Greg Sherrill, VP of Demand at Magnite, joins AdTech Unfiltered to dig into the current state of programmatic inventory, transparency in fee structures, and smarter supply path optimization strategies.
Greg shares insights on streamlining partnerships, rethinking curation, and balancing performance goals with sustainability efforts. From addressing fragmentation to navigating live sports access to advancing data-driven targeting in a post-cookie landscape, this conversation offers perspective for anyone looking to simplify their programmatic stack and deliver better outcomes.
The 2024 Olympic Games marked a major inflection point in the rise of connected TV advertising.
After a slower year in 2023, the channel exploded in 2024, fueled by the successful monetization of live events—particularly the Olympics—as well as years of sustained investment in content, new ad formats, and user acquisition. Now, CTV ad spend is expected to see double-digit growth through 2029.
For many advertisers, the Games served as a proving ground for the brand visibility and audience engagement that live sports can deliver on CTV. And with streaming platforms racing to secure sports broadcasting rights, live programming is poised to become a central pillar of CTV strategy.
While the broader CTV market is maturing, the live CTV space remains relatively nascent. As marketers look to make smarter media investments, understanding the value of live content, how the ecosystem is evolving, and what it takes to activate effectively will be key.
From engagement, to reach, to relevance, live CTV offers advertisers unique conditions for forging strong connections with audiences in real time.
One of the biggest advantages of advertising on live content lies in viewer mindset. Live content audiences tend to be more focused and emotionally invested in what they have committed to watch at a very specific time. This heightened attention can translate to higher engagement and ad recall.
Live content also allows advertisers to meet audiences where they are. With digital sports viewership now outpacing traditional TV sports viewership, live CTV has become the new home for real-time fan engagement.
And, crucially, live CTV advertising gives brands the opportunity to be part of cultural moments that matter. Tapping into these shared experiences can help brands deepen emotional resonance and reinforce relevance with target audiences.
To make the most of the live CTV advertising opportunity, advertisers need to consider how the marketing funnel is evolving—both within connected TV and across the broader digital landscape.
Historically, CTV (like linear TV) has been viewed as an upper-funnel channel best suited for brand awareness plays. However, as shoppable and interactive formats mature and attribution capabilities improve, CTV is proving to be a conversion powerhouse as well.
Live CTV takes this a step further. Thanks to the heightened attention and engagement it commands, live content can prompt immediate action even more effectively, with ads shown during live programming driving 43% larger average transaction values compared to those shown during non-live environments.
This evolution isn’t limited to CTV. Across the board—from holiday shopping behaviors to the rise of social commerce and commerce media more broadly—the traditional marketing funnel is collapsing. In this context, live CTV’s proven strength in brand awareness and expanding potential for performance makes it well positioned to play a central role in the next era of digital marketing, as full-funnel approaches take center stage.
Driving impact with live CTV requires advertisers to tailor their strategies to the dynamics of the channel.
To start, marketing teams should lean into the relevance of real-time moments and align their creative with specific events—think sports- or regionally-themed ads during live sports events, award-themed ads during award shows, and messaging tailored to the time of day an event takes place. This could also look like leveraging dynamic creative optimization (DCO) to create content based on specific moments within those events.
The right collaborators and integrations are also essential. For example, Disney Live Certified DSPs empower advertisers with the ability to scale and respond to bids on live content in real time, adapt to spikes in live viewership, stay responsive to shifting demand, and more.
From a conversion standpoint, tapping into high-impact formats such as shoppable or interactive ads—like pause ads or ads containing QR codes—can help advertisers take advantage of live CTV’s lower-funnel opportunities.
And, as with any channel, live CTV must be thoughtfully integrated into an omnichannel approach. Pairing it with digital, mobile, and social touchpoints allows for cohesive re-messaging and deeper engagement. For instance, a viewer might see a brand during a live game on TV, then again in a post-game highlight on social, or in a mobile sports app that same evening.
Frequency capping is also key. Because live audiences are highly engaged, repetitive ads can quickly lead to fatigue and negative brand sentiment. Sequencing creative across channels and using tactics like dayparting can ensure brand messages stay fresh and timely throughout the customer journey.
By activating strategies intentionally in these ways, advertisers can craft dynamic, responsive campaigns that meet the moment and move the needle with audiences.
As live content becomes an increasingly central part of the streaming landscape, live CTV offers advertisers a powerful way to capture attention, build relevance, and drive action. By understanding how the channel is evolving and approaching it with strategic creativity and precision, marketers can turn live moments into lasting impact.
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With baseball, football, basketball, and more hitting the live streaming lineup this fall, now’s the time for advertisers to step up to the plate, tackle their biggest challenges, and set themselves up for a slam dunk marketing season. Check out Going Deep on Live Sports Advertising Opportunities to explore how brands can make the most of live sports on CTV and beyond.
In this episode, Ali Mack, VP of AdTech at Experian, joins AdTech Unfiltered to explore how marketers can future-proof their targeting strategies as cookies fade and consumer privacy expectations rise.
Ali sits down with host Noor Naseer to unpack the shift from a single-source identity model to a more flexible, multi-signal approach rooted in cleaner, more organized first-party data. As identity continues to evolve, this episode delivers practical guidance for staying adaptive in a fragmented ecosystem.
Over the last few years, the internet has been flooded with AI-generated content: from bizarre viral imagery like shrimp Jesus, to lifelike dog videos that blur the line between real and synthetic, to fabricated news headlines and disturbingly realistic depictions of violence and tragedy.
Where such content may once have felt fringe or experimental, it has now quickly become mainstream. And while its quality and intent varies widely, the collective impact is clear: It is reshaping what people see, share, and trust online. AI slop has become a defining feature of the digital media landscape, fueled by algorithms that prioritize engagement over authenticity and by bad actors seeking to monetize low-quality content at scale.
As AI slop floods digital spaces, it’s altering audience behavior, skewing performance signals, and complicating efforts around brand safety and media quality. For marketing leaders, navigating this new reality requires more than reactive efforts. It demands a proactive strategy that can adapt to evolving content ecosystems, prioritize brand safety and suitability, and ensure that campaigns continue to deliver meaningful business outcomes.
While AI has introduced powerful efficiencies for advertisers, the growing presence of AI slop has introduced new challenges. And recent data confirms that marketing teams are taking notice: 57% of advertisers now view AI-generated content as a key challenge for the digital advertising ecosystem, and 54% believe it has led to a decline in overall media quality.
“AI slop is diminishing the quality and trustworthiness of digital advertising as a whole,” says Mallory Chaney, VP of Integrated Client Solutions at Basis. “However, it also opens up opportunities for brands to cut through the noise by investing in authentic, differentiated messaging.”
One of the most significant concerns is the impact of AI-generated content on made-for-advertising (MFA) sites. With the widespread availability of gen AI tools, bad actors are increasingly using them to mass-produce low-value content with little to no editorial oversight. In one recent example, more than 200 AI-driven websites impersonating sports news outlets were found blending synthetic content with stolen reporting, creating an illusion of legitimacy while undermining the integrity of the media environment.
And, as evidenced by phenomena like shrimp Jesus, AI slop isn’t limited to MFA sites. It is showing up in nearly every corner of the internet. On Quora and Medium, for example, AI-generated material jumped from 1.77% and 2.06% in 2022 to 37.03% and 38.95% in 2024, respectively. Social media platforms have seen similar patterns, with AI-generated content increasingly filling feeds and recommendation algorithms. The rapid pace of this growth signals that AI-generated content is steadily becoming a widespread and dominant force across the online ecosystem.
Compounding these challenges is the way algorithmic systems reward this content. Social platforms, in particular, often promote low-quality AI slop even if users don’t follow the pages that share it, creating feedback loops that reinforce and scale artificial content. This algorithmic promotion can inflate impression volumes far beyond what that content would naturally earn based on user preference, making it difficult for advertisers to gauge authentic audience interest.
The implications for advertisers are serious. Low-quality AI slop increases brand safety concerns by putting campaigns at risk of running adjacent to misleading, plagiarized, or even harmful content that may not align with a brand’s values. It distorts performance metrics by inflating impressions and engagement on content that may not reflect authentic user demand. It can also contaminate optimization models—if campaigns consistently run against algorithmically amplified but low-quality content, the resulting engagement signals may not accurately represent true audience behavior, leading to flawed optimization decisions. And it wastes media dollars by funneling ad spend into inventory that delivers minimal value—and potentially even harm. These challenges are amplified in today’s climate of economic turbulence, where marketers are under increased pressure to prove the ROI of every dollar spent.
Though the proliferation of AI slop poses many challenges for advertisers, its ability to undermine brand safety at scale presents a growing risk. This is, in large part, because such content is often designed to pass as human-made. As such, detecting AI-generated content requires looking beyond traditional content signals. According to Chaney, performance monitoring can reveal telltale signs of low-quality AI content: unusual URLs, high impression delivery to sites outside campaign parameters, and metrics patterns like high impression volume paired with low click-through rates or elevated bounce rates.
This detection challenge is compounded by the fact that many platforms don’t yet offer advertisers the option to avoid AI-generated content altogether. On YouTube, for example, advertisers can specify the types of video content they want their ads to run alongside—such as avoiding sensitive or graphic categories—but they cannot filter based on how that content was created. As a result, campaigns may run adjacent to synthetic videos that lack editorial oversight, factual grounding, or alignment with brand standards.
To adapt, leading advertisers are evolving to adopt more intelligent, layered approaches that combine pre-bid verification tools, contextual intelligence tools, and curated inventory strategies to both detect and avoid low-quality AI content. “Contextual intelligence engines, in particular, are resilient against AI-generated content because they can understand semantic context rather than just keywords and terms,” says Chaney.
At the same time, many teams are working with partners that monitor supply paths dynamically and identify domains known to misrepresent quality or exploit optimization systems through mass-produced, MFA-style content. “Advertisers are also turning to more premium inventory like private marketplaces and programmatic guaranteed deals, which are generally less susceptible to fraud,” says Chaney. Custom blocklists and curated PMPs can add another layer of protection against low-quality content.
As content creation and monetization methods continue to evolve, teams that embrace this kind of approach will be better equipped to maintain brand integrity without sacrificing scale or efficiency.
As AI slop continues to reshape the media landscape, marketing leaders are under pressure to ensure their teams are prepared—not just to react, but to plan intentionally. Leaders who embrace a cross-functional strategy grounded in adaptability will be well-positioned to both deal with the current challenges and to adjust as the digital media landscape continues to shift.
To ensure their ads aren’t running alongside AI slop, marketing leaders should first assess exposure. Teams should audit recent campaigns for unusual traffic patterns, off-target site delivery, or inflated impression counts tied to weak engagement—common signals of low-quality AI content, according to Chaney.
From there, partner evaluation criteria should evolve. Questions that once focused primarily on brand suitability and safety should now include whether partners can identify AI-generated content, how frequently their detection logic is updated, and how easily their tools integrate with existing tech stacks.
Internally, leaders should align media buyers, brand safety stakeholders, and analytics partners around a shared response plan. This could include establishing clear protocols for identifying AI content and flagging questionable placements. Education also plays a critical role, as teams trained to spot the signs of AI slop are better equipped to escalate concerns. “Continuing to recognize AI-generated content as well as understand both the strengths and limitations of tech will help advertisers to balance available tools with human oversight,” says Chaney. With early investments in processes and training, marketing leaders will be far better prepared as AI-generated content continues to spread—and potentially becomes more difficult to detect.
In a digital media environment shaped increasingly by low-quality AI content, brand safety, performance accuracy, and trust are all on the line. Marketing leaders that adapt now won’t just protect their campaigns—they’ll build trust with audiences and maintain competitiveness in a rapidly transforming digital media landscape.
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Looking for more insights on how AI is transforming digital advertising? We surveyed marketing and advertising professionals from top agencies, brands, and publishers to get a pulse on how teams are using and feel about the technology today, and how it could change things going forward.
What media type offers advertisers access to emotionally-charged audiences and rivals the viewership of tentpole events like the Olympics? In this episode, Rob Christensen, Global EVP at Vevo, joins host Noor Naseer to explore the often-overlooked power of music videos in today’s advertising ecosystem.
Rob unpacks how music intersects with culture, the influence of artist fandoms, and the growing role of nostalgia and platform-specific behaviors in shaping CTV strategies and ad formats. This episode offers a fresh perspective on how music videos are reshaping video advertising and driving deeper audience engagement.
While Ari Paparo may not be the AdTechGod, he’s undeniably a defining voice in the industry—highly visible, well-regarded, and widely followed.
Ari, founder of Marketecture Media and former CEO of Beeswax, is now debuting his first book, Yield: How Google Bought, Built, and Bullied Its Way to Advertising Dominance. Ari joins host Noor Naseer to discuss the book and the impact of storytelling in adtech.
In this episode, Lara Krug, CMO of the Kansas City Chiefs, joins AdTech Unfiltered to break down how one of the NFL’s most iconic franchises approaches marketing in a time of rapid innovation.
From Taylor Swift headlines to immersive fan experiences, Lara huddles up with host Noor Naseer to share how the Chiefs turn big moments into long-term brand equity. Tune in for insights on balancing tradition with innovation, why storytelling drives strategy, and how the team stays culturally relevant while honoring their legacy.
As the first-ever CMO of the Kansas City Chiefs, Lara Krug stepped into a brand with deep roots and high expectations. The team’s longstanding role in the community has made evolution a delicate task. For Krug, the key is using brand history as a filter for new ideas—whether that means exploring emerging media environments or crafting new experiences that still feel unmistakably “Chiefs.”
Rather than treating tradition and innovation as competing forces, her team sees them as interconnected. Legacy provides the foundation; innovation brings it to life in new ways. As Krug puts it, the goal isn’t to replace tradition with innovation, but to build on it. By staying grounded in what fans already love, the team continues to find fresh ways to connect with both new and established audiences.
For fans outside of Kansas City—or even outside the US—the draw to the Chiefs isn’t always the game itself. Often, it’s the culture around it, with audiences across the globe often connecting to the team through player personalities, social content, and community initiatives as much (or more) than stats or standings.
That understanding shapes the team’s global growth efforts, which are built around connecting with fans through emotional and cultural relevance. And with time zones working against live viewership in some areas, visibility across platforms becomes essential, so Krug’s team has worked to expand the brand’s presence beyond live games, creating fan touchpoints through content, partnerships, and off-field moments that don’t rely on kickoff times.
With tight restrictions on paid media, Krug’s team treats organic content as one of its key marketing engines and a powerful way to foster stronger connections. Each platform plays a distinct role, from showcasing players’ personalities on TikTok to spotlighting partnerships on Instagram to offering behind-the-scenes access on Snapchat.
To make the most of organic content, the team leans into stories that reflect the moment, the audience, and the Chiefs’ brand values. The result is a brand built on authenticity and intention—one that meets fans where they are, whether culturally, emotionally, or digitally. By prioritizing creativity, consistency, and cultural relevance, the Chiefs’ content strategy builds deep connection with fans while extending the brand’s reach.
In business, it’s rare to find a single solution that solves multiple problems at once. But when it comes to the greatest challenges marketing executives face today, one underlying issue connects nearly all of them: data.
Fragmented data, poor-quality data, overwhelming amounts of data, and/or a limited ability to extract actionable insights from it exacerbates all of marketing executives’ top pain points—from driving revenue to proving ROI to harnessing the incredible potential of AI.
The good news? By improving the quality, integration, and accessibility of their data, marketers can address all of those pain points at once, creating exponential value.
Read on to learn how challenges related to media fragmentation, visibility, revenue generation, proving ROI, talent effectiveness and retention, and AI adoption are all affected by data problems, and what steps marketing leaders can take to alleviate them.
If data challenges lie at the heart of marketers’ biggest pain points, then media fragmentation lies at the heart of those data challenges. From social media fragmentation to emerging complexity in the search space to the rise of commerce media, marketing efforts are increasingly spread across a growing number of platforms, channels, partners, and tools. This is creating major challenges for marketing organizations, with agency leaders naming siloed/disconnected systems as one of the most urgent issues facing their organizations.
Data fragmentation stemming from those siloed systems makes it difficult to track the customer journey at even a basic level. “When the view of the customer journey is fragmented, it’s difficult to identify quality touchpoints and how they’re working together,” says Lisa Olszewski, VP of Brand Development at Basis. “Which, in turn, makes it difficult to build a smooth and valuable experience for the customer.”
Building that seamless customer experience is crucial to marketing teams’ primary goals: driving revenue, building their brand, and forging trust and lasting connections with target audiences. Fragmentation in media and data doesn’t just complicate customer journey tracking—it sets the stage for many of the other challenges marketing leaders face today.
Data problems make it difficult for marketing executives to drive revenue efficiently—a goal that’s under increasing pressure from all sides.
For marketing leaders at brands, that pressure is compounded by growing skepticism around the CMO role itself. Some companies are experimenting with eliminating the role altogether, while others are turning to fractional CMOs. And even for those retaining full-time CMOs, the role is evolving. “CMOs today aren’t just expected to be brand stewards as they were in years past—the role is now blended with finance and tech,” says Grace Briscoe, EVP of Client Development at Basis. “Their biggest challenge, and objective, is to shift the view of marketing from a cost center to a profit driver.”
Agency leaders face similar demands, as rising costs and shrinking profit margins increase the need to demonstrate measurable business impact. At the same time, as economic volatility persists, marketing budgets are under greater scrutiny, with many agency and brand leaders expected to do more with less.
Amidst all this pressure, fragmented data hinders marketing teams from driving revenue. Specifically, it slows their ability to evaluate the effectiveness of investments across channels and make real-time adjustments. Even when raw data is technically accessible, it doesn’t always lead to meaningful insight due to fragmentation or a lack of tools or skills. “Most leaders have visibility into campaign data, but they might be lacking the strategic context for what story those data points are telling, and how it’s actually moving the business forward,” says Olszewski.
The manual effort required to stitch together data from disparate sources not only causes delays, but also raises the risk of human error, further limiting a team’s ability to act strategically. What’s more, this lack of visibility makes it challenging to connect media investments to business outcomes in a cohesive, narrative-driven way. A recent survey of marketing leaders found that the top activity they struggle to implement regularly is demonstrating how marketing activities translate into financial outcomes.
This difficulty to prove ROI has serious consequences. “Gone are the days when awareness-driving marketing investments are seen as a positive, long-term investment for a brand,” says Olszewski. “Everything needs to show some level of return with CMOs now reporting into CFOs, shareholders, and finance-minded CEOs, all of whom are scrutinizing every dollar.” Fragmented and inconsistent data makes it harder to show clear returns on marketing budgets. This not only weakens the case for future investment but, for agency leaders, can also strain already delicate client relationships.
In short, without unified, organized, and accessible data, it becomes difficult not only to understand performance and drive revenue, but to prove out even the strongest results. This makes it harder to earn internal alignment, external confidence, and continued investment.
Data fragmentation is also compounding the pressures facing hands-on-keyboard marketers. Team members typically spend hours manually pulling information from different sources and piecing it together in spreadsheets, which creates costly operational inefficiencies and raises the risk of human error.
This fragmentation has increased the difficulty of digital advertising work, with a growing majority of agency professionals reporting that their work has grown more difficult in just the past two years. This increase in complexity affects not just employee efficiency, but job satisfaction and fulfillment: When the skills of top marketing talent are underutilized, they’re less likely to stay, making data not only a performance issue, but a retention risk as well.
“If you’re finding the kind of talent that can pull insights from data and craft valuable stories around those insights, they do not want to spend six hours of their day cutting and pasting in spreadsheets to compile reports,” says Briscoe.
Finally, data issues are standing in the way of another top marketing priority: maximizing AI. In fact, 58% of industry professionals cite data quality and accessibility as major barriers to successful AI adoption.
When data is scattered across multiple systems, it's difficult to feed it into AI models in a usable form. And when that data has been stitched together manually, human error can lead to inaccurate inputs and, ultimately, unreliable outputs.
While the industry is still grappling with important questions around how to use AI in ways that safeguard data security and privacy, it’s clear that the teams that have unified and streamlined their data processes will be the ones best positioned to harness AI’s full potential.
“AI’s ability to rapidly aggregate and analyze huge data sets has the potential to give marketing organizations a wild advantage right now,” says Briscoe.
When marketing teams embrace technology that unifies and streamlines their data, they can alleviate nearly all of their most pressing pain points.
With unified data, visibility improves—not just into campaign performance, but into the stories that data tells. Revenue-driving opportunities become easier to spot and act on. The impact of marketing is easier to measure and communicate. Teams can spend less time wrangling spreadsheets, ensuring their time is spent more efficiently and more rewardingly. And as AI transforms the marketing landscape, unified, high-quality data will separate teams who can leverage it to drive real impact from those who can’t.
In these ways, by leveling up their teams’ approach to data, marketing leaders can turn today’s challenges into tomorrow’s competitive edge.
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Curious to learn more about how leading brands, agencies, and publishers are approaching AI? Our report, AI and the Future of Marketing, explores how industry professionals feel about the technology today how they expect it to transform the space moving forward.
In this episode, Tameka Kee, SVP of Programming & Operations at the Coalition for Innovative Media Measurement (CIMM), joins Adtech Unfiltered to unpack the state of media measurement.
From CTV to attention metrics and synthetic data to privacy compliance, Tameka explains how CIMM brings together platforms, publishers, agencies, and more to tackle the industry's most pressing challenges. Listen in for expert insights around why last-touch attribution is outdated, how value exchange must drive data usage, and why nerds run the show when it comes to measurement.
