Every year, we ask Adswerve's practitioners the same question: what are you seeing in client work right now that most marketers aren't planning for yet? Their answers shape our annual predictions, and this year a pattern emerged across every response. Data teams, media strategists, measurement leads, and AI specialists all pointed toward marketing systems that anticipate what customers need and act on those signals in real time, with less manual intervention and more connected infrastructure underneath.
Below are five predictions for 2027 grounded in the trends our teams are tracking across hundreds of brand and agency engagements. From real-time data pipelines powering AI agents to always-on measurement models that replace quarterly reports, these are the shifts we believe will define the year ahead.
AI agents are generating enormous excitement, but they are only as effective as the data flowing into them. An agent designed to adjust campaign bids, update audience segments, or trigger a personalized offer in real time cannot do its job if it is pulling from data that refreshes overnight or lives in disconnected systems. In 2027, we think the brands that get the most from agentic AI will be the ones that invested in their data plumbing first.
That means building connected, governed data pipelines that feed clean signals to every platform in the marketing ecosystem, from ad servers and DSPs to CDPs and data warehouses like BigQuery. The IAB Tech Lab's agentic advertising and AI initiatives are working to establish shared standards for exactly this kind of infrastructure, a sign that the industry recognizes the gap between agentic ambition and data readiness.
What to do about it
Evaluate whether your current data infrastructure can support real-time or near-real-time decision-making. Prioritize API integrations, connected pipelines, and timely conversion signals, with governance and controls in place so that AI agents can act on reliable information.
Ad operations are moving from manual campaign management to connected, autonomous systems. In 2027, we expect to see specialized AI agents handling campaign adjustments, fraud detection, real-time audience updates, and creative optimization with appropriate human oversight. Instead of tweaking daily settings, marketers will set high-level goals and guardrails and let agent networks execute against them.
WPP Media and a consortium including Disney Advertising, Netflix, and NBCUniversal are already testing how buyer and seller AI agents communicate, validate decisions, and execute in video advertising environments. Magnite reported a 56% year-over-year increase in global live sports ad spend through the first half of 2026, with more than 5,800 new advertisers spending on live sports inventory for the first time, much of it flowing through automated, programmatic channels.
At the same time, entirely new ad inventory is opening inside conversational AI platforms. OpenAI launched advertising in ChatGPT in early 2026, and Amazon has expanded its own conversational ad formats designed for AI-powered shopping environments. Brands now have a new surface where customers are actively expressing intent, going beyond browsing to ask questions and make decisions in real time.
These two trends reinforce each other. Agentic execution handles the operational complexity of running campaigns across fragmented platforms. Meanwhile, conversational advertising creates new touchpoints inside the AI interfaces where consumers increasingly start their research. Together, they accelerate a shift that forward-thinking marketers are already preparing for: systems that can sense demand and respond to it faster than any manual workflow.
What to do about it
For agentic operations, start by identifying the repetitive, rules-based tasks in your media workflow that could be handled by autonomous agents. Bid adjustments, pacing, and audience refreshes are natural starting points. For conversational advertising, test early, especially for verticals like travel.
For decades, marketing has been about influencing human decisions through awareness, emotion, creativity, and persuasion. But what happens when consumers delegate research, comparison, negotiation, and purchasing to AI agents? The traditional purchase funnel starts to disappear.
AI agents won’t necessarily see your advertisements, appreciate your creative campaign, or visit your beautifully designed website. They’ll evaluate structured information such as product performance, price, availability, customer reviews, and the credibility of the underlying data. Gartner projects that by 2028, 90% of B2B buying will be intermediated by AI agents, pushing more than $15 trillion in spend through agent-driven exchanges. Consumer purchasing is following the same trajectory.
That doesn’t mean brand building becomes irrelevant. Emotional preference still drives the human who sets the agent’s parameters. But marketers will increasingly need two parallel strategies: one that earns trust and affinity with people, and another that makes their products discoverable, credible, and transactable for the machines acting on those people’s behalf. Some are already calling this emerging discipline “agent relationship management,” and we think it may become as foundational as SEO was a decade ago.
What to do about it
Start by auditing how your brand shows up to machines, not just people. Is your product data structured, accurate, and accessible through APIs? Are reviews, specs, and pricing available in formats an agent can parse? The brands that make themselves easy for AI agents to evaluate and recommend will have a meaningful advantage as this behavior scales.
In the debate over marketing mix modeling (MMM) versus multi-touch attribution (MTA), the answer turned out to be…both, plus a third layer. In 2027, we believe the benchmark for sophisticated measurement will be triangulation: always-on MMM calibrated by insights from your data clean room and data warehouse, and validated with controlled incrementality experiments.
Modern MMM platforms now refresh weekly or biweekly against fresh spend and outcome data, replacing the quarterly report with a continuous decision engine that connects macro strategy to tactical budget allocation.
Data clean rooms and your data warehouse then add the layer MMM alone cannot provide. By connecting first-party data in privacy-safe clean rooms and unifying it with the customer, sales, and CRM data already in your warehouse, marketers can attribute conversions at a more granular level. Incrementality testing then validates both: did the campaign actually cause the lift, or would it have happened anyway?
To bring this to life, marketers need to connect three layers of data. Macro-level inputs feed the MMM. Identity-level data from clean room integrations and your data warehouse fine-tunes individual channel performance. And incrementality experiments provide the ground truth that keeps both honest.
What to do about it
Move from periodic MMM reports to an always-on model. Connect your first-party data to clean rooms and your data warehouse to track conversions in privacy-safe environments and tie them to business outcomes. Then build a cadence of incrementality tests to validate what your models are telling you.
In a media landscape defined by fragmented attention and declining linear viewership, live sports remain the exception. Ninety-six of the 100 most-watched US television broadcasts in 2025 were live sports, and EMARKETER projects sports TV ad spending will surpass $20 billion in 2027 and grow by more than $5 billion through 2030, roughly four times faster than the overall TV ad market.
In 2027, we recommend that advertisers plan early to get their media dollars to stretch further. Amazon sold out its Thursday Night Football inventory during the Upfronts before scatter buying even opened. Disney secured the Super Bowl broadcast rights for 2027, and new advertisers are entering the mix for those spots.
Programmatic access is expanding, with platforms like Display and Video 360 enabling automated buying against live sports inventory that was previously available only through direct deals. But the best inventory goes fast, and guaranteed delivery still requires advance commitments.
What to do about it
If live sports are part of your 2027 media plan, start mapping available inventory now, especially programmatically. Lock in what you can at upfront pricing. There will be scatter inventory available later, but availability shrinks and costs rise as game day approaches. Working with your programmatic partners early is the surest way to secure both a better price and guaranteed delivery.
Marketing in 2027 will reward the organizations that invest in connected, intelligent infrastructure. Whether that means real-time data pipelines that feed agentic systems, always-on measurement frameworks that replace quarterly guesswork, or programmatic strategies that lock in premium live sports inventory ahead of the rush, the advantage goes to teams that plan the system, not just the next campaign.
Adswerve works with brands and agencies across data strategy, media activation, AI-powered intelligence, and measurement to build exactly this kind of foundation. If any of these predictions resonated, or if you are already working through one of these shifts, we would love to talk about what it looks like in your environment.