XR Extreme Reach released findings from its first-ever State of Ad Ops study on June 22, 2026, painting a picture of an ad production system under measurable strain: marketers are producing more content across more platforms than ever before, budgets are breaking at scale, and a large share of finished creative never runs.
The volume problem
The numbers that open the XR report are blunt. According to XR, 81% of the 400+ marketers and creatives surveyed say content production has increased from just a year ago. Seventy percent say they are producing more ad content across more formats with fewer resources. Yet only 30% believe their resources are keeping pace with demand.
The survey, fielded in May 2026 by research firm MX8 Labs on behalf of XR, covered respondents in the United States and United Kingdom across full-service agencies, media agencies, boutique shops, creative production agencies, and national brands. The breadth of the sample matters: this is not a single-category or single-market reading of the situation.
Agencies, in particular, are absorbing the pressure from clients who want more content without proportional budget increases. Full-service agencies are the hardest hit segment in the data, with 48% scaling back creative scope "often" or "very often" - compared to just 21% of brand-side respondents. Nearly everyone surveyed, 74%, admitted to scaling back creative at least sometimes.
Budgets and the confidence gap
The report identifies a striking disconnect between how marketers perceive their financial controls and how those controls actually perform. According to XR, 92% of respondents described their visibility into production-related costs throughout a campaign lifecycle as "good" or "excellent." Eighty-four percent reported strong alignment between their creative and finance teams.
The actual outcomes tell a different story. Seventy percent of marketers report going over budget at least some of the time. For brands, the leading causes are scope creep and unplanned revisions or reshoots. Agencies, meanwhile, point to shifting platform and channel requirements as a major contributor to overages.
That gap - 92% feeling confident about cost visibility while 70% regularly exceed budgets - suggests measurement perception and operational reality are substantially out of sync.
Where campaigns get stuck
Budget approvals are the single biggest bottleneck, cited by 46% of respondents. Creative concepting ranks second at 38%. Asset versioning is third overall at 32% - but it is the number one bottleneck specifically for brand marketers, who are handling versioning, resizing, and adaptation in-house at a 58% rate, according to XR's findings.
The approvals problem is not just about money. Legal sign-off, internal handoffs, version creation, and platform spec compliance all introduce friction between a finished concept and an actual live campaign. According to XR, 98% of respondents admit to launching campaigns late - a figure that reframes "late launch" as an industry norm rather than an exception.
Wasted creative
Perhaps the starkest finding in the report concerns asset utilization. According to XR, more than half of all marketers admit to using less than 70% of the creative assets they produce. Eighteen percent use less than half of what they make. Only 8% use 100%.
The reasons are varied. Campaign direction changes after production account for 44% of unused assets. Asset underperformance in testing accounts for 33%. Budget reallocation is cited by 29%. Technical specs that do not meet platform requirements - building creative to the wrong dimensions, format, or file type for the intended placement - account for 24%. Timing failures, where the asset misses a campaign or promotional window, account for another 24%.
That last category has a direct connection to the bottleneck data. When approvals, versioning, and handoffs slow the pipeline, campaigns can miss the windows they were built for.
One commercial director quoted anonymously in the report described spending a year on a project for a major tech brand, only for the client to decide not to use it. According to the report, the same client returned four years later with the same brief, and the outcome was identical.
Where brands spend versus where they work
The report captures a notable divergence between where creative time goes and where budgets flow. According to XR, 84% of creative resource time is devoted to paid social media. CTV ranks third for time and effort. Yet when it comes to investment priorities for brands, the order shifts: podcasts rank first, followed by linear TV and then CTV.
Only 39% of respondents produce ad content for audio and podcasts. But podcasts top the budget priority list for every segment surveyed - a gap the report identifies as the central tension in channel investment for 2026. Podcast advertising grew 32% year-on-year in Q4 2025, a trajectory that helps explain why the channel is drawing attention even from production teams that have not fully committed to it.
For full-service agencies, linear TV still anchors the creative priority list, followed by podcasts and CTV. That reflects the continuing weight of national brand budgets, where high-production-value television spots remain a substantial share of the workload.
The in-house divide
The report includes a detailed breakdown of how creative work is divided between internal teams and agency partners. According to XR, brands are retaining early-stage and high-volume tasks: 58% handle ad versioning, resizing, and adaptation in-house; 51% manage social content internally; and 44% produce branded content themselves.
On the agency side, the work that flows outward tends to require deeper technical or production expertise. According to XR, 51% of brands rely on agency partners for post-production, VFX, and finishing. Forty-four percent depend on agencies for animation and motion graphics. Forty percent turn to agencies for full production involving cast and crew.
XR CMO Graham McKenna described the pattern this way: "The in-house agency model has advanced significantly just in the last few years. Brands have moved well beyond handling basic creative tasks and are increasingly taking on work that requires sophisticated operational expertise. But our findings make clear that agency partnerships remain essential for the work that demands specialized craft, technical execution and finishing capabilities. Even those with robust in-house studios still rely on agency partners for some of their most complex, high-value work."
That boundary - where in-house ends and agency begins - is an active operational question at most organizations. Former Extreme Reach CEO Louisa Wong, now leading ad operations platform MINT, described a similar inflection in February 2026, noting that brands and agencies urgently need solutions that reduce complexity, increase transparency and governance, and deliver measurable ROI in day-to-day operations.
AI enters the workflow
Eighty-eight percent of survey respondents say they are actively using or piloting AI in advertising production, with nearly half using it daily. The breakdown by organization type reveals significant variation in how deeply AI has penetrated different parts of the industry.
Full-service agencies are the deepest adopters: 62% use AI daily, applying it to scale VFX capabilities, ad testing, and storyboarding. Production companies follow, with 79% actively using or piloting AI tools for specific projects. National and global brands sit at 42% daily usage, focused on accelerating campaign brief writing, image creation, scripting, and voiceover generation. Media agencies are the least active group, with 36% still using AI primarily for experimentation.
The top AI use cases across all respondents are VFX and compositing at 45%, performance analysis and creative testing at 44%, and image creation at 44%. Video and motion generation follow at 42%, with scripting and copywriting at 41%, and ad versioning and adaptation at 38%.
Orlee Tatarka, Head of Production at Wieden+Kennedy, was quoted in XR's shots Magazine publication in 2026: "There's been a lot of fear of AI, but in reality, it's helping us move faster, be more efficient, and improve what we're already good at."
The primary business objective for AI deployment is creative improvement or personalization, cited by 41% of respondents. Speed to market ranks second at 38%. Cost reduction - often the most-cited driver in public narratives about AI adoption - ranks a distant third at 23%.
Synthetic talent and digital replicas
A separate thread in the report concerns the use of AI-generated performers. According to XR, 26% of respondents are already using AI digital replicas - AI-generated or modified performances tied to a real performer - and 22% are using AI synthetic talent, defined as AI performers with no connection to a real person.
Full-service agencies lead synthetic talent adoption at 31%, signaling greater comfort with AI in creative workflows. Brands are more cautious. The report notes that as AI moves deeper into production, governance becomes the next challenge: ensuring that rights, approvals, consent, and compensation keep pace with creative capability. XR recently expanded its Celebrity Pay platform to support payments for digital replica and synthetic performers under the new SAG-AFTRA contract.
XR itself is launching a next-generation advertising operations platform alongside the research, providing brands and agencies with oversight into ad production costs, asset delivery, and in-market usage. The platform covers end-to-end production tracking from creative briefs through to delivery, centralized cost management, and ad delivery visibility that connects spend on an asset to how it performs in market.
According to XR, the company processes over $1.3 billion in annual celebrity payments in advertising and manages more than 5 million ad deliveries across 45 countries. The firm has operated as a creative infrastructure platform since the 1990s, when it was founded as an advertising delivery and management company.
Context for the marketing community
The findings land at a moment when the structural pressure on creative operations is being driven from multiple directions simultaneously. AI agents are entering the buying layer of programmatic advertising, compressing timelines and raising expectations for campaign speed. Format proliferation - across CTV, FAST channels, social, audio, and emerging AI surfaces - has extended the versioning burden on production teams. And REI's publicly documented case of an AI tool modifying a product image without explicit approval illustrated the brand risk that can emerge when creative governance does not keep pace with platform automation.
The XR data adds industry-wide measurement to what has often been anecdotal in conversations about creative operations. Budget overruns, late launches, and wasted assets are not outlier events. They are, according to the survey, the default experience for the majority of marketing organizations.
Timeline
- May 2026 - XR commissions MX8 Labs to field the State of Ad Ops survey across 400+ US and UK marketers
- June 22, 2026 - XR Extreme Reach releases initial in-housing findings from the State of Ad Ops study, focusing on the divide between in-house and agency workloads
- June 22, 2026 - XR announces launch of its next-generation advertising operations platform alongside the research
- June 28, 2026 - Full State of Ad Ops report published, covering production volume, budget management, bottlenecks, asset utilization, channel investment, AI adoption, and synthetic talent usage
Related PPC Land coverage
- Former Extreme Reach CEO takes MINT's helm as advertising operations hit breaking point - Louisa Wong, who led XR as CEO through September 2024, moved to MINT in January 2026 to address the same operational pressures the XR study documents.
- Agentic ad tech tries to take over the buying layer as AI search budgets surge - Covers how AI agents are reshaping campaign infrastructure, providing context for how production bottlenecks interact with automated buying systems.
- REI's AI bike ad fiasco reveals a Meta auto-enrollment setting brands missed - A documented case of platform AI modifying brand creative without explicit advertiser approval, illustrating the governance risk the XR study flags.
- Podcast ad spending hits 32% growth but you won't believe what's driving it - Q4 2025 Magellan AI data showing the channel growth that explains why podcasts top brand budget priorities despite relatively low production commitment.
- TVSquared partners with Extreme Reach (ER) to measure TV content served across ad-supported OTT - An earlier integration showing XR's role in cross-platform TV ad delivery measurement before the company's broader platform expansion.
Summary
Who: XR Extreme Reach, a New York-based advertising operations platform that processes over $1.3 billion in annual celebrity payments and manages more than 5 million ad deliveries across 45 countries, in partnership with research firm MX8 Labs.
What: The XR State of Ad Ops report - the first industry-wide study of ad creative production and marketing operations - based on a survey of over 400 marketers across brands, agencies, and production companies. Key findings: 70% of marketers break budgets, 98% launch campaigns late, 81% are producing more content than a year ago, and more than half use less than 70% of the creative assets they produce.
When: The survey was fielded in May 2026. Initial in-housing findings were released on June 22, 2026. The full report covers AI adoption at 88% of respondents, production bottlenecks, channel investment priorities, and the emergence of synthetic talent.
Where: The survey covered marketers in the United States and United Kingdom. XR is headquartered in New York with offices across North America, Asia-Pacific, Europe, and Latin America.
Why: The report documents a structural mismatch in the advertising production industry: content demand is growing faster than resources and operational systems can support, while AI adoption is accelerating but primarily for speed and output rather than cost reduction. The findings have direct implications for how brands and agencies structure their creative workflows, divide work between in-house teams and external partners, and manage rights, governance, and accountability as AI-generated performers enter production pipelines.
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