrid work requirements4. Since the pandemic, customers and employees have maintained their expectations of high performance digital experiences.

As of Q2 20235, Amazon, Microsoft, and Google control two-thirds of the cloud computing market, with eight of the largest providers controlling 80%. Cloud computing infrastructure services brought in a cumulative total of $65 billion in Q2 2023, a $10 billion increase over Q2 2022. The cloud computing market is an estimated $247 billion opportunity5. It may be surprising, therefore, to know that a large majority6 of companies are still using on-premise servers. 

The cloud migration mega-trend has impacted companies of all scales, allowing a diversity of sectors and industries to migrate their data to the cloud. Companies young and old are often motivated4 to migrate to the cloud because it offers greater flexibility, speed, risk reduction, affordability, and performance.

So while AI and chatbots are the tech buzzwords of the moment, having advanced rapidly over the last year, they may not have gotten to this point if they had been limited by the up-front costs, rigidity, lag time, and risk of on-premise infrastructure. We think it’s safe to say that we are still in the early stages of cloud migration, with the most significant changes to the tech industry yet to fully materialize. 

The cloud computing inflection point is working in tandem with advancements in other technologies, from chips and semiconductors to security and algorithms. These behind-the-scenes support technologies form the basis of our Technology, AI, and Deep Learning ETF (LRNZ), which is designed to provide thematic exposure to a concentrated portfolio of innovative technology companies with solutions for tomorrow’s AI needs.

The tech landscape is constantly changing, so knowing how and where to invest is crucial. Learn about more inflection points and get your AI questions answered with our Investor’s Guide to Artificial Intelligence.


Chatbots: a computer program designed to simulate conversation with human users, especially over the internet.
Internet of Things (IoT): the interconnection via the internet of computing devices embedded in everyday objects, enabling them to send and receive data.
Software as a Service (SaaS): a method of software delivery and licensing in which software is accessed online via a subscription, rather than bought and installed on individual computers.

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.

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