How AI Is Rewriting The Rules of Social Media Performance

Social media advertising is no longer a visibility game but a battle for engagement. With the rise of short-form video, the emergence of AI-generated content, and the fragmentation of audiences across platforms, attention is increasingly scarce. 

Every interaction, whether it consists of a like, a swipe, or a video replay, signals potential brand impact. But creating these moments is a challenge, and proving them is even harder. The question is no longer “did people see my ad?” but “what was the return on investment?” 

With social media spend expected to reach $406 billion (£307) by 2029, advertisers are demanding deeper insights into how these increased budgets support full-funnel outcomes. How different formats perform and how attention correlates to business results have become considerable focus points for advertisers, as there is significant variance, even within platforms. Advertisers now want to know how much attention they are buying, and at what cost. This is putting pressure on social media platforms to differentiate their ad offerings through new solutions. Many have responded by leaning into AI-based tools. 

For example, AI video editing capabilities enable advertisers to transform still images into dynamic video ads and even expand video frames by generating additional pixels. Meanwhile, agentic AI enables advertisers to generate tailored ad campaigns from simple prompts, reducing the complexity and cost typically associated with ad creation. 

This means brands can iterate content more frequently and responsively, adapting to engagement feedback in near real time. This drives higher interactivity, more relevant messaging, and ultimately, stronger user responses.

While a high number of likes might mean an ad resonated with consumers, without context, the metric becomes less meaningful. A broader view that includes sentiment, audience behaviour, attention, and ultimately, business outcomes, is required. 

Social media platforms are increasingly providing this transparency by scaling AI-based bidding tools. A relatively recent innovation, these solutions are helping brands and agencies optimise every social media interaction for maximum impact.

Learnings from The Open Web

It is estimated that by 2027, 80% of ad spend will be controlled by algorithms. On the Open Web, AI-based bidding tools have long helped advertisers squeeze more business-specific value from their demand side platforms (DSPs). 

These custom algorithms can ingest a variety of signals, like first-party data, attention metrics and offline sales data. Offering greater control over media buying strategies, these algorithms enable brands and agencies to optimise campaigns for specific outcomes like brand lift or attention, rather than generic metrics.

As media costs rise advertisers are becoming more selective, favouring transparent channels that can demonstrate ROI, including those on the Open Web that offer these customisable solutions. 

The same pressures and thinking are now being applied to the walled gardens, and social platforms are increasingly offering programmatic-style tools designed to optimise towards the metrics that matter most. 

In concert with pre- and post-bid solutions, these algorithms offer advertisers more flexibility and choice in realising their social media strategies,  whether that is maximising engagement metrics such as video completion rates, replay behaviour and in-feed interaction on short-form-heavy platforms. 

In a media environment where attention is a scarce resource, focusing on high-quality impressions can help amplify moments of genuine user interaction. This enables advertisers to be more effective with their budgets while also unlocking the potential of formats proven to capture attention.

Moving The Social Engagement Dial

As platforms strive and compete to meet advertisers’ growing demands for business-specific outcomes, these programmatic-style tools will scale quickly across social media. For those brands and agencies that have not yet investigated their capabilities, the message is clear: winning in social is no longer about being seen. It is about sparking – and proving – meaningful engagement. AI-driven tools are making that shift possible, turning fleeting attention into measurable brand impact.

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