Open Internet: What It Is and Why It Matters in Digital Advertising
March 26, 2026
9
minutes read
The open internet accounts for a smaller share of global ad revenue than walled gardens, yet it remains the only environment where advertisers can access independent inventory, transparent measurement, and cross-platform flexibility at scale. In this article, we break down how the open internet ecosystem works, where it differs from closed platforms, and why it continues to play a critical role in modern media strategy.
Every advertising platform measures performance differently. Google reports conversions through its own attribution models. Meta uses its proprietary Business Manager dashboards. Amazon ties ad spend to retail outcomes within its closed ecosystem. Each of these platforms delivers useful data for campaigns running inside its walls. But when a brand's media plan spans display, connected TV, social, search, and independent publisher inventory simultaneously, platform-level reporting alone cannot deliver a complete picture.
This disconnect between platform dashboards and actual cross-channel performance is growing. According to the IAB's 2026 Outlook Study, cross-platform measurement has risen to a priority for 72% of advertisers in 2026, up from 64% the previous year—a clear signal that brands are actively seeking visibility beyond any single platform's reporting.
This article explores what the open internet actually means in digital advertising, how its infrastructure works, what advantages it offers, and where its structural challenges lie. It also examines why the growing fragmentation of the broader ecosystem is pushing advertisers toward new frameworks for understanding performance across platforms.
What is open internet in digital advertising?
The open internet (sometimes called the open web) refers to the collection of independent websites, mobile applications, streaming services, and digital publishers where advertising inventory is available through open marketplaces and programmatic platforms. It is the portion of the digital ecosystem that operates outside the closed environments controlled by major tech platforms.
Unlike advertising within a single platform, the open internet runs on a distributed infrastructure. No single company controls the inventory, the data, or the measurement. Instead, a network of ad tech platforms connects advertisers to publishers through open-access bidding environments.
Several characteristics define the open internet as an advertising environment:
Open-access inventory. Publishers make their ad space available through exchanges and supply-side platforms (SSPs), allowing any qualified buyer to bid on impressions.
Independent publishers and media owners. The open internet includes everything from major news outlets and niche content sites to CTV apps and podcast networks—all operating independently from platform-owned properties.
Programmatic buying infrastructure. Advertisers access open internet inventory primarily through demand-side platforms (DSPs) that automate bidding and targeting across thousands of properties in real time.
Decentralized ecosystem design. Rather than a single platform dictating the rules, the open internet ecosystem is governed by industry standards, open protocols, and multiple competing technology providers.
This is the environment where programmatic open internet advertising operates at scale. It is also where the tension between reach and complexity plays out most visibly.
⚡ Think of the open internet as the full ecosystem of independent digital properties where advertisers can access audiences free from any single gatekeeper's control.
How the open internet differs from walled gardens
The difference between the open internet and walled gardens is structural. In a walled garden, a single platform controls inventory access, audience data, campaign measurement, and reporting. Google, Meta, and Amazon are the most prominent examples. In the open internet, these functions are distributed across multiple independent providers, giving advertisers more flexibility and more operational complexity.
Google's, Meta's, and Amazon’s vs traditional media’s ad revenues (Source)
According to Statista, walled gardens accounted for approximately 78% of global digital advertising revenue in 2022, with that share projected to reach 83% by 2027. The open internet captures the remainder, yet it represents a disproportionately large share of where users actually consume content beyond social feeds and search results.
The practical implication is straightforward. Walled gardens trade flexibility for convenience—they simplify execution within a single environment but restrict an advertiser's ability to compare, verify, or optimize across platforms. The open internet offers the opposite trade-off: broader access and greater transparency, but more coordination required.
The technical infrastructure behind open internet advertising connects advertisers to publishers through a chain of specialized platforms. Each one serves a distinct function.
Publishers—the websites, apps, and streaming platforms that create content—make their ad inventory available by working with supply-side platforms (SSPs). SSPs manage the publisher's inventory, packaging it for sale and connecting it to ad exchanges, which function as open marketplaces where buying and selling happens in real time.
On the buying side, advertisers use demand-side platforms (DSPs) to place bids on available impressions. DSPs evaluate available inventory against the advertiser's targeting criteria—audience segments, contextual signals, geography, device type—and submit bids through real-time bidding (RTB) auctions. The entire process, from a user loading a page to an ad being served, takes roughly 100 milliseconds.
This infrastructure allows advertisers to reach audiences across thousands of independent properties through a single buying interface, rather than negotiating directly with each publisher. It is the mechanism that enables programmatic advertising at scale—and in the US alone, programmatic transactions have accounted for more than 90% of digital display ad spending since 2023.
The open internet ecosystem is not static. Connected TV, digital audio, and digital out-of-home inventory are increasingly transacted programmatically, expanding the range of environments where advertisers can buy through open marketplace infrastructure.
Understanding how ads move through the open internet supply chain matters because it directly affects cost, efficiency, and transparency.
A single impression on the open internet may pass through several intermediaries before reaching a user. The typical path runs from the advertiser through a DSP, into an ad exchange or SSP, and finally to the publisher. Some impressions travel even more complex routes—through multiple resellers or exchanges—before they find a buyer.
This structure creates both scale and fragmentation. On one hand, advertisers can access enormous reach and compete for inventory across diverse publisher environments. On the other, each intermediary in the chain introduces fees, latency, and potential opacity.
The economics are significant. According to ANA's Q2 2025 Programmatic Transparency Benchmark, roughly $26.8 billion of global programmatic media spendremains unrealized—lost to inefficiencies, poor ad quality, or mismatched supply paths. Separate analysis suggests that publisher revenue was materially lower than the top-line ad dollar, averaging 51% in the 2020 study and 65% in the 2022 follow-up, with stronger results in some PMP environments.
⚡ Every intermediary in the supply path either adds measurable value or subtracts from the advertiser's working media. The challenge is knowing which is which.
Industry standards like sellers.json and the SupplyChain Object (SChain) now allow buyers to trace exactly which intermediaries are involved in a transaction. Supply path optimization (SPO) has become a core discipline, focused on selecting the most direct, cost-efficient, and transparent routes to quality inventory.
Despite its complexity, the open internet remains a critical component of the media mix. The IAB's 2026 Outlook Study projects9.5% growth in total US ad spend for the year, with CTV—a core open internet channel—forecast to grow 13.8% year over year. Advertisers continue investing here for clear structural reasons.
Broader audience reach
The open internet encompasses millions of websites, apps, and streaming platforms. This means advertisers can reach audiences in environments that major platforms do not control—from niche publisher sites and news outlets to independent CTV apps and podcast networks.
CTV alone illustrates the scale of this opportunity. According to Winterberry Group data reported by Marketing Charts, US CTV ad spend grew15.1% to $33.1 billion in 2025, with a further 22% increase forecast for 2026, bringing the total to approximately $40.4 billion. Much of this inventory is transacted through open programmatic infrastructure.
US online media spending revenue and outlook 2025-26 (Source)
Unlike walled gardens, where attribution and reporting remain proprietary, open internet advertising allows brands to work with independent measurement providers, third-party verification tools, and custom attribution frameworks. Advertisers can audit where their ads appear, verify viewability, and validate audience delivery through providers that are not owned by the same company selling the media.
The open internet supports a range of transaction types—from open RTB auctions to private marketplace (PMP) deals and programmatic guaranteed arrangements. Advertisers can adjust inventory sources, creative formats, and targeting strategies dynamically without being locked into a single platform's tools or optimization logic.
Diversification beyond platform ecosystems
Relying heavily on two or three platforms concentrates risk. Policy changes, algorithm updates, or pricing shifts within a walled garden can materially affect campaign performance overnight. Open internet campaigns distribute that risk across a broader set of publishers and technology partners, giving brands more resilience and negotiating leverage.
⚡ On the open internet, diversification serves two roles: media planning strategy and risk management discipline.
Structural challenges of the open internet
The same distributed architecture that gives the open internet its advantages also introduces operational and strategic friction.
Fragmented inventory
Inventory on the open internet is spread across thousands of publishers, exchanges, and SSP connections. This creates enormous reach, but also makes it difficult to maintain consistent quality standards, brand safety controls, and frequency management across all sources without dedicated infrastructure and expertise.
Complex measurement environments
With no single platform controlling both the buy side and the sell side, measurement on the open internet requires assembling insights from multiple tools and frameworks. The IAB's State of Data 2026 report found that between 60% and 75% of senior brand and agency decision-makers believe current advanced measurement approaches fall short on rigour, timeliness, and trust. This is a significant finding, and it points directly to the challenge of operating across disconnected systems.
Supply path inefficiencies
As noted in the supply path section, multiple intermediaries can erode the percentage of ad spend that reaches working media. Without active supply path optimization, advertisers risk overpaying for inventory that could be accessed more directly—or, worse, funding low-quality placements that deliver negligible business value.
The rise of ecosystem fragmentation
The advertising ecosystem no longer divides neatly into "walled gardens" and "open internet." A third category has emerged: retail media networks, commerce media platforms, and CTV-specific ecosystems that blend characteristics of both models.
US retail media spending through programmatic channels grew by 41.7% in 2024 and is projected to exceed $30 billion by 2026. Commerce media overall is forecast to grow 12.1% in 2026, nearly 30% faster than the rest of the ad market, per the IAB.
Each of these environments operates with its own data, its own measurement framework, and its own reporting dashboard. The result is a multi-layered fragmentation where advertisers must reconcile performance data from walled gardens, open internet campaigns, retail media buys, and CTV platforms—all simultaneously, all using different metrics.
This is not simply an operational inconvenience. It is a structural challenge that affects strategic decision-making. When no single view of performance exists across channels, budget allocation decisions are based on incomplete information. Attribution becomes contested. Incrementality is difficult to prove.
The industry's response is still emerging. The IAB launchedProject Eidos in early 2026—a multi-year initiative to develop shared, interoperable standards for cross-channel advertising measurement. The need for this type of coordination underscores how far the ecosystem remains from a unified framework.
For advertisers, this means the question is no longer just "open internet or walled garden?" It is: how do we build independent visibility across an ecosystem that is fragmenting faster than measurement can keep up?
The future of the open internet in a privacy-first world
Privacy regulation, signal loss, and evolving identity frameworks are reshaping how the open internet operates—but they are not diminishing its importance.
The deprecation of third-party cookies has been the industry's dominant narrative for years. While Google ultimately reversed its plan to remove cookies from Chrome entirely, the broader shift toward privacy-first infrastructure continues. Advertisers are adapting through several parallel strategies:
Contextual targeting has re-emerged as a core tactic, with adoption reaching an estimated 55% among programmatic advertisers globally. Advances in natural language processing now enable granular content analysis that was not possible even two years ago.
First-party data strategies are becoming essential, as brands build consented data relationships directly with consumers to reduce reliance on third-party signals.
Clean rooms and privacy-safe measurement allow advertisers and publishers to match data sets for attribution and analysis without exposing individual-level information.
Alternative identity frameworks, including Unified ID 2.0 and publisher-authenticated traffic, offer open-internet-compatible identity solutions that respect user consent while maintaining targeting precision.
⚡ The open internet draws on multiple identity signals rather than relying on any single one. Its distributed architecture allows it to absorb privacy shifts through parallel solutions working simultaneously.
The open internet remains essential precisely because it is not controlled by a single entity's privacy framework. Where walled gardens impose their own rules on data access (and benefit commercially from doing so), the open internet allows the industry to develop and adopt shared, interoperable privacy standards collaboratively.
Conclusion: building independent visibility in a fragmented ecosystem
The open internet is not a niche corner of digital advertising. It is the foundational infrastructure through which brands access audiences, publishers, and inventory beyond the control of any single platform. It provides reach, flexibility, and transparency that walled gardens, by design, do not offer.
At the same time, the open internet introduces real operational complexity. Inventory fragmentation, supply path inefficiencies, and disconnected measurement systems require dedicated strategy, technology, and expertise to manage effectively.
This is the challenge that AI Digital's Open Garden framework was built to address. Open Garden operates as a DSP-agnostic, cross-platform ecosystem designed to give advertisers complete transparency and control over their media investment, without being locked into a single platform's tools, data, or optimization logic. Rather than replacing the open internet's distributed architecture, Open Garden works with it, connecting advertisers to 15+ DSPs and unifying campaign performance data across channels that would otherwise remain siloed.
Supporting this framework are two complementary solutions. Smart Supply, AI Digital's supply-side service, uses AI-powered supply path optimization to filter out low-quality inventory, reduce intermediary fees, and ensure brand-safe placements across premium publisher environments. Elevate, AI Digital's intelligence platform, layers predictive analytics and real-time optimization across the entire media buying process, enabling faster, data-informed decisions while maintaining strategic human oversight.
Together, these solutions reflect a broader principle: that the open internet's advantages—reach, transparency, flexibility—are only fully realized when advertisers have the infrastructure to coordinate across its fragmented ecosystem, not just participate in it.
Key takeaways for marketers:
The open internet expands audience reach far beyond major platform ecosystems, including access to CTV, independent publishers, and programmatic marketplaces.
Independent measurement and third-party verification tools are available on the open internet—a structural advantage over closed-platform reporting.
Diversifying media investment across open internet environments reduces dependency on any single platform's policies, pricing, or algorithm changes.
Supply path optimization is essential for controlling costs and ensuring that ad spend reaches quality inventory through the most efficient routes.
Cross-channel measurement and coordinated campaign management are no longer optional—they are the defining challenge for advertisers operating across a fragmented ecosystem.
If the themes in this article resonate with how you're thinking about your media strategy,get in touch with AI Digital—we're always happy to talk through the challenges of building cross-platform visibility and what a more coordinated approach could look like for your business.
Blind spot
Key issues
Business impact
AI Digital solution
Lack of transparency in AI models
• Platforms own AI models and train on proprietary data • Brands have little visibility into decision-making • "Walled gardens" restrict data access
• Inefficient ad spend • Limited strategic control • Eroded consumer trust • Potential budget mismanagement
Open Garden framework providing: • Complete transparency • DSP-agnostic execution • Cross-platform data & insights
Optimizing ads vs. optimizing impact
• AI excels at short-term metrics but may struggle with brand building • Consumers can detect AI-generated content • Efficiency might come at cost of authenticity
• Short-term gains at expense of brand health • Potential loss of authentic connection • Reduced effectiveness in storytelling
Smart Supply offering: • Human oversight of AI recommendations • Custom KPI alignment beyond clicks • Brand-safe inventory verification
The illusion of personalization
• Segment optimization rebranded as personalization • First-party data infrastructure challenges • Personalization vs. surveillance concerns
• Potential mismatch between promise and reality • Privacy concerns affecting consumer trust • Cost barriers for smaller businesses
Elevate platform features: • Real-time AI + human intelligence • First-party data activation • Ethical personalization strategies
AI-Driven efficiency vs. decision-making
• AI shifting from tool to decision-maker • Black box optimization like Google Performance Max • Human oversight limitations
• Strategic control loss • Difficulty questioning AI outputs • Inability to measure granular impact • Potential brand damage from mistakes
Managed Service with: • Human strategists overseeing AI • Custom KPI optimization • Complete campaign transparency
Fig. 1. Summary of AI blind spots in advertising
Dimension
Walled garden advantage
Walled garden limitation
Strategic impact
Audience access
Massive, engaged user bases
Limited visibility beyond platform
Reach without understanding
Data control
Sophisticated targeting tools
Data remains siloed within platform
Fragmented customer view
Measurement
Detailed in-platform metrics
Inconsistent cross-platform standards
Difficult performance comparison
Intelligence
Platform-specific insights
Limited data portability
Restricted strategic learning
Optimization
Powerful automated tools
Black-box algorithms
Reduced marketer control
Fig. 2. Strategic trade-offs in walled garden advertising.
Core issue
Platform priority
Walled garden limitation
Real-world example
Attribution opacity
Claiming maximum credit for conversions
Limited visibility into true conversion paths
Meta and TikTok's conflicting attribution models after iOS privacy updates
Data restrictions
Maintaining proprietary data control
Inability to combine platform data with other sources
Amazon DSP's limitations on detailed performance data exports
Cross-channel blindspots
Keeping advertisers within ecosystem
Fragmented view of customer journey
YouTube/DV360 campaigns lacking integration with non-Google platforms
Black box algorithms
Optimizing for platform revenue
Reduced control over campaign execution
Self-serve platforms using opaque ML models with little advertiser input
Performance reporting
Presenting platform in best light
Discrepancies between platform-reported and independently measured results
Consistently higher performance metrics in platform reports vs. third-party measurement
Fig. 1. The Walled garden misalignment: Platform interests vs. advertiser needs.
Key dimension
Challenge
Strategic imperative
ROAS volatility
Softer returns across digital channels
Shift from soft KPIs to measurable revenue impact
Media planning
Static plans no longer effective
Develop agile, modular approaches adaptable to changing conditions
Brand/performance
Traditional division dissolving
Create full-funnel strategies balancing long-term equity with short-term conversion
Capability
Key features
Benefits
Performance data
Elevate forecasting tool
• Vertical-specific insights • Historical data from past economic turbulence • "Cascade planning" functionality • Real-time adaptation
• Provides agility to adjust campaign strategy based on performance • Shows which media channels work best to drive efficient and effective performance • Confident budget reallocation • Reduces reaction time to market shifts
• Dataset from 10,000+ campaigns • Cuts response time from weeks to minutes
• Reaches people most likely to buy • Avoids wasted impressions and budgets on poor-performing placements • Context-aligned messaging
• 25+ billion bid requests analyzed daily • 18% improvement in working media efficiency • 26% increase in engagement during recessions
Full-funnel accountability
• Links awareness campaigns to lower funnel outcomes • Tests if ads actually drive new business • Measures brand perception changes • "Ask Elevate" AI Chat Assistant
• Upper-funnel to outcome connection • Sentiment shift tracking • Personalized messaging • Helps balance immediate sales vs. long-term brand building
• Natural language data queries • True business impact measurement
Open Garden approach
• Cross-platform and channel planning • Not locked into specific platforms • Unified cross-platform reach • Shows exactly where money is spent
• Reduces complexity across channels • Performance-based ad placement • Rapid budget reallocation • Eliminates platform-specific commitments and provides platform-based optimization and agility
• Coverage across all inventory sources • Provides full visibility into spending • Avoids the inability to pivot across platform as you’re not in a singular platform
Fig. 1. How AI Digital helps during economic uncertainty.
Trend
What it means for marketers
Supply & demand lines are blurring
Platforms from Google (P-Max) to Microsoft are merging optimization and inventory in one opaque box. Expect more bundled “best available” media where the algorithm, not the trader, decides channel and publisher mix.
Walled gardens get taller
Microsoft’s O&O set now spans Bing, Xbox, Outlook, Edge and LinkedIn, which just launched revenue-sharing video programs to lure creators and ad dollars. (Business Insider)
Retail & commerce media shape strategy
Microsoft’s Curate lets retailers and data owners package first-party segments, an echo of Amazon’s and Walmart’s approaches. Agencies must master seller-defined audiences as well as buyer-side tactics.
AI oversight becomes critical
Closed AI bidding means fewer levers for traders. Independent verification, incrementality testing and commercial guardrails rise in importance.
Fig. 1. Platform trends and their implications.
Metric
Connected TV (CTV)
Linear TV
Video Completion Rate
94.5%
70%
Purchase Rate After Ad
23%
12%
Ad Attention Rate
57% (prefer CTV ads)
54.5%
Viewer Reach (U.S.)
85% of households
228 million viewers
Retail Media Trends 2025
Access Complete consumer behaviour analyses and competitor benchmarks.
Identify and categorize audience groups based on behaviors, preferences, and characteristics
Michaels Stores: Implemented a genAI platform that increased email personalization from 20% to 95%, leading to a 41% boost in SMS click through rates and a 25% increase in engagement.
Estée Lauder: Partnered with Google Cloud to leverage genAI technologies for real-time consumer feedback monitoring and analyzing consumer sentiment across various channels.
High
Medium
Automated ad campaigns
Automate ad creation, placement, and optimization across various platforms
Showmax: Partnered with AI firms toautomate ad creation and testing, reducing production time by 70% while streamlining their quality assurance process.
Headway: Employed AI tools for ad creation and optimization, boosting performance by 40% and reaching 3.3 billion impressions while incorporating AI-generated content in 20% of their paid campaigns.
High
High
Brand sentiment tracking
Monitor and analyze public opinion about a brand across multiple channels in real time
L’Oréal: Analyzed millions of online comments, images, and videos to identify potential product innovation opportunities, effectively tracking brand sentiment and consumer trends.
Kellogg Company: Used AI to scan trending recipes featuring cereal, leveraging this data to launch targeted social campaigns that capitalize on positive brand sentiment and culinary trends.
High
Low
Campaign strategy optimization
Analyze data to predict optimal campaign approaches, channels, and timing
DoorDash: Leveraged Google’s AI-powered Demand Gen tool, which boosted its conversion rate by 15 times and improved cost per action efficiency by 50% compared with previous campaigns.
Kitsch: Employed Meta’s Advantage+ shopping campaigns with AI-powered tools to optimize campaigns, identifying and delivering top-performing ads to high-value consumers.
High
High
Content strategy
Generate content ideas, predict performance, and optimize distribution strategies
JPMorgan Chase: Collaborated with Persado to develop LLMs for marketing copy, achieving up to 450% higher clickthrough rates compared with human-written ads in pilot tests.
Hotel Chocolat: Employed genAI for concept development and production of its Velvetiser TV ad, which earned the highest-ever System1 score for adomestic appliance commercial.
High
High
Personalization strategy development
Create tailored messaging and experiences for consumers at scale
Stitch Fix: Uses genAI to help stylists interpret customer feedback and provide product recommendations, effectively personalizing shopping experiences.
Instacart: Uses genAI to offer customers personalized recipes, mealplanning ideas, and shopping lists based on individual preferences and habits.
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Questions? We have answers
What is the open web definition in digital advertising?
The open web definition in digital advertising refers to the network of independent websites, apps, streaming environments, and publisher-owned properties where ad inventory can be bought through interoperable ad tech rather than within a single closed platform.
How is the open internet different from walled gardens?
The open internet is a distributed ecosystem of independent websites, apps, and publishers where advertising runs through open marketplaces and programmatic infrastructure. Walled gardens are closed environments—like Google, Meta, and Amazon—where a single platform controls inventory, data, measurement, and reporting. The core difference is structural: the open internet offers transparency and flexibility across multiple providers, while walled gardens offer convenience within a single, controlled system.
What does open web meaning actually imply for advertisers?
In practice, open web goes beyond “the internet outside big platforms.” For advertisers, it describes a media environment with more supply diversity, more flexibility in buying, and more room for independent measurement—though it also comes with more operational complexity.
What are examples of the open internet?
Examples include independent news websites, content publishers, mobile apps not owned by major platforms, podcast networks, CTV apps and streaming services that sell inventory through open exchanges, and any digital property where advertising is available through programmatic platforms rather than a single closed ecosystem.
What is the open internet ecosystem made up of?
The open internet ecosystem includes publishers, apps, SSPs, ad exchanges, DSPs, data providers, identity partners, and measurement tools. Together, these players make it possible for advertisers to access inventory across many independent environments instead of relying on one platform owner.
What is open web advertising?
Open web advertising is the practice of running campaigns across independent digital properties using programmatic or direct buying methods outside closed ecosystems such as major social or search platforms. It can include display, video, CTV, audio, mobile app, and other formats.
What is programmatic open internet advertising?
Programmatic open internet advertising refers to the automated buying and selling of ad inventory across the open internet using DSPs, SSPs, exchanges, and related tools. It allows advertisers to reach audiences across many publisher environments while managing bids, targeting, and optimization at scale.
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