Top AdTech Trends That Shaped Digital Advertising in 2026

AdTech sits at the intersection of media, data, and advanced technology, with rapid innovation reshaping how digital advertising is planned, bought, and measured.Identity-powered marketing of an unprecedented scale; real-time multi-channel convergence; AI-powered transformation – these are only a couple of the next-gen AdTech trends that are becoming the new normal. With the pace of change being so fast, every digital advertiser must keep pace with what’s coming to keep the quality bar high and receive solid output from advertising activities.

The scale of that pace is measurable. Global retail media ad investment alone is projected to cross $200.4 billion in 2026 and climb to $223.4 billion in 2027, when it will account for 15.2% of all worldwide ad spend. That growth is driving changes in AdTech strategy.

In this article, we take a closer look at the following AdTech industry trends expected to shape the industry landscape in 2026:

• AI and machine learning.
• Privacy-first advertising.
• Retail media networks.
• Connected TV and streaming.
• Walled gardens vs. open web.
• Emerging ad formats.
• Measurement and attribution in the attention economy.
• Sustainability and responsible media.

Read on to see how they affect digital advertising tools and methods to supercharge your business practices with their help.

AI and Machine Learning

What once appeared experimental is now foundational to modern AdTech architecture. Artificial intelligence has rapidly evolved from isolated optimization use cases into a core operational layer powering campaign execution, measurement, and governance at scale. Leading platforms, such as Amazon, illustrate this shift through AI-driven video generation and real-time localization capabilities that enable advertisers to scale creative output across markets with unprecedented speed and precision.

Amazon Ads AI-powered Video Generator

https://advertising.amazon.com/library/news/video-generator

Importantly, AI adoption in AdTech is not entirely new. Machine learning has long underpinned bidding logic, forecasting models, and audience targeting. What has changed is the sophistication of these systems and the level of trust advertisers now place in automated decision-making. Today, AI operates as a full-stack campaign engine rather than a standalone tool, influencing nearly every stage of the advertising lifecycle.

In practice, AI-driven AdTech systems enable:

• End-to-end campaign orchestration, from setup and traffic allocation to omnichannel optimization.
• High-velocity experimentation, with teams testing hundreds of creative and targeting variations daily.
• Continuous performance improvement through automation paired with controlled experimentation.
• Built-in governance, including brand-safety enforcement, version control, and disclosure for AI-generated content.

By enhancing analytical accuracy and automating execution across the advertising pipeline, AI enables advertisers to operate at a scale that manual workflows can’t support. This shift now has a name: agentic AI. These systems are given a goal (say, a target CPA or a sales number) and independently plan, execute, and adjust the campaign to reach it, without a human approving every step.

AI-powered personalization is widely adopted in marketing, with 92% of business leaders saying they use it to fuel growth. Yet only a small share of companies have reached a mature level of personalization. The BCG Personalization Index found that just 10% of companies currently qualify as “personalization leaders”. AI adoption may be widespread, but turning it into efficient strategies still requires work across data, targeting, testing, content, and measurement.

Human control still matters in AI-driven advertising. Companies need to:

• know how AI makes decisions;
• set clear rules for its use;
• monitor its output.

These safeguards help prevent compliance, operational, and reputational problems. In 2026, AdTech brands need clear rules and human oversight around AI.

Privacy-First Advertising

Third-party cookies are still available, but advertisers can no longer treat them as the only foundation for audience targeting and measurement. Privacy rules now place more limits on how audience data can be collected and used. AdTech businesses should work with a mix of first-party data, contextual signals, consented IDs, and modeled attribution.

This shift puts more focus on:

• Owning direct customer relationships and first-party data.
• Measuring campaigns without exposing unnecessary user data.
• Reducing reliance on third-party tracking.
• Following privacy and compliance requirements across advertising platforms.
• Maintaining clean identity and consent data.

Identity hygiene and consent represent the new backbone of ethical, compliant advertising. Brands that activate first-party audiences and provide privacy-safe onboarding channels win in the new, privacy-focused market. On the practical level, the implementation of privacy-first advertising works as follows:

• Upper funnel scaling for consenting customers in walled gardens.
• Contextual and attention-based ad space buying for incremental increases in outreach.
• Closed-loop customer data measurement in retail media or specialized commerce environments.

The next step is the use of data clean rooms, which give advertisers and their partners a way to compare and analyze audience data without directly sharing sensitive user information.

Clean Rooms: Where First-Party Data Actually Gets Activated

First-party data gives brands a direct view of their own customers, but it doesn’t show the complete audience they could reach or measure. Data clean rooms bridge that gap by letting advertisers securely match their first-party records with data from publishers, platforms, or other partners without sharing user-level information.

This isn’t a theoretical concept anymore. SiriusXM Media is one example of how publishers are putting this model into practice. The company partnered with LiveRamp to build an audio-focused clean room where advertisers can match their customer data with SiriusXM’s listener base to plan and measure campaigns.

More publishers across CTV, retail media, and the open web are likely to adopt similar models in 2026. Clean rooms are becoming a common way to support audience targeting and measurement without relying on third-party cookies or device IDs.

Retail Media Networks

The present of the AdTech industry is quite monopolistic, with Amazon controlling a dominant share of retail media ad revenue and traffic. In the U.S. specifically, Amazon captured 78% of retail media ad spend in 2025, with Walmart a distant second at 7.5%. However, retail media networks (RMNs) are rising in outreach and creating healthy competition for well-established advertising giants. Some examples of industry-wide significance include:

• Carrefour Links is currently positioned as a cross-asset retail media platform with a full transaction measurement feature suite.
• Tesco Media and Insight Platform is now powered by dunnhumby’s data science team to provide full-funnel tools for customer outreach planning, targeting, and campaign evaluation.

Tesco Media and Insight Platform
powered by dunnhumby

https://www.dunnhumby.com/tesco-media-insight-platform/

This fundamental change thrives on first-party shopper data, which gives ad buyers and sellers a safe environment for mutually beneficial transactions. They possess the much-needed closed-loop accountability that enables informed investment in ad impressions that really work. In other words, retail media gives tangible insights into ads that translate into sales, thus informing high-ROI ad activities.

Retail media businesses operate through many advertising channels spanning on-site placement, CTV, video, and audio ads, thus giving ad buyers unique opportunities to affect consumer decisions at early stages of marketing funnels and achieve high advertising impacts.

Globally, retail media ad spend is projected to cross $200.4 billion in 2026 and $223.4 billion in 2027. Higher spending doesn’t automatically mean higher ad impact. A WARC Media report found that shoppers remembered ads 47% less often on major retailer platforms like Amazon and Walmart than in generic off-site environments. The same study shows that stronger creative increased short-term brand choice among undecided shoppers by 12%. These findings suggest that access to closed-loop sales data works best when advertisers also pay attention to creative quality.

Thus, businesses that wish to take advantage of the RMN rise can follow the best industry practices as follows:

• Develop RMN advertising plans around a nuanced understanding of the buyer’s journey.
• Develop consistent measurement KPIs for RMN advertising, making performance comparable and informative.
• Design product offerings in a retail-ready, creative format, thus removing shoppers’ friction and delivering a consistent experience from advertising to sales.
• Focus on data analytics and reporting across the RMN’s advertising pipeline to assess performance and plan the budget.

These moves can turn an RMN partnership into a scalable growth lever, giving tangible benefits to businesses in 2026.

Retail Media Is Moving Beyond the Website

Retail media used to mean sponsored product listings and on-site display. That definition is now too narrow. Networks are expanding into off-site programmatic advertising, social and video, and digital screens in physical stores. New placements are bringing retail media closer to digital out-of-home (DOOH), particularly as retailers add screens in stores and other high-traffic locations.

Programmatic DOOH is growing alongside this shift. Among recent buyers, average spend is expected to rise 44% over the next 18 months, with 99% planning to increase or maintain their investment. For retailers and advertisers alike, a screen inside a store is no longer just signage. It is measurable advertising inventory that can connect with first-party shopper data that makes retail media valuable.

Connected TV and Streaming

Multi-platform viewing is the new normal, and brands need to factor this content consumption pattern into their advertising campaign designs. The Connected TV (CTV) format transforms even traditional TV-based buying models into digital formats, with frequency management and audience targeting coming to the fore. Some examples of creative solutions in CTV advertising are as follows:

• Amazon’s Prime Video limited ads feature, which expands ad inventory beyond traditional TV formats in multiple eligible countries.
• Amazon offers interactive video and pausable ads in European markets, where the viewers can learn more about the product, scan a QR code, and add products to a cart without leaving the stream.

Amazon Interactive & Shoppable Ads on Prime Video

Amazon Ads example of an interactive Prime Video ad with on‑screen product engagement options like “Add to cart” and interactive CTAs (as documented in Amazon’s ad specs).

https://advertising.amazon.com/library/guides/interactive-ads

CTV ad design for streaming platforms evolves with the market, posing new technical demands for marketers. For instance, the golden standard for 2026 includes:

1. Strong first 2 seconds
2. Clear audio branding
3. An engaging CTA, with a QR code, short URL, or voice/click instructions.

Notably, CTV ad revenue is concentrated among a small group of sellers, including Amazon, Disney, Google (YouTube), and Roku. In the U.S. alone, CTV ad spending is projected to reach roughly $38 billion in 2026, growing close to 14% year-over-year, making it the fastest-growing advertising channel in the country. These dynamics can make it harder for smaller CTV players to access audience data and compete on pricing.

CTV advertisers also face inconsistent measurement across platforms. They often have to piece together reach, frequency, and attribution data from separate ecosystems.

This fragmentation is pushing the industry toward the “Total Video” model. It brings linear TV, CTV, and online video together for measurement instead of treating them as separate buys. Server-side ad insertion and dynamic ad insertion help streaming platforms serve targeted, addressable ads within live and on-demand content without disrupting playback.

Walled Gardens vs. Open Web

Walled gardens, often powered by clean room environments, are closed advertising ecosystems controlled by a single platform. These environments centralize user data, inventory, buying tools, and measurement under one operator, enabling deterministic attribution and privacy-safe activation. However, this control comes at the cost of limited transparency, restricted interoperability, and reduced data portability.

In contrast, the open web consists of independent publishers, premium editorial inventory, and mobile applications operating across a decentralized ecosystem. It offers advertisers flexibility, partner diversity, and broad reach, allowing them to dynamically adjust supply paths based on performance. At the same time, responsibility for quality control, fraud prevention, and brand safety shifts entirely to the advertiser.

In 2026, successful advertisers rarely choose one environment over the other. Instead, they design hybrid media strategies based on each ecosystem’s strengths.

When walled gardens deliver the most value:

• Activating consented, first-party audiences at scale.
• Running upper-funnel and performance campaigns with closed-loop measurement.
• Operating within strict privacy and compliance frameworks.

Where the open web excels:

• Accessing premium editorial environments and regional inventory.
• Executing differentiated ad formats with greater creative control.
• Maintaining pricing leverage and reducing platform dependency.

To operate effectively on the open web, advertisers must invest in supply-path optimization (SPO), fraud detection, and brand-safety enforcement to ensure predictable performance and risk management.

The most resilient AdTech strategies balance both models. Walled gardens provide control and stability, while the open web delivers flexibility, transparency, and continuous optimization opportunities. When combined thoughtfully, these environments enable advertisers to scale reach, preserve governance, and avoid over-reliance on any single platform.

Owning the Stack and the Rise of Custom AdTech

A related and increasingly visible shift is happening in both environments. More publishers, retailers, and advertisers are choosing to own core layers of their AdTech infrastructure instead of renting them from third-party platforms. Common reasons include opaque platform fees, tighter privacy requirements, and the need for direct control over first-party data and AI models.

This doesn’t mean abandoning walled gardens or the open web. A publisher may own its clean room, ad server, or identity graph. It can then connect these systems to Amazon, Google, and other advertising platforms while keeping key parts of its data and monetization logic under control.

Supply-path optimization is also changing. Advertisers are removing unnecessary intermediaries from programmatic supply chains. Some are taking this further by eliminating low-value intermediaries altogether, a practice often referred to as Supply Path Elimination (SPE).

Emerging Ad Formats

Advertisers experiment with ad formats to bridge consumer attention and action. These efforts are tech-driven and contingent on trending content formats. In 2026, the AdTech community makes its chief stake on the following:

• Shoppable videos.
• Interactive CTV units (QR-driven CTAs, pause ads).
• Location-personalized ads and videos.
• In-game and esports ad integrations.
• Commerce-aware creative formats.
• Digital out-of-home and in-store digital screens.

A key 2026 trend is location-based interactive video. Innovative technology enables brands to create one original ad, which gets localized in real time to reach out to consumers in multiple locations in a way that works the best for them.

Much of this real-time localization and personalization is powered by Dynamic Creative Optimization (DCO). This technology assembles and adjusts ad creative on the fly based on live signals such as location, weather, inventory, or a viewer’s stage in the funnel, rather than shipping one static version of an ad to everyone.

Podcasts also remain popular and compete with video streams, showing that consumers are still attracted to an audio format of data consumption. Thus, marketers and AdTech industry players have to take this trend seriously; some of them stick to audio formats, while others develop new fusions of audio and video to capture new audiences. Some examples of action in this area include:

• Netflix’s growing collaboration with Spotify and iHeartMedia.
• SiriusXM’s video ads project on YouTube.

Each of these approaches offers distinct benefits, including new audience outreach, channel diversification, and sustainable growth in the conditions of transient AdTech trends. Omnichannel and omniformat advertising also gives AdTech brands greater flexibility, with continuous experimentation keeping them on top.

Measurement and Attribution in the Attention Economy

Advertisers now measure campaigns across more channels, from walled gardens and the open web to CTV, retail media, and physical stores. Last-click attribution can’t capture the complete customer journey when people see ads across several of these environments.

That’s why the following measurement approaches are gaining more attention in 2026:

• Marketing Mix Modeling (MMM) is being modernized. AI and automated data processing are making MMM models faster to update. Marketers can use them more often when deciding where to allocate budget.
• Attention metrics are becoming more common as advertisers look beyond whether an ad appeared on screen. Viewability measures an ad’s visibility after it loads. Metrics such as dwell time, eye-tracking-based engagement, and scroll depth indicate how much attention an ad receives.
• Clean-room measurement lets advertisers and publishers work with first-party data without exchanging raw user-level data. Advertisers can use clean rooms to measure conversions, audience overlap, and incrementality.

The measurement framework needs to match the campaign objective. CTV, retail media, and open-web campaigns generate different types of data, so advertisers may need different metrics to assess reach, attention, conversions, or incremental impact.

Sustainability and Responsible Media

Sustainability is becoming a factor in consumer spending and media planning. According to PwC’s 2024 Voice of the Consumer Survey, consumers say they are willing to pay 9.7% more on average for sustainably produced or sourced goods. The same survey found that 85% have experienced the effects of climate change directly in their daily lives.

In AdTech specifically, this is showing up as Responsible Media. The strategy brings carbon footprint, ad quality, brand safety, and inclusive creative into the same media evaluation. High-emission ad environments often have cluttered pages, excessive redirects, and slow load times. These technical issues can also hurt viewability and page performance.

AdTech vendors and buyers can reduce unnecessary ad processing and infrastructure use through lighter ad delivery and cleaner supply paths. These changes can also improve load speed and exposure without relying on additional ad inventory.

Conclusion

The AdTech trends discussed above show how the ad market is evolving in 2026. Deeper integration of new technologies, AI automation, identity management, ad quality controls, and new ad formats are changing how advertising works across channels.

These trends also put more focus on proving results. Agentic AI needs to show measurable business value. Retail media and CTV need to connect ad exposure with outcomes such as attention, conversions, and sales. Sustainability is becoming another factor in media evaluation, alongside other performance and quality metrics.

Brands that adapt to these trends can maintain existing customer relationships and reach new audiences as new advertising channels and formats gain traction.