It is estimated that the amount of data we have generated will grow from about 33 zettabytes (ZB) at the end of 2018 to 175ZB by 2025.
To put this into perspective - one ZB is equal to one trillion gigabytes. If we tried to store 175ZB on DVDs, we could stack them to the moon 23 times or circle the earth 222 times.
Both cloud computing and artificial intelligence (AI) play a central role in how we store and extract meaning from this data to enhance our daily lives.
Netflix as a case study
The fact that many people have experienced Netflix makes it a great case study in its use of both cloud computing and AI.
In August 2008, the company began a migration to the cloud. As of 30 June 2019, Netflix served more than 150 million paid subscribers that were located in more than 190 different countries.
Netflix is aware that people will not sit and scroll for hours to figure out what they would like to watch - they need to see something enticing quickly in order to continue to pay for the service. Amazon Prime, for example, is usually only a single click away.
For Netflix to have continued maintaining its own physical datacentre capable of supporting more than 150 million customers in 190 countries would have been a staggering task.
Shifting to Amazon Web Services allowed Netflix to take advantage of world class cloud infrastructure distributed across the world, taking away the need to rack physical servers or worry about fixing bugs or network infrastructure.
Amazon Web Services represents one of the leading cloud infrastructure platforms, often referred to as 'infrastructure-as-a-service' or IaaS.
While Netflix would be a very large customer, the platform can support customers of any size, offering them on-demand computing power and data storage. Instead of maintaining hardware physically, businesses can simply pay for exactly what they need from Amazon's platform.
AI is what allows Netflix to offer unique recommendations to every customer, based on their own preferences. Amazon Web Services allows for the on-demand computational power necessary to take all past customer decisions into account to form better and better recommendations.
It was not very long ago that businesses of almost any size would be maintaining their own servers on premises (On prem + Mainframe, which would then require a team of information technology (IT) professionals to handle updates and troubleshooting).
This was very expensive for the business. The recent growth has clearly been in the software-as-a-service (SaaS) space.
By adopting the cloud, customers can have the most updated software instantly and providers have a much more predictable revenue stream from their monthly subscriptions.
It is difficult to think of new software in 2019 that does not take advantage of the cloud distribution model.
AI is still in the early stages
AI, in most incarnations, is software that can harness massive processing power to find patterns and ultimately make very accurate predictions after being trained over millions or even billions of iterations.
Cloud services, such as Microsoft Azure, Google Cloud or Amazon Web Services offer instant scale to store and process this data.
We have begun to see very interesting developments in the automation of repetitive tasks at work or the integration of processes like insurance claims, where software might recognise speech, process images of damage and even award claims.
While we can guess at the possible benefits that we may see in a world dominated by the internet of things (IoT), which may include more than 75 billion connected devices by 2055, we do not yet exactly know every area that AI will impact in the future.
The initial conclusion could be that the ubiquitous adoption of cloud computing, which now dominates how software is distributed and consumed today, could be paving the way for the future ubiquitous presence of AI, and a world where companies know what customers will buy before they buy it.
Christopher Gannatti is head of research, Europe at WisdomTree