There’s no turning back for AI now. With the launch of ChatGPT, which is creating everything from song lyrics to business proposals, and Lensa, the AI art tool everyone’s using to transform their images into ‘Magic Avatars’ on Instagram, AI has well and truly hit the mainstream.
AI has of course been commonplace in the marketing industry for a while, with many solutions already powered by sophisticated AI algorithms but this is not the case across the board. Having recently been propelled into the limelight however, everyone suddenly wants a piece of the pie.
Consequently, we’re starting to see the gap between technology utilising Deep Learning AI and tech using less advanced Machine Learning growing, as the capabilities just don’t match up. It seems safe to say that soon, the absence of advanced technology in martech offerings will mean they’re not taken seriously by potential clients or partners in the field.
So what will this mean for the industry, are we likely to see a cohort of industry players go bust or will 2023 be a year of widespread AI adoption across the sector?
Why AI and why now?
You’d be forgiven for thinking AI is a new technology, but in fact its origins date way back to 1950 with The Turing Test, which was considered the first serious proposal in the philosophy of artificial intelligence. Over the years, as digital technology has become more sophisticated, so too has AI. Its uptake, however, has been sluggish; fears it might displace workers and the cost and intricacies of integrating this technology have overshadowed the hype, until now. In fact, the sheer speed and accuracy it can bring to marketing is becoming clearer. While the analysis of data previously had to be done manually, this technology can analyse massive amounts of data in microseconds, bringing a new lease of life to marketing and ensuring brands can target consumers better than ever before.
There’s no future that AI won’t be a major part of and every player in the ecosystem should jump on board now or risk being stranded. With the cost-of-living crisis driving lower media demand across many platforms, now is the perfect time for brands to embrace AI and find what delivers the best results. It can also provide a way of reaching new consumers and driving sales at a time when many are struggling to hit KPIs.
Deep Learning over Machine Learning
While Machine Learning has the ability to learn and adapt from experience without explicit programming, it only works across limited data sets and requires human intervention. Deep Learning on the other hand attempts to model the same neural networks you see in the human brain. It’s more complex to design, but enables the generation of much more sophisticated insights from any dataset, including unstructured. Plus it can learn independently and improve over time without the need for any human programming. Marketing solutions powered by Deep Learning can process data through varying layers of complexity, and derive meaningful insights far faster than traditional Machine Learning solutions can. Given the amount of data marketers have to deal with, often from numerous siloed sources, understanding and interpreting this in the quickest way possible is imperative to hit key metrics and maximise return on ad spend (ROAS).
We’re, therefore, likely to see a slow decline in the use of Machine Learning platforms that don’t have the budget or capacity to upgrade their tech. As Deep Learning within the industry becomes more and more prevalent, brands of all shapes and sizes will be intent on utilising it.
How the cookieless future is driving AI adoption
The other issue that has been a driving force in the recent investment and adoption of Deep Learning AI, is increasing consumer privacy legislations and in particular Google’s upcoming deprecation of cookies. The death of the cookie means many marketers will lose access to structured datasets, which in turn will render many existing Machine Learning solutions even less competent.
To reach the right consumer at the right time, brands need to know where they are. It’s often assumed that without cookies tracking users on the web this won’t be possible, but this is where Deep Learning’s prowess really comes into play. Because Deep Learning mimics the human brain, it’s able to understand user intent and learn from it. Its abilities extend to identifying audiences who may not be searching for a particular brand, but who would be interested in its products or services all while remaining completely privacy compliant.
There’s no doubt 2023 is the year that AI and in particular Deep Learning, will take the marketing industry by storm. Propelled by the need for speed, efficiency and consumer-privacy, this technology will become a requirement among marketers before long. While this may lead to the demise of solutions powered by Machine Learning – particularly among bigger brands – the adoption of Deep Learning and continued investment in this technology, will ultimately lead to more sophisticated and advanced marketing on an unprecedented level compared to what we’ve seen before. Marketers be clear; this year it’s AI or bust, so get your advanced tech in order or prepare to be left behind.