The AI Revolution in Marketing

From self-driving cars and smart applications to voice technologies and intelligent diagnostics, artificial Intelligence (AI) is now an ever-present force in our modern world, powering innovations in industries such as healthcare, manufacturing, finance, and retail that make our lives tremendously easier. 

Yet just five years ago, it was a completely different story; few businesses were on board with the idea of integrating AI into their core processes. The perceived complexity, cost, and lack of familiarity initially deterred them from incorporating this new technology. This all changed in 2019 when AI adoption shot up to 58%, from an underwhelming 20% in 2017.

Global AI Adoption

Why the sudden change in global adoption? Well, over the course of a few years, AI has become more accessible, affordable, and user-friendly, prompting businesses to dip their toes into the water. It was also around this time that people finally started to gain a deeper understanding of AI and its remarkable benefits. 

And this had a lot to do with the growing availability of data from a plethora of digital platforms that have emerged in recent years. Businesses started using this wealth of data to unlock valuable insights to discover the potential of AI and further leverage it. As a result, various industries began to incorporate AI into their core processes.  

Fortunately, the marketing industry wasn't the last to try its hand at AI. In fact, it quickly tapped into AI’s potential. Amazon was the first to test out AI in 1998, drawing from a renowned study on clustering conducted by computational linguist Jussi Karlgren.

Amazon and Predictive AI

Using this concept, the e-commerce giant developed “collaborative filtering,” a function that serves up product recommendations based on collected data from its users (the same way Netflix suggests programs today, which we’ll touch on shortly). Back then, this function was an enormous breakthrough in marketing.

Amazon's early AI implementation playeda pivotal role in developing what it now calls "predictive delivery," a system that effectively manages inventory and anticipates customer demand (a groundbreaking innovation that has since been adopted by numerous businesses throughout the industry).

Machine Learning in Google Search

In the same year, Google started exploring AI techniques like natural language processing and machine learning to improve the accuracy of its search results. Using AI, the search engine was able to analyze huge volumes of data on the internet, including historical search patterns, to deliver relevant suggestions to users. And we all know Google has made serious enhancements to its AI over the years to improve the overall search experience.

Netflix AI for Behavioral Insights

In 2006, Netflix started utilizing AI to build a recommendation system to deliver personalized recommendations to its subscribers. Through AI, the streaming platform gathered behavioral data to enable personalized thumbnails and customized content recommendations tailored to each profile's unique preferences.

Facebook AI in Targeted Advertising

Not long after that, Facebook, which was still gaining popularity, took an early leap into AI to improve content recommendations and targeted advertising within its platform. Through AI algorithms, it delivered targeted content based on collected user data and could even identify people in photos with the help of AI. Facebook then started to use AI to moderate its content. 

AI Generated Content for Adobe

In 2016, Adobe achieved a groundbreaking development in the field of AI with the launch of Adobe Sensei, an AI integration within its ecosystem. Adobe Sensei is what enables users to streamline workflows and automate content creation processes within Adobe, which was a significant game-changer in the field of marketing.

With industry giants integrating AI into their processes, many other brands have followed suit, from Spotify using AI algorithms to create personalized playlists to TikTok leveraging AI for tailored content recommendations. Indeed, the widespread pursuit and interest in AI is further fueling its growth, and we’re eager to see how it continues to evolve.