Technology
Basis Platform
Advertising Operating System
Communication Portal
Intelligent Collaboration
All Channel Activation
Activate Media on Every Channel
Consulting
Resources
Agentic AI is rapidly emerging as the next frontier in marketing technology. The global market is forecast to surge from $7.55 billion in 2025 to a whopping $199.05 billion by 2034—a compound annual growth rate (CAGR) of 43.84%.
While interest and momentum among marketers is building, adoption remains tentative, with only 20% currently deploying AI agents for marketing work.
Understanding what’s changing, what’s coming, and how to prepare for an agentic AI-powered future is essential for marketers looking to navigate these shifts effectively.
Key Takeaways:
Agentic AI represents a fundamental shift for marketers. These autonomous systems differ from the assistive AI many teams use today by handling complete workflows without constant human intervention. This evolution to proactive execution is poised to transform how marketers operate in three major ways: driving significant efficiency and ROI gains, reshaping marketing roles from execution to oversight, and creating an entirely new agentic web where AI systems interact alongside humans.
One of agentic AI’s biggest selling points for marketers is its ability to drive significant efficiency and effectiveness gains. Through capabilities like autonomous campaign optimization across channels, real-time personalization at scale, and intelligent lead qualification, agentic AI can help marketers achieve better results with less manual effort.
Use of the technology across marketing and sales is forecast to fuel over 60% of agentic AI’s overall value across the enterprise. Early deployments for task automation and human assistance can boost company-wide productivity by 3 to 5% annually, with gains potentially reaching 10% or higher as systems evolve to handle more sophisticated workflows.
Today, most marketers primarily use AI as assistive tools—systems that respond to prompts but need human guidance for each task.
Agentic AI is poised to change how marketing teams work due to its ability to autonomously complete multi-stage processes in service of key goals. Rather than simply generating a single ad variant or analyzing one dataset, AI agents will be able to handle entire workflows end to end. For example, within the realm of programmatic advertising, agentic AI will eventually streamline entire campaign processes from start to finish. Beyond media buying, AI agents are expected to take on specialized roles like strategy assistants that generate and test campaign ideas, data analysts that surface actionable insights, and customer engagement coordinators that manage personalized communications across channels.
As agentic AI expands across marketing functions, the marketer’s role will evolve from hands-on execution to managing AI agents that complete tasks autonomously.
As agentic AI transforms how marketers work, it will also alter consumer behavior.
Consumers are expected to increasingly adopt AI agents to handle complex spending decisions such as booking vacations, planning weddings, and comparing financial products. These behavioral shifts will further disrupt the search landscape, with experts saying that many consumers will eventually delegate entire research and decision-making processes to AI agents.
This shift signals a new era for the internet, where the web will be made up not only of the traditional human-facing web, but also an agentic web where AI systems communicate, evaluate, and transact autonomously. Marketers will need to evolve to ensure discoverability across both layers, optimizing for algorithmic systems while maintaining the creative storytelling that resonates with humans.
While agentic AI promises significant transformation, most marketing teams are still in the early stages of adoption. Successfully integrating this technology requires four key steps: identifying high-impact opportunities for AI agents, preparing data infrastructure, managing organizational change effectively, and optimizing for both human and agentic web discovery.
To harness the efficiency and effectiveness benefits of agentic AI, marketing teams must start by identifying the marketing functions where the technology can make the most impact. This involves auditing workflows for repetitive tasks and processes that can be automated by AI agents.
Key opportunity areas include media and performance optimization, creative operations, account management, and strategy and intelligence. More specifically, agentic AI tools can minimize errors and speed up execution across tasks like budget management, creative testing, ad placement verification, and cross-platform data analysis.
Beyond these foundational areas, marketers should explore creative use cases specific to their team’s unique needs.
Agentic AI’s effectiveness hinges on data quality. However, most marketing teams don’t have the data readiness to make the most of the technology: Only 17.9% of marketers say their first-party data is extensive and well-structured, and one-third report that first-party data plays a minimal role in their current AI initiatives.
To get ahead, teams must work to unify their data within centralized platforms and databases and establish clear governance protocols for its usage. Without unified data that AI agents can access and act on, autonomous decision-making proceeds on a fragmented foundation. AI agents may still be able to execute workflows, but their decisions will be based on incomplete datasets that produce generic or flawed outputs rather than unique, differentiated benefits suited to an organization and its specific audience(s). Marketing teams should also invest in measurement tools that provide real-time, cross-channel insights, as this powers AI agents’ ability to learn and optimize continuously.
Thoughtful change management is another critical component of integrating agentic AI effectively. This means earning employee buy-in, providing comprehensive training to build AI fluency across teams, embedding AI tools into standard workflows, and finding ways to measure how successfully teams are using the technology. Leadership should also establish clear governance frameworks that define how AI agents operate and make decisions. These frameworks should clarify the critical role that human employees play in monitoring and managing those processes.
As consumers increasingly delegate research and purchasing decisions to AI agents, brands must ensure they’re discoverable to both autonomous systems and human audiences. This means creating structured data, clean APIs, and metadata-rich content that AI systems can easily ingest and interpret. Marketing teams should audit their websites, product catalogs, and digital assets to verify they’re optimized for both human visitors as well as AI agents.
The rise of agentic AI represents both a challenge and an opportunity for marketing teams. Those who prepare now—by identifying opportunities, building data readiness, proactively managing organizational change, and optimizing for machine discoverability—will be best positioned to capitalize on the technology’s transformative potential.
—
Looking for information on how your peers are approaching and thinking about AI? Our report, AI and the Future of Marketing, synthesizes unique insights from a proprietary survey of marketing and advertising professionals across leading agencies and brands.
YouTube has grown into the largest political video platform in the US. In this session of Basis' 2026 Political Advertising Bootcamp, our experienced Candidates & Causes team breaks down exactly how to win with YouTube advertising in the 2026 election cycle—from ad formats and targeting strategy to compliance and cost considerations. It’s your practical playbook for running political, advocacy, ballot initiative, or issue-based campaigns.
Watch now to learn how to build smarter, more efficient YouTube campaigns.
You'll Learn:
The Basis Political Advertising Bootcamp series continues series next month with: Winning with Audio.
Where clicks used to play a key role in the customer journey of discovering, evaluating, and eventually purchasing a product, zero-click search is changing how consumers discover and interact with brands. Learn how advertisers can adapt attribution models and media strategies for AI-driven search.
Key Takeaways:
With the emergence of zero-click search environments, how consumers discover and evaluate brands is fundamentally changing. AI-driven summaries and chatbot responses now deliver near-instant answers, curated recommendations appear without clicks, and purchase decisions often happen quickly.
Today, users who see AI summaries in Google only click a link in the search results 8% of the time, compared to 15% when those summaries don’t appear. And about 80% of consumers now rely on zero-click results in at least 40% of their searches. For advertisers who have built discovery strategies around driving measurable traffic through organic and paid search, that foundation is shifting.
Thanks to zero-click search, today’s customer journey is often shorter and faster. Where users may have previously conducted multiple searches, clicked through various links, and synthesized information themselves, many are now choosing rapidly based on AI-generated results—often without clicking through to any of the sources cited. For advertisers, this means rethinking measurement frameworks, adjusting channel strategies, and optimizing content for AI consumption rather than just human readers.
Zero-click search environments fundamentally change how audiences encounter brands. In traditional search, advertisers compete for clicks through SEO-optimized content and paid placements. In AI-driven search, whether within browsers or large language models (LLMs), the algorithm decides which sources to surface, synthesize, and recommend.
Consider someone searching for vegan protein powder. Upper-funnel queries like “Are there non-dairy protein powders?” now yield AI-generated summaries pulling from reviews, blogs, and retail sites. Middle-funnel searches for “best” recommendations now often surface lists scraped from affiliate content rather than brand pages. And lower-funnel branded searches often show retail listings, not the manufacturer’s site.
As a result, AI serves as a sort of intermediary between brands and consumers, contextualizing information in ways advertisers and brands can’t control. This shift is accelerating: As of late 2025, about 50% of Google searches included AI summaries, and this figure is expected to surpass 75% by 2028. This means approximately half of searches now include AI-generated content that may reduce click-through rates or obscure brand messaging.
This new search environment creates winners and losers. Small publishers and content creators, for instance, report traffic falling by as much as 70% after the introduction of AI Overviews. And brands relying on broad upper-funnel queries, rather than product-specific information, have faced similar drops. Take, for example, HubSpot. The company previously drove pipeline through broad searches like “famous sales quotes”—content that attracted traffic but wasn’t tightly aligned to their product. When AI Overviews launched, their traffic dropped between 70% and 80%. AI systems prioritize content that directly addresses what a product does or solves, so teams must optimize for relevance over volume.
This trend extends beyond traditional search engines. Between about 40% and 70% of LLM users use these platforms for traditional search engine use cases: conducting research and summarizing information, understanding the latest news and weather, and asking for shopping recommendations. The shift from click-based to zero-click discovery is becoming the norm across multiple interfaces.
The attribution challenges that follow zero-click are fairly predictable: If users don’t click, traditional tracking breaks down.
Historically, clicks on non-brand search terms (i.e., generic category searches like “vegan protein powder”) signaled awareness-stage engagement. Teams tracked users gathering information, then returning later to convert through branded search. In zero-click environments, that initial touchpoint disappears. Users may not enter attribution models until (or if) they appear in brand searches, making it difficult to measure which campaigns drove discovery.
For advertisers, this means top-of-funnel visibility now often gets cut off. Someone researching products may not appear in measurement systems until they search for a specific brand name. This measurement gap makes it even harder to understand the already complex “messy middle” consumer journey that connects awareness to conversion.
Yet drops in click-through rates don’t necessarily signal poor performance. In fact, conversion rates may increase even as fewer people click, as the users who do take the time to click through may have already completed their initial research and be closer to making a decision. Users may see ads alongside AI summaries without clicking, and those impressions still influence purchase decisions. In some ways, zero-click makes non-brand paid search campaigns even more valuable. Ads appearing in category searches deliver messages that brands and advertisers can control, versus AI-generated results that they cannot. The challenge is that impression-based influence is harder to measure and easier to overlook. And higher conversion rates from fewer clicks can mask the total impact of a campaign. As such, pulling back on search investments because CTRs are declining could mean abandoning a channel that’s still driving conversions.
To adapt, advertisers should adopt broader measurement frameworks that account for both the quality of clicks and the reach of impressions. Statistical modeling across platforms, on-site surveys that ask “How did you hear about us?,” and brand lift studies can help replace lost upper-funnel indicators. As zero-click behavior further fragments the customer journey, understanding campaign impact across channels becomes more complex. Tools like automated advertising platforms that consolidate and unify data from search, social, programmatic, and video into clear dashboards help teams see patterns that single-channel reporting can miss.
Zero-click search demands strategic shifts across channels:
As a growing share of searches conclude within the results pages themselves, the brands that adapt most effectively will diversify their channel strategies, invest in measurement tools that capture impression-based influence, and optimize content for AI consumption. Success in a zero-click search environment requires expanding beyond reliance on search traffic alone and maintaining presence across channels where messaging remains controllable.
__
Looking for more insights on how search and programmatic advertising are evolving? Our 2026 Programmatic Trends report explores the shifts reshaping digital advertising in the year ahead.
Innovation gets thrown around a lot in advertising—but what does it actually mean inside an agency?
In this episode of AdTech Unfiltered, we sit down with Savannah Westbrock, Head of Agency Solutions at Radar Analytics, to unpack how agencies can spot real opportunities for change, avoid hype-driven distractions, and build innovation that truly helps clients. From "desire paths" to pilot programs, Savannah shares practical frameworks for testing new ideas, improving workflows, and using AI to accelerate creative and media performance.
Welcome to our recurring blog series, “The Breakdown.” Each post breaks down a complex marketing concept and explores its applications—helping you make smarter decisions that drive meaningful results.
Marketers and advertisers face a pivotal choice in 2026: to frame their use of AI around driving business growth, or around cutting costs.
While AI can accelerate efficiency and reduce costs by speeding production and scaling content, its real power lies in the effectiveness it can deliver in the form of optimized creative, personalization, and predictive insights. Marketing leaders should guide their teams toward strategies that use AI to strengthen brand equity and long-term enterprise value, rather than focusing solely on its ability to drive efficiency gains and short-term margin improvements.
Data readiness is critical to achieving this goal. Without a strong foundation of unified first-party data and custom AI solutions trained on that data, organizations will struggle to create the differentiated outputs that drive brand and business growth.
How marketing leaders approach and position their use of AI in 2026 will define the role of marketing within their organizations for years to come.
While teams should absolutely use AI for efficiency-related gains like faster campaign execution and lower production costs, emphasizing its impact on efficiency alone can inadvertently play into the notion that marketing is merely a cost center that should be trimmed to the bone, rather than a strategic asset that can fuel effectiveness and multiply revenues. This, in turn, can reduce departmental resources and weaken marketing’s role in the larger organization.
Instead, marketers should embrace AI-powered marketing's ability to drive sustainable growth through smarter targeting, better creative, and real-time optimization. This can look like implementing enterprise AI tools to augment or automate the media planning process, leveraging AI-powered software to improve and scale creative ideation and testing, exploring AI-powered optimization for real-time performance enhancement across campaigns, or creating AI synthetic audiences—AI-generated, data-driven models of real people—that simulate how specific customer groups might respond to creative variations.
This value-driven approach can have transformative impacts: When AI is used to enhance marketing effectiveness rather than just to improve efficiency, companies can more than double marketing-driven profitability.
Critically, this work goes beyond using AI to drive long-term growth. Marketing teams must also demonstrate how their teams’ use of AI impacts business outcomes, and earn executive buy-in for reinvesting productivity gains into long-term growth rather than settling for short-term wins.
Differentiated AI results require proprietary solutions fueled by large volumes of clean, unified first-party data. And with 58% of industry professionals citing data quality and accessibility issues as critical challenges to adopting AI, marketers must prioritize data readiness to realize these maximal business-level gains.
A lack of data readiness appears to be the norm among marketing teams: Just 17.9% of marketing and advertising professionals describe their first-party data as extensive and well-structured, and a whopping one-third of those professionals say that first-party data plays little-to-no role in their businesses’ current AI initiatives. Even more, nearly half of marketers and advertisers report that their organizations don’t currently use any custom AI solutions or have any imminent plans to develop them.
Personalized, company-specific instances of AI solutions are critical to driving the business-level outcomes that can position marketing as an indispensable revenue driver, but they require quality data for training and rigorous planning to ensure that any desired use cases align with specific, measurable outcomes. As such, organizations that prioritize data readiness—and use that infrastructure to power custom AI solutions—stand to substantially outperform their competitors.
Marketers who frame AI as a driver of business growth rather than solely operational efficiency will be better positioned to secure ongoing investment and strategic influence.
This starts with building business cases that connect specific AI capabilities directly to revenue and brand outcomes. Demonstrating marketing's contribution to enterprise value creates the foundation for budget expansion rather than contraction.
Realizing these outcomes requires prioritizing first-party data infrastructure. Quality, accessible data differentiates AI outputs—without it, even sophisticated tools produce generic results competitors can replicate. Once that data infrastructure is in place, it should fuel custom AI solutions built to amplify growth. Proprietary (and/or semi-custom) models trained on brand-specific data reflect unique market positioning and audience understanding, enabling organizations to establish competitive advantages that strengthen marketing's strategic position over time.
Ultimately, the choices marketing leaders make about AI positioning today will determine whether their teams are properly perceived as growth drivers—or unfairly maligned as cost centers—for years to come.
—
Want more insights into how AI is reshaping marketing strategy? We surveyed marketing and advertising professionals from top agencies and brands to gather data on AI adoption trends, performance improvements, and implementation challenges. Check out AI and the Future of Marketing for a deeper dive into the opportunities and obstacles shaping marketing’s AI future.
Do marketing leaders ever really get a winter break? You’re supposed to be relaxing, but your brain won’t cooperate. You’re thinking about Q1 budgets while waiting for your flight. Mentally drafting your board presentation while the family watches a holiday movie. Lying awake in the wee hours of the morning running through 2026 talent considerations.
We’ve curated this reading list specifically for the realities of the holidays, matching key resources to those moments when you might have a few minutes to yourself. Whether you’re feeling inspired or just need a break from that one relative (you know the one…), these reads can help you start the new year informed and energized.
And if you only get through a couple of paragraphs before you’re called away to a snowball fight? We’ll call that a win.
Ah, the joys of holiday travel. You’ve been gifted a couple of extra hours in everyone’s favorite place: A crowded airport. Instead of spending it all on retail therapy at the duty-free shop, why not invest a few of those minutes in building up your industry smarts? This article provides an in-depth look at how the CMO role is transforming, how CMOs can set themselves up for success, and why brands that embrace these changes are best positioned to unlock their full potential.
The house is finally quiet, everyone’s asleep, and you’re wide awake staring at the ceiling. When work anxiety strikes in the middle of the night, it helps to know that many of your biggest challenges share a common denominator (address it, and you can alleviate multiple problems at once!). This article connects major challenges around proving ROI, AI adoption, talent efficiency and retention, and more back to data problems, and outlines practical steps marketing leaders can take to address them at their source.
Your aunt has had a bit too much eggnog, and she’s finally revealed the secret to everyone’s favorite holiday cookies: Real, high-quality vanilla extract. It has you thinking about other things that require quality inputs to generate quality outputs—AI, for instance. This article explores how marketing teams can get around barriers to AI adoption and drive ROI by improving their data readiness. While holiday cookies can still taste decent with artificial vanilla, AI tools simply can’t function without clean, unified, high-quality data.
Everyone has an opinion about AI, and when the topic comes up at the holiday party, you know that you’ll be expected to offer an authoritative take. This report provides the exclusive, data-based insights you need to sound like an expert, even if holiday brain fog has temporarily eclipsed your expertise. More importantly, you’ll gain a deeper understanding of how your peers are approaching AI adoption, the efficiency gains they’re seeing, the risks they’re most concerned about, and more.
You’re driving home from the holiday party, and that AI conversation is still rattling around in your mind. Have you done enough to optimize your team for an increasingly AI-driven future? This report provides exclusive data and actionable recommendations for navigating the AI revolution from a talent perspective in 2026. It’ll transform those anxious questions into ideas to fuel your tech and talent strategies next year.
Sometimes, sitting alone at the local pizza place waiting for your order provides the greatest holiday gift of all: A few precious minutes alone. This brief read offers expert guidance around one of marketing’s biggest debates—how to strike the right balance between performance and brand investments—with a particular focus on achieving that balance amidst economic uncertainty. You’ll arrive home not only with dinner, but with fresh insights for leading your business through volatility.
With the stress of Q4 2025 still fresh in your mind, you may be resolving to do things a bit differently in 2026—if only for the sake of your future self’s blood pressure. It’s a good call, as earning executive buy-in during budget season is considerably easier when you’ve been nurturing cross-departmental alignment and goodwill throughout the year. This article, written by Basis CMO Katie McAdams, outlines how marketing leaders can find more success securing C-suite backing by working to build trust with executives year-round. Her recommendations work in any economic climate, but are especially valuable when budgets are tight.
Well, there you have it: You just made smart use of the odd pockets of solitude that winter break provides. Made it through everything? Great. Only got through half of one article? Still counts. Either way, you’re heading into 2026 sharper and more informed than you were before.
—
Looking for one more resource to round out your winter break reading? Check out Rewinding to Fast Forward: The 2026 Digital Advertising Trends Report for an in-depth look at four key forces shaping the year ahead for brands.
Three industry veterans discuss the trends every advertiser should understand heading into 2026, including the crisis of programmatic waste, the rise of agentic AI, and the growing importance of consumer trust.
Key Takeaways:
1. Media quality must become a strategic priority: With only 36 cents of every programmatic dollar reaching publishers, it’s critical for advertisers to invest in verification tools and transparent supply paths to deliver real effectiveness.
2. CTV "premium" inventory requires scrutiny and validation: CTV inventory quality often falls short of advertiser expectations, requiring more rigorous evaluation and ongoing monitoring throughout campaigns.
3. Agentic AI adoption demands careful experimentation: As AI evolves from assistive to autonomous, marketers should start with small pilots, invest in their teams’ prompting skills, and prioritize enterprise tools that protect intellectual property.
4. Trust-building requires continuous strategic investment: With trust now as important as price and quality in purchase decisions, brands must leverage customer evangelists, maintain authentic creative, place ads in trusted environments, and use diverse measurement approaches to track results.
From AI breakthroughs to the proliferation of retail media networks to significant industry consolidation through M&A activity, 2025 brought transformative shifts that forced advertisers to rethink their strategies.
To explore how these shifts may impact brands and agencies in 2026, we brought together three industry veterans to share their insights and predictions. Their discussion spanned the challenges of supply chain transparency, the complexities of CTV inventory quality, the practical implications of agentic AI adoption, and the strategies brands are using to build authentic consumer trust—all critical trends that every advertiser should understand heading into 2026.
Editor’s note: This conversation has been edited for length and clarity.
Programmatic advertising waste has reached crisis levels, with only 36 cents of every dollar reaching consumers while the rest disappears into opaque fees and intermediaries. What does it look like when advertisers treat media quality as a strategic imperative rather than a nice-to-have?
April Weeks | Chief Investment & Media Officer, Basis: First, it looks like advertisers safeguarding the media quality of their buys by partnering with media quality and brand safety verification vendors like Peer39, DoubleVerify, and IAS. It’s easy for brands to avoid paying for those when they sound like they’re “extras.” But when they’re not included, low value inventory seeps in.
Like most things in life, you get what you pay for. When advertisers don’t take measures to protect their spend, they’re trading efficiency for effectiveness. Personally, I place less value on how efficient a buy was—I care about how effective it was. When you chase the efficiency game with low CPMs, you sacrifice high-quality inventory and the effectiveness needed to drive real outcomes.
Grace Briscoe | EVP of Client Development, Basis: This is one of those areas where advertisers can make the mistake of valuing and measuring the wrong metrics. If you focus on maintaining low CPMs or a low cost per click rather than on the outcomes your media plan is driving, you’re going to end up spending on lower quality, cheaper inventory.
Katie McAdams | Chief Marketing Officer, Basis: Those short-term vanity metrics can look really good from an efficiency standpoint. But in the long term, you’re trading effectiveness for efficiency.
GB: I also think it’s important for advertisers to get really clear about what they consider to be premium inventory. I’ve grown to kind of hate the word “premium”, because if you ask five different advertisers to define it, you’re going to get five different answers. It’s not an objective standardized term. It’s an opinion.
Take, for example, some brands avoiding news content. There’s this knee-jerk reaction to block all news because advertisers don’t want to show up near anything negative. But I would consider journalistic news content to be premium, and when advertisers avoid it, I think it continues a cycle of defunding quality content. And that hurts the whole ecosystem in the long run.
AW: I completely agree. Gaming is another great example of both a channel and content that’s easy to stereotype. There’s this idea that gaming only reaches teenage boys sitting in their basements, but that’s not the case at all. If you look at the research and the audience data, a lot of women and high-income households are engaging with gaming content and platforms regularly. So another essential part of the story here is the importance of taking an informed and data-driven approach to how you’re defining inventory, rather than making assumptions.
KM: I think similar assumptions can lead advertisers down the wrong path when it comes to connecting with diverse audiences. Buyers tend to assume that general audience inventory is going to give them spillover into diverse audiences, but that’s often not the case. They need to tap into the supply networks that truly represent the publishers where those audiences spend time.
AW: That’s right, and it's a critical point at a time when the economic impact of diverse audiences continues to increase. The best way to reach diverse audiences is to take an authentic community approach, tapping into specific inventory sources that curate high-quality content that actually resonates and is specific to those audiences.
Speaking of “premium,” that label has largely lost its meaning across CTV, as advertisers paying for inventory on major streaming platforms often end up with ads running on long-tail apps and user-generated content. Considering that “premium” no longer guarantees quality in CTV, how are leading advertisers adapting their CTV strategies?
GB: Again, I think it’s important to note that premium is in the eye of the beholder. When it comes to streaming TV, does inventory qualify as “premium” because of its production value? Because it’s sold by a major streaming service? Or is it about the ad load of how many ads are shown within that content?
I do think we’re seeing brands demand more transparency—particularly in the CTV space— because there are a lot of players in the marketplace operating as black boxes and offering opaque bundles. Often when you start to unpack those bundles, you realize that the “CTV inventory” you purchased actually had a lot of mobile video or other online video mixed in.
There are ways to tell when inventory isn’t premium, though. If the CPM seems too good to be true, then it probably is—you’re not getting ESPN for a sub-$30 CPM. So it’s important for advertisers to evaluate those kinds of signals critically.
KM: It’s also critical for advertisers to check in on their campaigns midstream. That’s when you can validate if your ads are really landing where you placed them and make changes if needed.
GB: Right. Some of that also has to do with how clean the supply path is and maximizing how much of your spend is going as directly as possible to publishers with as few middlemen as possible. The more you tap into aggregators and resellers, the less transparency you have, and the quality starts to go downhill as well.
AW: That ties into the dialogue around the value of curation. With curation, you’re adding another middleman to the supply chain. Curation partners are supposed to filter, bundle, and curate high-quality inventory that delivers access to valuable audiences in premium environments. But is that worth the additional cut they take? These are the questions advertisers have to ask themselves: what’s the value, and is it worth the additional cost and supply chain complexity? The best way to know is to test and learn—understand the potential lift in performance vs. the cost trade-offs by implementing curation.
I would also note that the inclusion of ACR (or automatic content recognition) data, and overlaying ACR data from a reporting standpoint, provides an additional level of granularity around placements, which can help validate you’re getting the quality you want.
GB: ACR also gives you a lot more visibility—for example, frequency of ads per household and the incremental reach. If you’re buying, say, linear TV as well as CTV, then ACR allows you to see how much of the audience is unique versus overlap and duplication. You might see that certain viewers were exposed to an ad on NBC news on linear TV, but also got impressions from Tubi on CTV. Then you can start to optimize on that information— perhaps reallocating budget because it might be a much more effective CPM to reach those viewers on Tubi than it is on primetime linear TV.
AW: And ACR can also help by showing when you’re burning impressions against the same audience.
There are some other important considerations when it comes to targeting and addressability as well. We know there’s often a high, high degree of inaccuracy with IP-based targeting. Considering that, using first-party data and deterministic data layered into buys is a good strategy to increase the integrity of your TV targeting.
Deterministic data—which could be something like user verified login data—is the most precise data advertisers can use for targeting. Probabilistic data, on the other hand, is modeled data inferred from deterministic data, which means that it’s less accurate. It's really important for advertisers to understand these different types of data, because many platforms claim that they can offer addressability, but the accuracy of that addressability varies significantly based on the kind of data powering it.
Agentic AI is poised to fundamentally transform marketing operations, evolving AI from assistive technology into autonomous systems capable of executing complex, multi-step tasks independently. What lessons from the rise of generative AI and the industry’s approach to adopting those AI tools can help marketers more effectively adopt agentic AI?
AW: One thing I would say is that many of the use cases for both gen AI and agentic AI are undefined. Because of that, it’s important for marketers to be open and curious about exploring different possible use cases.
Additionally, my belief is that AI—whether it be generative or agentic—is becoming an overused and almost abused term. You have to ask questions, because there are a lot of companies claiming to have AI solutions where, when you pull back the layers, the tools are actually very clunky, not well developed, and may not be true AI tools.
KM: That all rings very true with my team’s experience as well. As advertisers start testing agentic AI, I’d recommend starting with very small pilots. It takes time to build confidence and trust that an agentic AI tool is going to be able to, for example, capably represent your brand or market it in the same way that you’d expect an employee to. That trust is only going to come with time and testing and learning. That's why it's best to start with a small, controlled test where you're comfortable with some margin of error.
GB: I’d also recommend that advertisers keep in mind that generative AI and agentic AI are both tools that are still very much people-powered, and the outputs are only as good as the inputs. I think of these AI tools as interfaces between human thinking and computational superpower.
KM: Yes—to build upon what Grace is saying, humans should be questioning all the responses they receive from AI tools. You need to continually question and test the narrative they’re creating for you. And, to Grace’s point about AI tools being people-powered, that drives home the importance of having skilled prompters. It’s really important to invest in those skills among your team.
Personally, I’ve also seen a lot of progression and improvement in enterprise AI tools like Copilot. I think we’re going to see those enterprise tools grow to be more on par with the other major tools, and we may see companies mandating that their employees only use those pre-approved enterprise tools as they seek to protect their IP.
AW: Agreed. The way these enterprise tools can store and process so much of a company’s data and information really unlocks a lot of use cases that people may have previously been hesitant about, because they were concerned with data privacy and security.
GB: That brings to mind some of the concerns I've heard from several brands and marketers: If we're all using the same generative or agentic AI tools for creative purposes, are all our ads going to look the same? How do you ensure that your brand's identity and integrity and data stay yours and don't get diluted or distributed? Enterprise tools offer solutions for some of those concerns, but there are still a lot of unanswered questions.
New studies show that trust has emerged as equally important to price and quality in consumer purchase decisions. At the same time, in an era marked by cultural volatility, social fragmentation, and widespread consumer distrust, earning trust represents a significant challenge for many brands. How are brands incorporating trust into their marketing strategies and assessing the success of their efforts?
AW: One thought I have is around the role of influencers within marketing. Research shows that recommendations from family, friends, and trusted influencers can have a greater influence in terms of building trust for the brand than traditional advertising. That impact varies among categories, but for many brands, a strategy around building trust may look like reevaluating how they leverage brand ambassadors and influencer marketing.
KM: I agree. To extend that into the world of B2B, brands really need to invest in things like customer marketing and look at their customer evangelists as their best marketing tool. Ultimately, people are going to have more trust in a brand if they are hearing good things from someone who’s actually a customer. That’s always going to feel more authentic than what a brand says about themselves. The goal is to build a system where word of mouth is consistently generating leads.
Another critical piece of trust-building is authenticity when it comes to your ads and your creative. Going back to AI, brands need to use generative AI in a way where they’re still creating things that look and feel authentic to their brand.
And then, lastly, this also connects back to our conversation around media quality. When consumers see ads in trusted environments, in context of trusted content, that’s going to further brand trust. On the flip side, seeing the same ad run on an MFA site creates a poor user experience, which impacts how people perceive and feel about the brand.
AW: Yes, 100%. When it comes to measuring trust in a certain brand, social listening comes to mind as one good way for advertisers to get a baseline of consumer sentiment around a brand. Brand studies are another solid option.
GB: There’s no silver bullet that’s going to give you a full picture, so advertisers need to leverage a variety of different approaches to get an accurate read on consumer sentiment—a combination of social listening, customer reviews, customer surveys, brand lift studies, maybe a brand index study, et cetera. Using only one of those lenses to assess consumer trust will likely give advertisers a skewed view, so it’s important to embrace a healthy mix of approaches.
KM: It's really about identifying all the touchpoints where customers interact with or talk about your brand, then figuring out how to collect and analyze that information holistically.
AW: I would also add there’s a benefit in widening the aperture and looking not just at your own brand, but what’s happening in your sector more broadly. For example, if there’s a particularly high level of consumer distrust in your sector, what opportunities does that open for your brand to rethink their positioning to gain trust?
GB: One last recommendation: To build brand trust, brand marketing needs to be continuous. As soon as you disinvest in that, your customer base will erode over time.
KM: This all goes back to the effectiveness vs. efficiency play that we were talking about at the beginning.
GB: Full circle.
AW: Full circle!
It's critical for leaders at agencies and brands to nurture a thorough understanding of how these four trends are likely to develop over the next year. Check out Rewinding to Fast Forward: The 2026 Digital Advertising Trends Report for more insights advertisers can use to gain a competitive edge in 2026.
Between holiday travel, endless leftovers, and the annual rite of forgetting what day it is, the end of the year can be a bit of a blur. Yet it can also offer a rare pocket of breathing room, allowing agency leaders to step back from the daily rush and think about the bigger shifts shaping the future of the advertising industry. With AI accelerating, data fragmenting, and client expectations rising, leaders are heading into 2026 with more complexity to manage—but more opportunity to capture as well.
This winter break reading list highlights many of the themes defining the next chapter of agency work: operational clarity, AI readiness, unified data, and stronger strategic partnerships. For your convenience, we've grouped the reads by the moments that tend to emerge during winter break—planned or otherwise. When you find a few minutes to yourself, this list is ready for you. And if you need a reason to hide in the guest room for twenty minutes, you’re welcome.
You’ve heard, “So what exactly is it you do again?” one too many times and need a few minutes to yourself. Instead of scrolling mindlessly, why not escape into the world of strategy, leadership, and the future of agency work?
Agencies are being asked to do more with less while navigating shifting client demands, agentic AI, and an increasingly complex media environment. Here, gain expert perspectives on the pressures driving change and the strategic choices leaders must make in response. Topics include how to balance profitability with investment in talent, how to integrate AI without losing the human touch, and how to sharpen strategic focus instead of trying to do everything for everyone. Consider it your guide to what will separate future-ready agencies from the rest.
With budgets tightening and client expectations rising, agencies are navigating an increasingly challenging landscape. This piece outlines how tech-driven efficiency can help stabilize teams, strengthen client relationships, and protect margins amidst economic pressure. It also highlights why integrated systems and automation are becoming essential for agency resilience and provides practical guidance on using technology to maintain performance and drive long-term growth.
If the departures board has betrayed you, dive into the pieces that show how consolidation and smarter systems can restore a sense of order—at least to your data.
With more tools, more channels, and more platforms, advertisers are struggling to achieve a holistic view of performance. This presents a major barrier to agency teams, especially in the context of the rising pressure to prove impact. This article breaks down how disconnected data and tech sprawl fuel operational inefficiencies and limit teams’ ability to adapt quickly. It also explores how consolidating data into one source of truth strengthens reporting, improves optimization, and unlocks the full value of AI-driven tools. For leaders navigating complexity, it offers a clear case for why consolidation is both a strategic and operational imperative.
From media fragmentation to revenue pressure to stalled AI initiatives, many of marketing leaders’ toughest challenges share a common source: poor data foundations. This article unpacks how inconsistent, siloed, or overwhelming amounts of data complicate decision-making, weaken storytelling, strain teams, and limit the impact of new technology. It also outlines practical steps leaders can take to consolidate insights, strengthen visibility, and unlock more strategic value across operations.
Perfect for a quiet morning with coffee or a rare uninterrupted afternoon, these pieces zoom out to help you see the industry with a fresh perspective.
This year’s Advertising Agency Report captures a sector in transition, with teams grappling with increasingly fragmented workflows, tougher client demands, and heightened brand safety risks. The report uses data to outline the most urgent challenges agencies are facing, as well as the strategic investments leaders plan to make next—especially around AI and operational efficiency. If you’re short on time, catch the executive summary here.
Brand-agency relationships are shifting fast, and the gap between how agencies think they’re performing and how brands grade their performance is significant. This piece breaks down why that gap exists, how tech and media complexity are reshaping expectations, and what agency leaders can do to strengthen client trust and demonstrate their value.
For easing from vacation mode into the new year, these pieces provide a gentle reentry into operational discipline, efficiency, and the systems that help teams thrive.
Pitching remains essential for agency growth, yet it’s become increasingly complex and costly. With clients demanding faster turnarounds and more operational transparency, agencies must show not only strong ideas but the systems that enable them. This piece breaks down how tech maturity, unified data, and AI readiness can ease the burden on teams while strengthening pitch performance. It offers a clear view into how agencies can modernize their approach to win business in a more competitive market.
From privacy shifts to brand safety concerns to a sprawling tech ecosystem, agencies are feeling the weight of growing complexity. This article argues that improving efficiency is the key to cutting through complexity and helping agencies work faster, drive better performance, and strengthen client relationships. It breaks down the risks created by disconnected systems, manual processes, and underutilized AI, and highlights how streamlined systems and automation can simplify operations and strengthen client relationships.
As the year winds down, consider this reading list your invitation to recharge, recalibrate, and head into 2026 with a clearer view of what matters. And if diving into any of these articles gives you an excuse to procrastinate packing your suitcase? Even better.
__
Looking for more insights to inform your 2026 planning? Rewinding to Fast Forward: The 2026 Digital Advertising Trends Report provides perspective on four key topics that will influence how advertisers work next year. Get your copy now and uncover the trends and opportunities that will shape 2026 for advertisers.
Features like Spotify’s “Wrapped” or Netflix’s “Your Next Watch” resonate because they surface data-based insights into our actual behavior. Similarly, the articles that were most popular among our audience in 2025 reveal the challenges and opportunities that most captured marketers’ time, curiosity, and attention over the past year.
In analyzing the posts that drew the most traffic in 2025, four key themes appeared: AI’s transformative influence on the search landscape, evolving and oft-conflicting regulatory pressures, leadership roles expanding and evolving, and media formats continuing to fragment. Below, we unpack what these four themes tell us about the current state of marketing—and where the industry is headed in 2026.
When Gartner predicted in early 2024 that 25% of traditional search engine volume would shift to AI chatbots and agents by 2026, it crystallized what many marketers were already sensing: A fundamental shift was underway. The rise of zero-click search is radically changing where and how consumers engage with information—and, by extension, where advertising needs to show up.
The popularity of our search-related content reveals where marketers are seeking guidance most urgently: Navigating the fragmentation of the search landscape, understanding how to adapt to AI Overviews, and building the operational flexibility needed to adjust as platforms and query formats continue to evolve.
This piece explores what the shift to natural-language queries and AI-powered agents means for advertisers, highlighting fragmentation in the search space, brand safety and misinformation risks, and organic traffic declines. Plus, it provides guidance on upskilling teams, testing with AI-driven tools, and building the operational flexibility needed for a rapidly evolving search landscape.
Early research has found the appearance of AIOs to be correlated with lower organic and paid click-through rates. Here, learn why certain verticals and query types trigger AIOs more often, how the format changes user behavior, and what marketers can do to adapt.
Alongside these AI-driven changes, regulatory shifts are pulling marketing leaders in competing directions. The popularity of our regulation-focused content in 2025 reveals how much uncertainty exists around what’s actually changing and what it means for advertisers.
On one hand, the Trump Administration has taken a deregulatory approach, signing an executive order requiring that for every new rule, regulation, or guidance, 10 existing ones must be repealed. At the same time, the number of states that have comprehensive consumer privacy laws enacted or in effect continues to climb, and consumer concern about data privacy remains high. As teams plan for 2026, they must understand existing regulations and build strategies flexible enough to absorb diverging and ever-evolving compliance requirements without constant overhauls.
The return of the Trump Administration introduced a new regulatory posture for digital advertising, with many anticipating reduced federal oversight and heightened economic uncertainty. This post explores the political, economic, and cultural pressures evolving under the new administration, giving teams context for how future planning may need to adjust.
Despite the Trump Administration’s focus on deregulation, regulatory activity across states and global markets continues to accelerate. New privacy laws, stricter enforcement under the CPRA, rising false advertising scrutiny, and movement on AI regulation are reshaping the compliance landscape. This post provides a clear overview of the regulatory trends influencing data use, targeting precision, and campaign operations.
These external technological and regulatory pressures—alongside other forces like economic volatility—are transforming expectations for leadership.
For brands, the CMO role has expanded. Today’s leaders are tasked with not only building their brand but also bringing product and sales strategies together to build alignment and ensure cross-functional success. Meanwhile, agency leaders are also navigating complexity, caught between client demands for efficiency gains and the need to maintain profitability—and inaction on new capabilities only makes them vulnerable to competitors who move faster.
In 2026, competitive advantage will come from understanding these pressures and adapting to them quickly. Leaders who can integrate AI meaningfully, evolve how their teams work, and prove business impact faster than peers will separate themselves from competitors still debating whether to act.
Agencies are navigating a perfect storm of pressures: economic volatility, shrinking client budgets, rapid innovations in AI, and a media landscape that is growing increasingly fragmented. Here, industry veterans share where agencies are feeling the most strain, how expectations from brands are shifting, and what leaders can do to evolve their talent, technology, and operating models.
The CMO role has expanded far beyond more traditional brand building expertise. Today’s leaders are expected to blend strategic vision, technical fluency, financial logic, and cross-functional influence—all while navigating growing misalignment across the C-suite. This deep dive unpacks the pressures reshaping the CMO role, the growing expectations for business impact, and the leadership traits that will matter most in the years ahead.
While leadership grapples with new mandates, the media landscape continues to splinter. The continued growth of short-form video and streaming TV in 2025 wasn’t a surprise, but the scale of their impact became impossible to ignore. As of this year, 40% of sports fans only watch sports on streaming services. And people (especially younger audiences) are spending an increasing amount of time watching short-form video—and making purchases as a result.
Understanding how media consumption continues to change is key for deciding where advertising dollars go, how creative gets developed, and what “engagement” actually means when formats and platforms are constantly fragmenting.
Short-form video has become a default media habit, reshaping how people discover products, engage with creators, and make purchase decisions. TikTok and TikTok-esque features across platforms have normalized fast, highly personalized content that blurs the line between entertainment and advertising. Here, learn how this shift is changing creative expectations, funnel dynamics, and brand safety needs, as well as what it takes to use short-form video as a meaningful driver of attention.
Live sports are evolving from cable mainstays to a fragmented, streaming-first world, with leagues striking exclusive deals across platforms and rights fees soaring. This post breaks down how shifting inventory packages, rising sports betting engagement, and second-screen behavior are reshaping the value of live sports advertising.
As viewers continue to migrate to streaming and advertisers look for flexibility, programmatic CTV is becoming a critical way to reach audiences on the big screen. This piece breaks down why upfront commitments are losing ground to dynamic, data-driven buying and how AI is improving contextual targeting, reporting, and brand safety controls.
The themes that drove engagement this year won't be resolved neatly in 2026. If anything, they'll deepen. Teams will need ongoing strategies for adapting to AI-driven search changes, managing evolving regulatory requirements, proving business impact as CMO and agency leader responsibilities expand, and reaching audiences across increasingly fragmented media channels. The common thread across all four themes? Success will require strategies built for continuous adaptation, not one-time fixes.
For a more comprehensive look at what’s ahead—including expert perspectives and strategic guidance on navigating these shifts—download our full 2026 Trends Report: Rewinding to Fast Forward.