As Chief Technology Officer and Head of Data Science, Ian Liddicoat leads the optimization of Adludio’s world-beating marketing analytics.

Though artificial intelligence (AI) has been a background part of many people’s lives for several years, 2023 has seen the technology thrust into the mainstream, waking the world up to its power to change the world.

An area where it has already had a significant impact is the digital advertising industry, where the technology has been playing a role within a plethora of processes for a long time—from programmatic media buying to SEO generation and optimization. Now, AI is perfectly placed to change every other aspect of the industry, making an impact across everything from production right through to insights and reporting.

This is especially the case in the realm of ad creativity, as was seen recently at the Cannes Lions International Festival of Creativity, where it was difficult for advertisers to escape the technology’s long shadow.

 
Tying Everything Together

The rise of AI is the latest technological development in the constantly evolving world of digital advertising and is unlikely to be the last we will see in the coming years. Like mobile and social media before it, AI has completely changed how digital advertising is approached. However, more than these technologies before it, AI will push capabilities to a point that would previously have been the stuff of dreams.

Its development has been especially opportune as the industry says goodbye to third-party cookies next year, with AI enabling marketers to continue to deliver relevant, targeted advertising and gain insights into campaign effectiveness.

Nevertheless, with or without cookies, the driving force behind effective ads has always been creativity. However, there has always been difficulty in establishing how creative components interact with media and data. As a result, insight into what makes a successful campaign design has been elusive. AI aims to solve this problem by helping marketers understand how different campaign components are interoperable, and how this creative intelligence can be subsequently used to drive the best possible outcomes.

More Than A One-Trick Pony
Deep learning, computer vision, neural networks, large language models and re-enforcement learning are just some of the subsets of AI that will drive creativity in digital advertising forward and ensure that marketers can gather real insights and drive consumer attention, rather than relying on often-incorrect assumptions about outcomes.

For instance, computer vision and generative AI can be used in conjunction to understand how individual creative components drive attention and engagement. As these technologies develop, they’ll enable digital marketers to create custom content in real time that is deterministically designed to maximize the attention of any audiences being targeted. Meanwhile, the combination of deep learning and neural networks can be used to link that engagement to the brand-specific outcomes that really matter.

This ability to track a clearly defined attention metric opens the door for marketers to inform their ad creatives using accurate data and optimize for the best possible performance. The unique insights can also then help future campaigns by providing a historic reference of the elements that drove that level of performance. This means campaigns can be continuously improved over time, thanks to AI.

Adapting For The Future
As its integration into creative processes becomes more widespread, it’s widely accepted that many jobs will be affected by AI. However, the technology can only be as effective as the data and the people behind it. It wouldn’t be a wise move for a business to be pushing out AI-generated content without oversight from a human and the nuances they can provide.

This is particularly the case when one considers the continuing importance of brand safety and suitability and the relationship between machine-learned content and the publisher's inventory. We will steadily see AI being used to increase the relevance of digital advertising relative to its placement and the audience interests it attracts.

For brands, there are important decisions to be made about the integration of AI into their digital advertising and wider business. This will require a clear strategy and direction from the board and appointing a CTO with data science and data engineering expertise as well as conventional software development experience.

Brands must then make a clear distinction between the AI-driven applications that are needed in-house versus those that could be delivered through third-party vendors. The appropriate level of investment in data science resources will be a critical decision as many have not addressed this thus far. Many CEOs will need to consider how they best understand the benefits and the risks attached to the wholesale adoption of AI at a strategic level. This will then need to feed directly into their technology strategy for the short and long term.

While all this won’t mean the end of human input (existing teams may likely become more efficient), the outcomes delivered by AI will nevertheless change everything about digital advertising. Notably, the biggest, and most valuable change for digital advertisers will be in the arena of creativity and optimizing it to achieve the best possible business outcomes.