The Supply-Side Renaissance: How Supply Intelligence Navigates Programmatic's AI Evolution

Gabriella Aversa

October 15, 2025

10

minutes read

After two days at Programmatic I/O NYC 2025, the industry's flagship conference for programmatic media and marketing, one thing became crystal clear: the programmatic ecosystem is experiencing a fundamental power shift. The long reign of demand-side dominance is ending, and supply-side innovation is taking center stage. For organizations investing in intelligent supply optimization, this shift validates the importance of real performance over promises.

Table of contents

What follows draws from two days of sessions and conversations, backed by industry research that demonstrates how supply intelligence is reshaping programmatic's competitive dynamics—and which approaches will capture the value others are leaving behind.

TL;DR Key takeaways at a glance:

  • Supply-side innovation is now the primary lever for performance, not a support act.
  • “Zombie” deal IDs drain efficiency—continuous path optimization keeps them out.
  • Standards (transaction IDs, LEAP, OpenRTB extensions, ads.txt/sellers.json) are the backbone of cleaner supply chains.
  • AI matters when it proves lift against real KPIs, not when it’s just a label.
  • CTV’s growth—especially live events—rewards platforms with real-time, low-latency infrastructure.

Supply intelligence: the new competitive frontier

The conference revealed that successful programmatic strategies now require sophisticated supply-side control. SSPs are evolving from passive inventory pipes to active optimization partners, while data and decisioning power migrate back to the supply side. This isn't just header bidding 2.0—it's a complete reimagining of how inventory flows through the ecosystem.

Jounce Media's presentation coined the term "zombie supply chains," which resonated throughout the conference. These aren't horror movie creatures—they're the thousands of deal IDs sitting dormant in DSPs, consuming resources without delivering results. These unoptimized paths drain efficiency and create the fragmented, inefficient marketplace we see today. Effective supply intelligence prevents these zombie chains from forming by continuously optimizing every path, ensuring deals stay alive and performing.

The migration of intelligence to the supply side reflects a broader recognition: proximity to inventory creates advantage. Publishers possess unique signals about their audiences, content context, and user behavior that become exponentially more valuable when paired with machine learning models trained on years of performance data. Platforms that can synthesize this proprietary information with real-time bidding dynamics deliver outcomes that generalist approaches cannot match.

Standards build cleaner supply chains

The industry is embracing standardization as the path to cleaner, more efficient supply chains. IAB Tech Lab's frameworks like Transaction IDs, LEAP APIs for live events, and OpenRTB extensions create a unified approach that benefits everyone. Publishers are layering supply intelligence onto their deals through metadata and direct integrations, creating more value at the source.

The push for standardization gained urgency in 2025 as 87% of brands, agencies, and DSPs reported actively implementing SPO strategies, citing brand safety, reduced fraud, and improved KPIs as primary motivations. With approximately 60% of mobile and 35% of desktop impressions now ID-free according to Comscore data presented at the conference, the need for alternative signals has never been more acute.

Leading platforms are adopting these standardization efforts while maintaining agnostic approaches. Clean, direct paths are becoming the new currency of trust in programmatic, and cross-SSP visibility ensures organizations can identify and activate the cleanest paths regardless of which standard emerges victorious. Tools like ads.txt and sellers.json have evolved from optional transparency measures to essential infrastructure. Advanced SPO implementations demonstrate measurable impact: Jellyfish's proprietary analysis methodology achieved a 27% reduction in viewable eCPM for campaigns using their optimization approach.

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AI's reality check: from buzzword to business value

Here's what nobody wants to admit: AI dominated every conversation at the conference, yet most presentations offered little substance beyond the buzzword. The industry is in an innovation phase, clamoring for AI solutions while the actual applications remain nascent. Gartner's progression timeline revealed the truth—most platforms operate at the basic "Tool" stage (simple automation), while few have reached the "Agent" stage (autonomous decision-making).

This gap between AI hype and reality creates opportunity for platforms that have been refining machine learning models over years of real-world application. As Dave Colford of Chief Marketer Network noted during day one, "The future will be propelled by AI," but the critical distinction lies in identifying how AI delivers measurable impact—from campaign optimization to creative personalization—rather than getting distracted by impressive-sounding but unproven tools.

The winners will be those that deliver measurable performance improvements through AI, not just marketing claims. Organizations need expertise to distinguish genuine innovation from noise, particularly as vendors rush to slap "AI-powered" labels on existing technology. The conference made clear that success requires disciplined implementation strategies balancing short-term wins with long-term infrastructure building.

Consider the numbers: while programmatic ad spending continues its explosive growth trajectory, global programmatic is expected to account for 90% of digital display ad spending by 2026. Yet this dominance brings heightened scrutiny. Advertisers demand proof that AI-driven optimization actually works, with concrete metrics showing improved CPMs, reduced invalid traffic, and better audience matching. Platforms built on years of proprietary performance data—not hastily assembled AI wrappers—will capture the value as the market matures.

SPO evolves into supply intelligence

The conference made clear that SPO 1.0, focused solely on reducing hops and fees, has outgrown itself. Today's winners focus on the "smartest path," not the cheapest one. The distinction matters enormously in an environment where only 51% of advertiser spend reaches publishers, with 15% completely unattributable—representing one-third of all supply chain costs. Optimization that focuses purely on cost reduction without considering quality and outcomes simply redistributes waste rather than eliminating it.

With the majority of impressions now ID-free, the industry needs intelligent solutions that recover signal quality, not just reduce costs. This requires a more sophisticated approach than simply eliminating supply path hops. Publishers working with leading platforms report average reductions of 50% in unqualified traffic and 20% CPM savings—metrics achieved through intelligent, pre-bid optimization powered by years of proprietary performance data, not through crude path reduction.

The evolution from cost-focused SPO to outcome-oriented supply intelligence reflects the industry's maturation. Early SPO implementations concentrated on transparency and fee reduction. Today's advanced implementations leverage machine learning to predict which supply paths will deliver the best campaign outcomes before bids are placed. This predictive capability, built on massive datasets of historical performance, separates true supply intelligence from basic path optimization.

From curation to intelligence

The distinction between curation and intelligence emerged as a crucial theme. The market is finally defining true supply optimization: pre-bid, source-level intelligence that adds measurable value. A panel of experts, bringing together agency, data, and curation expertise, demonstrated how specialized knowledge outperforms generalist approaches. Their presentation represented the evolution of intelligent supply optimization.

The key metrics are clear: significant reductions in wasted bid requests, improvements in CPM, and measurable performance gains. Platforms that consistently exceed these benchmarks focus on intelligence, not intermediation. They differentiate by answering a single question before every bid: "Will this impression deliver value for this campaign?" Simple curation cannot answer that question. Only platforms with deep performance histories, sophisticated models, and real-time decisioning can.

This evolution matters because the programmatic supply chain remains bloated. As mentioned, up to 15% of every programmatic dollar is lost to hidden fees, redundant tech layers, and inefficient supply routes. True supply intelligence identifies these inefficiencies and routes around them automatically, without requiring constant manual intervention from trading teams. The platforms delivering on this promise report client retention rates that speak volumes about the value of genuine intelligence over superficial optimization.

CTV's opportunity in live events and streaming growth

Perhaps the most honest session addressed CTV's uncomfortable truth: most CTV SPO is just repackaged PMPs. With 90% of streaming impressions coming from the top 10 publishers (per Tatari), the real opportunity isn't in aggregation—it's in intelligence and measurement.

Live events represent the frontier. The technical requirements—real-time APIs, concurrent stream management, pre-fetching capabilities—demand sophisticated infrastructure that traditional SPO approaches cannot provide. The opportunity is substantial: a resurgence in live events and sports programming helped CTV rebound with 16% year-over-year growth in 2024. Real-time optimization engines and cross-SSP visibility are uniquely positioned to help organizations capture the $2-4 billion opportunity mentioned at the conference.

The Jake Paul vs. Mike Tyson fight broke records with 65 million concurrent streams, demonstrating the scale live streaming can achieve. Yet monetizing these massive, simultaneous audiences requires technology that can handle bid density, latency sensitivity, and rapid scaling—capabilities that separate purpose-built solutions from retrofitted platforms.

Streaming wars are shifting focus. While the early 2020s emphasized original content, 2025 belongs to live sports streaming. Every major platform has entered the space, from Amazon Prime Video to Netflix. For programmatic platforms, this shift presents both challenge and opportunity. Those with the infrastructure to handle live event complexity—concurrent stream management, real-time decisioning, sub-second latency requirements—will capture disproportionate value as advertisers allocate budgets toward premium live inventory.

The path forward

Programmatic I/O 2025 confirmed a fundamental truth: the future belongs to those who can deliver genuine supply intelligence, not just claim it. As the industry moves beyond AI buzzwords toward real implementation, organizations need proven technology, measurable results, and expertise to guide them through this evolution.

The supply-side renaissance isn't coming—it's here. And for those ready to embrace intelligent optimization over simple efficiency, the opportunities have never been greater. With 56% of marketers planning to increase OTT/CTV budgets and roughly 75% of CTV transactions occurring programmatically, the edge belongs to platforms that pair strong machine learning with end-to-end supply visibility.

The conference left attendees with a clear mandate: implement supply intelligence now or let competitors capture the value you’re creating. In a market compounding this fast, the cost of delay grows daily. Organizations that move with intent—backed by data, not slogans—will set the pace for the next era of programmatic.

If you’d like to pressure-test these insights against your stack—or see what a targeted supply-intelligence rollout would look like for your plan—let’s talk. AI Digital can audit your supply path, size the upside, and build a phased roadmap to results.

Inefficiency

Description

Use case

Description of use case

Examples of companies using AI

Ease of implementation

Impact

Audience segmentation and insights

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.
Medium
Medium

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