By Iryna Kozirevych
Traditional TV advertising is fading away – by 2028, CTV ad spend in the USA is forecasted to surpass linear TV and reach approximately $46 billion. What is the driving force behind this evolution? CTV marketing enables precise targeting, enhanced engagement, and more effective measurement. However, the opportunities offered by AI are the key benefit related to CTV.
But what is the role of AI in CTV advertising? What are the key applications? What challenges and limitations to consider? In this guide, we answer these and other questions, so read on to find out how AI can transform your CTV campaigns.
Key Takeaways:
AI is the backbone of effective CTV advertising as it enables precise targeting, automates optimization, and reduces wasted ad spend.
With AI, you can scale your campaigns with greater efficiency.
AI enables data-driven advertising, which enables you to increase conversions and ROI.
Accurate performance measurement still remains a challenge due to the ecosystem’s highly fragmented nature.
Why AI is transforming CTV advertising?
As usual, let’s start with the basics.
What is CTV advertising?
CTV advertising implies delivering ads on smart TVs, gaming consoles, and other devices that are connected to the Internet (like, for instance, a streaming stick from Roku). It combines the storytelling power of TV with digital capabilities like audience targeting, real-time optimization, and performance measurement. Even though there are certain challenges associated with measuring the performance of CTV campaigns, this type of advertising allows you to deliver high-quality ads to engaged viewers and maximize the efficiency of your omnichannel strategy.
The shift from manual to data-driven advertising
Traditional CTV buying heavily relies on manual planning, broad audience assumptions, etc. AI revolutionizes the classic approach by enabling automated analysis of large datasets (viewing behavior, device data, contextual signals, and so on). This way, AI allows you to make smarter, faster, and more precise media decisions at scale. Since your effort becomes more data-driven, the conversion rate increases along with other important metrics.
Limitations of traditional CTV targeting
Basically, without AI, CTV advertising is pretty similar to linear TV marketing. In terms of targeting, the key limitations include inaccuracy, lack of flexibility, fragmentation across platforms, limited real-time optimization, and inefficient frequency control. These lead to wasted impressions and lower ROI.
How AI enhances decision-making in CTV
AI models can process vast amounts of first-party, contextual, and behavioral data to predict viewer intent, optimize bidding, and dynamically adjust targeting. This results in better audience segmentation, smarter budget allocation, improved frequency management, and continuous performance optimization throughout the campaign lifecycle. In general, CTV advertising with AI is much more effective than the traditional approach.
AI-powered data collection and analysis in CTV
To enhance the performance of any campaign, you need to analyze it continuously. Obviously, CTV is no exception. Let’s review some nuances related to CTV ad optimization with AI.
First-party, second-party, and third-party data in CTV
AI helps unify and analyze multiple data sources within CTV ecosystems. First-party data provides the most accurate audience insights. Second-party data enables you to fill in the gaps and build partnerships. Third-party data may help you to scale, but avoid leveraging it. Apart from introducing regulatory challenges, it usually lacks quality.
Instead, focus on first-party data and consider enhancing it with second-party information. AI models can then integrate these sources, resolve inconsistencies, and prioritize high-quality signals for targeting.
Household-level and cross-device data matching
CTV ads are typically delivered at the household level rather than to individual users. AI-powered identity resolution is a way to connect viewing behavior across TVs, smartphones, tablets, and desktops to build a more complete picture of audience activity. This enables consistent messaging, better frequency control, and more accurate attribution.
Privacy, consent, and data compliance challenges
Privacy frameworks and regulations like GDPR keep getting stricter, which poses a challenge for any brand. However, machine learning models can help anonymize data, manage consent signals, and support privacy-safe targeting methods (like contextual targeting). This allows you to maintain performance while respecting user rights and regulatory requirements.
“AI is redefining what’s possible in CTV. It eliminates the guesswork, optimizes bids, and continuously improves performance. Basically, AI transforms CTV from just another channel into a powerful conversion source.”
Olena Chudinovych
The CPO of Attekmi
Advanced audience targeting with AI
AI can streamline loads of tasks, including content creation, creative optimization, and so on. However, AI targeting in CTV advertising remains among the most significant benefits.
Behavioral and interest-based targeting
AI can analyze viewing patterns, content preferences, app usage, and engagement signals to identify what households are interested in. This allows you to target audiences based on their real behavior and deliver more relevant ads that align with their interests.
Predictive audience modeling and forecasting
AI can forecast which households are most likely to convert or engage with a brand based on historical exposure, cross-device behavior, and contextual factors. As a result, you can prioritize high-value audiences, optimize budget allocation, and improve the overall campaign ROI.
Contextual and real-time targeting
AI evaluates real-time signals to serve ads that match the viewing environment. For example, these can be fitness ads delivered during workout content. That is a privacy-safe approach, and it helps you increase relevance while remaining compliant with international regulations.
Lookalike audience creation
AI can leverage high-performing customer segments as a base for identifying new households that resemble your already existing customers. This can help you scale effectively.
Programmatic CTV advertising and AI automation
What about programmatic AI-based TV advertising? Here are the things you need to know.
Role of AI in programmatic CTV buying
AI automates the planning, buying, and optimization of CTV campaigns by analyzing audience data, placement quality, and performance signals in real time. Instead of relying on manual effort, you can use machine learning to determine which impressions to buy, at what price, and for which audience segments.
Real-time bidding and inventory optimization
AI can evaluate every available impression based on factors such as viewer behavior, content context, device type, historical performance, etc. This enables real-time bidding decisions that prioritize high-quality inventory, adjust bids dynamically, and allocate budgets to placements that are most likely to drive impact.
Reducing ad waste and improving efficiency
AI minimizes wasted spend by identifying low-quality inventory, managing frequency, and avoiding irrelevant impressions. As a result, you achieve better cost efficiency, higher ROAS, and more consistent campaign performance.
Automating optimization
AI continuously learns and optimizes throughout the campaign. It reallocates budget in real time, refines targeting, and adapts to changes in supply and viewer behavior.
Key benefits of AI-powered CTV advertising for brands
AI-powered CTV campaigns offer an entire set of benefits, and here are the main ones.
Improved targeting accuracy and ROI
AI enables you to reach the most relevant viewers based on real behaviors, interests, and predicted intent. By prioritizing high-value impressions and continuously optimizing bids and placements, AI reduces wasted spend.
Better audience insights and transparency
AI-powered analytics provide deeper visibility into who your ads reach, how often, and how campaigns perform across devices and platforms. You gain clearer insights into audience segments, viewing patterns, and conversion paths, making it easier to evaluate performance and refine future strategies.
Scalability and campaign automation
You can manage complex CTV campaigns at scale without increasing operational overhead. Machine learning handles targeting, bidding, and optimization in real time, which enables consistent performance even as inventory, audiences, and market conditions change.
Enhanced personalization
AI supports more relevant ad delivery by aligning messaging with audience interests and other factors. AI personalization in CTV ads leads to more engaging experiences, higher completion rates, and stronger brand recall.
Challenges and limitations of AI in CTV advertising
At the same time, there are also some challenges that you should consider.
Data fragmentation across platforms
The CTV ecosystem is highly fragmented. AI models often operate on incomplete or inconsistent datasets, which makes it difficult to build a unified view of the audience. This can limit targeting accuracy, measurement consistency, and cross-platform attribution. To reduce fragmentation, invest in data unification and interoperability.
AI transparency and explainability issues
Many AI-driven systems provide limited insight into how decisions are made, which can complicate performance analysis. It may be simply challenging for you to understand why certain audiences or placements perform better.
Choose an AI platform (or platforms) that offer explainable insights into targeting, bidding, and optimization decisions.
Regulatory and privacy constraints
As you know, regulations are getting stricter, so adopting a privacy-first strategy is critical. Instead of third-party cookies, rely on first-party data and privacy-safe approaches such as contextual advertising. AI can also be used to automate consent management, anonymize datasets, and ensure compliance with regulations like GDPR.
Data quality and bias risks
Incomplete, outdated, or biased datasets can lead to inaccurate targeting, ineffective optimization, and other issues. You should actively monitor data sources and model outputs to ensure performance and ethical compliance.
Conclusion
Integrating AI into your CTV strategy can drive impressive results, but it is crucial for you to remember that AI still requires human oversight. Consider it a powerful assistant, not a replacement for your skills, knowledge, and intuition.
By the way, getting your own ad exchange solution with support for CTV formats and environments can provide you with even greater control over your operations. At Attekmi, we offer a wide range of platforms, from a basic option to a fully customizable solution.
Contact us, and we will help your business grow.
FAQ
AI targeting in CTV advertising is based on viewing behavior, content context, and cross-device signals. AI predicts which audiences are most likely to engage or convert, optimizes bids in real time, and manages frequency. Thus, you deliver more relevant ads and reduce wasted ad spend.
Yes, when implemented correctly. AI can help you make the most of your data and reach your audience in a privacy-friendly manner. It also supports compliance with regulations like GDPR by automating consent management. However, you need to prioritize first-party data collection – it is the most valuable and “safest” type of information.
Actually, AI-powered CTV campaigns can be beneficial for virtually any brand. The number of CTV users is growing, so if you can reach your audience within this environment, CTV can become an effective addition to your omnichannel strategy. In turn, AI will enhance your efforts and help you reach your goals in a streamlined way.
