As the utilisation of AI in advertising matures, brands have progressed beyond implementing a single AI technology to experimenting with the dizzying potential of deploying multiple AIs in tandem. One of the most exciting combinations is having contextual AI “talk” to generative AI, providing data and insights that the latter can use to optimise assets at superhuman speed and scale.

Let’s look at how each of these revolutionary technologies are delivering on the hype individually, and the magic that happens when we bring them together.

On one side, contextual AI, modern advertising’s privacy genius

As third-party cookies lose relevance and privacy regulations tighten, advertisers need new methods to deliver targeted messages without depending on user data. This is where contextual AI comes into play. Rather than relying on personal data or the dizzying number of identifiers in the market, contextual AI analyses the content users are consuming — whether it’s an article, a video, or an app — to determine the most relevant ads to display.

Contextual AI’s magic stems from deep learning and natural language processing which can identify patterns in text, visuals, and network-wide usage patterns. By understanding the meaning behind content and how users engage with it, contextual AI places ads in environments where they’re most likely to engage target audiences at the right time and place. Contextual advertising has evolved from optimising where an ad appears to considering precise timing, relevance, and audience habits.

With consumers increasingly aware of how their data is being used, brands that respect privacy concerns are gaining trust and loyalty. Contextual AI not only solves privacy challenges but also improves the effectiveness of campaigns by ensuring that ads feel naturally integrated in their environments and are less intrusive, which increases engagement and brand recall while reducing frustration.

On the other side, generative AI, a tireless asset creating machine

While contextual AI handles where and when an ad should be shown, generative AI takes over the creative side, producing the ad content itself. While human oversight remains essential, generative AI can generate or modify vast amounts of high-quality assets, including text, images, and even videos, at a scale and speed that humans simply cannot match.

For advertisers, this means they can create multiple versions of an ad with minimal effort, tailoring content to different audiences, formats, or platforms. From crafting personalised messages to attention-grabbing graphical design, generative AI provides creative teams with the tools to work more efficiently and experiment with new ideas. The technology can suggest keywords, headlines, or entire themes for ad campaigns based on existing data and past performance.

Generative AI’s ability to produce diverse content also aids in A/B testing. Marketers can quickly create and test different variations of an ad to determine which performs best, optimising campaigns in real time. The impact is clear: faster production, lower costs, and more engaging campaigns that resonate with target audiences.

Bring them together, and watch sparks fly

Contextual and generative AI each offer game-changing benefits on their own, but when combined, they create a powerful synergy that elevates campaign performance to new heights. By layering the creative capabilities of generative AI on top of insights gleaned from contextual AI, advertisers can produce more relevant, engaging, and personalised campaigns.

Here’s how this match made in heaven works in practice:

Contextual AI first analyses the content a user is engaging with, identifying key elements like themes, keywords, and sentiment to understand the context. Generative AI then uses this analysis to adapt ads so they fit seamlessly within the desired pre-defined contexts. The result is an ad that not only looks and feels like part of the surrounding content but is also optimised to match the user’s current mindset and needs — without one byte of data tied to the individual.

For example, if a campaign is intended to target users reading articles about eco-friendly products, advertising teams equipped with contextual AI can automatically detect aligned media content and serve ads that have been rapidly modified with generative AIto highlight its sustainability credentials, complete with messaging that resonates with the user’s values and a colour scheme that is associated with climate-friendly messaging. The combined use of these two AI technologies ensures that ads are not only well-targeted but also relevant to the user’s immediate interests, significantly boosting engagement.

This fusion also offers flexibility in content creation. With generative AI’s ability to produce numerous variations of an ad, marketers can tailor messages for different contexts without the need for completely new campaigns. The content can be adjusted in real-time to better match the webpage or app it appears on, ensuring that the ad feels natural and integrated.

Does AI synergy pay off in campaign results?

Of course, no matter how impressive AI is on paper, it wouldn’t matter if it didn’t drive results. To test what happens when contextual and generative AI work together, attention measurement pioneers Lumen gathered a panel of 300 whisky fans for an A/B test of a Johnnie Walker gift-themed campaign. One group was exposed to a campaign delivered with default contextual assets, while the other was exposed to contextually optimised assets created ad-hoc by Seedtag’s gen AI tool.

The gen AI optimised test returned 25% more attention than the generic test, which provided better brand recall as participants who saw more of the ad remembered the Johnnie Walker brand more strongly. Overall, the gen AI optimised campaign returned 400 seconds more attention per 1,000 impressions served.

The synergy between contextual and generative AI becomes even more exciting when we consider the full multimedia capabilities of the technology. One of the most impressive early indications of AI’s power came with the award-winning #NotJustACadburyAd 2.0 by Wavemaker in India (above), where a video of megastar Shah Rukh Khan was modified by generative AI to promote 2,500+ local stores. While this campaign did not use contextual AI, it did use contextual data — in this case, estimated location — to instruct the generative AI on what asset to create.

It’s easy to imagine the possibilities of such innovative deployments of AI once it proliferates further. Generative AI automatically updates images, videos, and audio based on AI-fed contextual signals such as content sentiment, device type, surrounding media, and its content. Ads will be more relevant and integrated into their surroundings than ever, while personalised to the user without impeding on their privacy. 

The combination of contextual and generative AI represents a major step forward for the advertising industry, offering the ability to deliver hyper-relevant, personalised campaigns at an unprecedented scale. Contextual AI ensures that ads appear in the right place at the right time, while generative AI takes care of crafting compelling content that resonates with audiences. Together, they create a superhuman level of campaign performance that is more efficient, engaging, and effective.