Digital advertising has always been about one thing: getting the right message in front of the right person at the right time. However, as online competition grows, achieving this has become increasingly complex. Consumers expect personalised, relevant ads, and businesses need efficient targeting methods to avoid wasted ad spend.
AI-powered ad targeting is transforming the way businesses connect with their audiences. By leveraging machine learning, predictive analytics, and automation, advertisers can now serve highly relevant ads to the right people, at the right time, on the right platform.
From search ads on Google to paid social campaigns on Meta, LinkedIn, and TikTok, AI is refining how businesses engage potential customers. But not only online ads are benefiting from AI advancements. Out-of-Home (OOH) advertising, such as digital billboards, are also getting a data-driven upgrade, making them more targeted and responsive than ever before.
AI’s role in digital ad targeting
How AI refines audience targeting
Traditional advertising methods relied heavily on broad demographic data—age, gender, income, and interests—often leading to wasted impressions on the wrong audience. AI has changed this by introducing advanced audience segmentation techniques based on real-time behaviour, intent signals, and contextual data.
For example, Google Ads’ In-Market Audiences use AI to analyse search queries, browsing history, and purchase patterns to predict when users are ready to buy. This means advertisers don’t just target people interested in their industry but also those who are actively looking for a product or service right now.
AI also enhances audience segmentation through:
- Lookalike audiences: AI scans existing customer data and finds new users with similar online behaviours.
- Dynamic intent signals: Instead of relying on static user interests, AI constantly updates audience profiles based on real-time activity.
The result? More relevant ad placements, higher engagement, and better conversion rates.
Real-time bidding & smart automation
AI plays a crucial role in real-time bidding (RTB), the automated auction system that determines which ads appear when a webpage loads. Rather than relying on fixed bidding strategies, AI-powered platforms like Google’s Smart Bidding continuously adjust bids based on factors like:
- Device type
- Time of day
- User’s past interactions
- External signals like weather conditions
For instance, if an AI system detects that users in London convert better on mobile devices after 6 PM, it can automatically increase bids for mobile ads during evening hours, maximising budget efficiency.
This level of automation means advertisers can focus on strategy rather than manually adjusting campaigns, allowing AI to optimise performance at scale.
AI-Driven personalisation & dynamic ads
Beyond targeting and bidding, AI is reshaping ad creative optimisation. Dynamic Creative Optimisation (DCO) ensures that ad content is tailored to individual users in real time.
For example, Meta’s Advantage+ Creative Suite automatically tests different combinations of headlines, images, and calls to action (CTAs), learning which versions perform best for different audience segments.
Imagine an e-commerce store running a campaign for trainers. AI can:
- Show sports-focused ads to users who browse fitness websites.
- Display fashion-oriented creatives to users interested in streetwear.
- Adjust colour and design based on past purchasing behaviour.
This approach not only improves engagement rates but also reduces ad fatigue, ensuring audiences don’t repeatedly see the same message.
AI in social media advertising
Social media platforms have fully embraced AI to enhance ad targeting precision.
On Facebook and Instagram, AI analyses user engagement patterns to determine which ads users are most likely to interact with. If someone frequently watches beauty tutorials, Meta’s AI will prioritise beauty-related ads in their feed.
LinkedIn, meanwhile, uses AI for predictive lead scoring, identifying professionals most likely to engage with B2B content. This ensures that businesses advertising on LinkedIn can prioritise high-quality leads, reducing acquisition costs.
On TikTok, AI plays an even bigger role by analysing video-watching habits, engagement duration, and content preferences. This allows brands to deliver ads that blend seamlessly into the user’s content feed, making them feel less intrusive and more engaging.
By leveraging AI across social platforms, businesses increase relevancy, improve conversion rates, and reduce wasted spend.
AI’s growing role in OOH advertising
Historically, OOH advertising—billboards, bus stop ads, and transit posters—was limited in its ability to target specific demographics. Marketers relied on placing ads in high-footfall locations without real-time audience insights.
However, AI is transforming OOH into a dynamic, data-driven channel. Digital Out-of-Home (DOOH) advertising now integrates AI-powered:
- Geo-fencing: Serving ads to mobile users near specific OOH placements.
- Audience heatmaps: Determining the best times and locations for ad placements based on crowd density.
- Programmatic buying: Automating OOH ad placements based on real-time conditions.
Case study: AI-Powered DOOH in the UK
Audi utilised digital billboards that responded to real-time traffic and weather conditions to display contextually relevant advertisements.
Campaign details:
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Duration & Locations: The campaign ran across 211 digital screens in nine UK cities, including London, Birmingham, and Manchester.
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Dynamic content: The billboards showcased different Audi models based on real-time data:
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Weather conditions: For instance, during adverse weather conditions, ads for Audi’s quattro all-wheel-drive vehicles were displayed, highlighting their capability in challenging conditions.
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Traffic density: In heavy traffic areas, the billboards promoted Audi’s compact models, emphasising their suitability for urban driving.
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This innovative approach allowed Audi to deliver highly relevant advertisements, enhancing engagement by aligning their messaging with the immediate environment and audience needs.
AI’s impact on ROI in UK advertising
AI-driven advertising strategies have led to remarkable improvements in campaign efficiency and cost-effectiveness.
According to a Statista report, AI-powered campaigns in the UK achieved:
- 32% higher ROAS (Return on Ad Spend) than non-AI campaigns.
- 18% lower CPA due to smarter bid adjustments.
- More accurate attribution modelling, helping brands identify which channels drive conversions.
As AI continues to evolve, businesses that integrate it into their advertising strategies will remain ahead of the competition, benefiting from better audience insights, lower costs, and higher engagement.
Conclusion & Next steps
AI is no longer a futuristic concept—it’s a game-changer in modern advertising. From PPC and social media to DOOH advertising, machine learning is making ad targeting more efficient, responsive, and profitable.
If you’re ready to optimise your ad strategy with AI, get in touch for a free AI marketing audit today.
