Although the value of traditional media metrics, such as first-click, last-click and viewability, is rapidly dwindling in the face of the imminent deprecation of third-party cookies, forward-thinking digital advertisers have been exploring alternative ways of assessing their campaign effectiveness for quite some time. In particular, by measuring user engagement with creative-focused ads.

While engagement and measures of attention are undoubtedly the right path to go down, there is a broader opportunity here. To optimise engagement with a deeper understanding of the contribution that creativity, specifically which permutations of creative objects, have made to engagement and, ultimately, a hard metric such as completed sale.

AI, in its many forms, is perfectly suited to the development of advanced “creative intelligence” and will have significant implications for traditional dynamic creative techniques and digital ad production. Taking this further, it would be reasonable to assume digital ads will soon be assembled in real-time from very large repositories of creative objects and insights.

This includes items such as the role of the logo, text, product shot, use of colour, sound and call to action, and specifically how this engages a given audience segment. Indeed, the era of true “creative intelligence" is upon us and this must be optimised to sales, long term customer loyalty and brand impact. 

AI’s rise to prominence 

AI may seem to have had its big break in the mainstream in 2023, but it’s been playing a significant role in digital advertising for a number of years, in areas such as in machine-learned bidding optimisation as well as SEO. Nevertheless, recent developments of AI such as Large Language Models and generative techniques are beginning to change how campaigns are designed and delivered, and are pushing the boundaries of what is possible. Indeed, the fact that AI-led campaigns featured extensively at this year’s Cannes Lions Festival is a strong indicator that AI is impacting creativity in the broadest sense.

While creativity has always been one of the most important elements of any successful ad campaign, the industry has historically found it difficult to establish what truly makes one collection of creative objects more effective than another. Let alone how this can be optimised over time.

AI can deliver against this use case. By enabling advertisers to analyse campaign performance at the most granular level, i.e. creative objects, a unique set of historic insight can be accumulated. This can then be applied to future campaigns and optimised through machine learning. The interface or control of such systems is also being revolutionised with the use of prompt or natural language-based commands. This gives the less technical marketing community a unique ability to apply AI in language that is familiar to them. 

Bridging the gap 

It's important to note that AI is an umbrella term, and there are a number of subsets with roles to play across creativity in advertising. These different technologies can work hand-in-hand to drive engagement and produce the real insights needed during and after a campaign.

For example, computer vision can be harnessed alongside generative AI to gain an understanding of how specific creative components are driving attention and engagement. In the coming years, as the technologies develop further, they will enable marketers to produce highly customised and very personalised content in real-time.

Furthermore, deep learning and neural networks can work together to link that engagement to brand awareness or brand uplift. Being able to track defined attention metrics creates a capability in which marketers can produce their ad creatives based on very granular data, and ensure they are optimised to produce the best performance. Importantly, the effectiveness of these insights, or this ‘creative intelligence’ can go further by helping to inform future campaigns in a genuine sequence of continuous improvement. 

Driving force for the future 

AI will be the principal driver of creativity in digital advertising going forward, and will be the key to driving real business outcomes. This will have significant implications for the current ecosystem. For example, legacy creative agencies will need to recognise that they may not have sufficiently invested in data science and engineering teams and therefore have not accumulated historic data to power their creative intelligence.

With this comes the fear that traditional roles will be directly impacted. Whilst this is true, it would be short-sighted to see this as a negative rather than reflecting on the opportunity this creates for designers to be even more innovative and allow AI to assess the results of their work.

AI, and a combination of many forms of AI will change everything about digital advertising, and will result in better outcomes across the board. But the area where advertisers will see the most dramatic change will be in creativity. This will also result in the gap between creative insight and campaign performance closing significantly, and the repository of creative intelligence becoming as important as the core brand values for a given advertiser.