AI and Marketing Data

The age of artificial intelligence is here, and marketers in 2026 face a new landscape where the technology is woven into nearly every aspect of the advertising industry. AI is changing how campaigns are created, deployed and measured, and could help marketers finally deliver on holy grails like personalization at scale and closed-loop measurement as emerging channels, from connected TV to retail media, become performance driven.

But there’s still a lot of work that needs to be done to bring those promises to fruition. As stakeholders jockey for position, often promising one-stop shops and turnkey solutions powered by AI, the savviest marketers will need to navigate the changed ecosystem by separating reality from hype — especially around emerging areas like agentic AI.

When it comes to AI in 2026 and beyond, marketers would do well to embrace a version of the serenity prayer: accepting what they cannot change, courageously changing what they can and wisely knowing the difference between the two.

“You look at some of these structures, and you start to say, when everything works, it truly is like magic,” said Jacob Davis, executive director and global head of performance at Crossmedia. “It very infrequently works perfectly.”

In the last few years, major agencies, ad platforms, media conglomerates and ad-tech companies have rolled out AI-powered solutions that seek to automate much, if not all, of the advertising process. When launching campaigns, advertisers can pick and choose from Meta’s Advantage+ suite, Google’s Performance Max and Amazon’s full-funnel campaign offering; WPP Open, Publicis’ CoreAI and Omnicom’s Omni; and publisher offerings from giants NBCUniversal and Disney. 

While they have different capabilities and components, these solutions look to decrease costs and increase performance, often at the cost of transparency into their machinations. In that way, AI supercharges pre-existing machine-driven automation systems — “the algorithm on steroids” said Mathieu Roche, co-founder and CEO at ID5. 

“It's still very much a black box, which works if you're just interested in outcomes, however they define outcomes,” Roche said. “I don't think it works for the top-end of the pyramid of advertisers, but for small- to long-tail advertisers who are looking for traffic to websites or app downloads… there is a sliver of the market that really welcomes that.”

Platform, agency challenges

Over the last few years, AI has been integrated into marketing workflows around creative, planning, targeting and optimization. Each area represents a different challenge for AI and a level of tolerance for outsourcing by marketers. For example, brands are likely to retain control over their creative but more likely to hand over audience planning to AI, Roche claimed. The way media planners and buyers work could change the most as platforms roll out plain-language chatbots that assist in generating media plans.

However, these AI-powered platforms are usually mass-market solutions, not purpose-built for individual marketers. The question remains whether they can truly address brand needs. 

“Do they work the way they are supposed to work? Because these platforms are so big, they're not really changing things based on what a brand wants, even if they're willing to spend money,” said Unni Kurup, director of client consulting and strategy at Theorem.

As brands look to navigate this new AI-powered landscape, the role of agencies could evolve, turning the adland players into a layer of connectivity and enablement for environments like Meta and Amazon — walled gardens that have used the AI moment to strengthen their positions, explained Nicole Greene, vice president and analyst at Gartner.

“Every one of these platforms is going to have their own data. They're going to own the experience, and now they're going to own the creative, optimization and measurement. … You're playing by their rules,” Greene said. “Agencies might be a great way for brands that otherwise don't have the capacity to do it on their own to have visibility across those platforms.” 

Amid the push for automation, marketers still face questions around identity, a space that remains in flux despite Google’s decision not to deprecate third-party cookies. Marketers must decide whether to spend on media or on media plus identity resolution, which is potentially more effective. Currently, many are choosing the former, and possibly making a mistake, Davis said.

“If I could put $100,000 into LiveRamp, or I could put $100,000 into Meta, the smart choice would be $100,000 in LiveRamp,” Davis said, using the data-collaboration platform that recently secured a strategic partnership with Publicis as an example.

The ability to justify performance media offered by AI-powered ad platforms to other C-suite stakeholders could make it an easier choice, especially as marketers become wary of high fees in programmatic and suspicious of additional players in the media supply chain taking a cut of media spend. Through it all, marketers continue to face issues pinpointing which media drives conversions and value.

“Was it because we had a Kargo SSP overlay with PubMatic? Was it because of the creative that we ran? Was it because of LiveRamp, or was it because we ran it through The Trade Desk?” Davis posited, illustrating a common marketer quandary.

The rise of the agents

Just as marketers were getting comfortable with a new AI-powered status quo, the next step of the automation revolution has begun with the growth of agentic AI: fully autonomous systems that can coordinate without human intervention and could simplify and optimize applications like programmatic advertising.

WPP and Omnicom began 2026 by announcing new agentic AI offerings. PubMatic debuted an agentic operating system intended to solve pain points around programmatic that launched with partners including WPP Media, Butler/Till, Wpromote and MiQ, and is part of a consortium that launched the new Ad Context Protocol. Meanwhile, the IAB rolled out frameworks and roadmaps for the agentic future — an opportunity for adland to learn from the mistakes of past technical developments and bake in standardization from the start.

“Although AI solutions will increasingly take shape, the industry should expect several false starts in deploying agentic solutions,” said IAB Tech Lab CEO Anthony Katsur in a statement. “The promise of agentic AI is real and meaningful, yet its practical application will require years of market experimentation, standardization and alignment across platforms, agencies and publishers.”

Marketers that adopt agentic AI and let agents plan, test and continuously optimize campaigns will save time and resources on laborious tasks, giving them time to work on big-picture ideas like goal setting and experimentation.

“Agentic AI will change marketing by shifting the burden of execution,” said Upwave CEO Chris Kelly in emailed comments. “The real advantage comes from agents making thousands of small optimization decisions in real time… far more than any team could manage manually. Brands that adopt these systems early will simply move faster and learn faster than their competitors.”

But like other applications of AI in advertising, agentic AI success isn’t guaranteed. Along with sorting through a new alphabet soup of agent protocols — AdCP, MCP, UCP — marketers will need to have their own data, APIs and other tech stack elements prepared.

“Do you have quality APIs where you can pass through data? That's going to be really important, to make sure that you're agent ready, so that as these different platforms begin to consolidate and allow for more accessibility, you're able to deliver into these environments,” said Gartner’s Greene. “People [who say] it's all going to connect and be seamless… if that happens, I can probably sell you a bridge.”

During upfront presentations in May 2026, leading media companies made their big pitches to secure advertising dollars, enlisting Hollywood talent and audio-visual flair to punch up programming slates and digital capability offerings. Across the sometimes literal dog-and-pony shows were several reminders of how these presentations continue to evolve to meet changing consumer behaviors and advertiser demands.

"The biggest shift heading into this year’s upfronts is that TV is no longer insulated by awareness-only measurement expectations,” said YJ Kim, strategy director at consultancy AI Digital, in emailed comments. “Premium reach still matters, but measurable business impact is increasingly what unlocks incremental budget."

Several themes emerged during upfronts hosted by legacy publishers including NBCUniversal, Disney, Warner Bros. Discovery and Fox, as well as tech giants Netflix and Amazon that are relative newcomers to TV advertising. Marketing Dive was on the ground in New York for these showcases, and has assembled key takeaways from a series of presentations that had more in common than not.

Live sports win

The sitcoms and hour-long dramas that previously dominated the upfronts felt like afterthoughts in presentations increasingly dominated by sports. 

NBCU is expanding its Sunday night sports strategy from football to basketball and baseball, giving advertisers a more consistent opportunity year-round. Its Telemundo channel will also feature 700 hours of FIFA World Cup programming and be on-site at all 104 matches for the soccer tournament. For its part, Fox will broadcast a record 70 World Cup matches on network television, with 40 in primetime. 

“This week, you’re going to hear a lot about the value of live sports and ad-supported streaming. At Fox, that’s not a new story: It’s what we’ve been delivering successfully for years,” Fox CEO Lachlan Murdoch said during the company’s presentation. “Fox is the leader in live programming and home to one of the fastest growing ad-supported streaming platforms in the business. That combination isn’t accidental — it’s intentional.”

Streamers Netflix and Amazon talked up their NFL offerings, with the former adding three additional games to its slate and the latter continuing to find success with its football programming. Amazon Prime Video’s “Thursday Night Football” delivered its largest season-long audience in the show’s 20-year history, and the streamer’s wild card game presentation drew 31.6 million viewers — the most-streamed NFL game of all time. 

“Prime audiences don’t merely tune in, they lean in,” said Charissa Thompson, a sportscaster on Prime Video, during the Amazon upfront. “Our audience is younger and more likely to engage with advertised brands than sports viewers on any linear network.”

Not to be outdone, Disney is preparing for what ad chief Rita Ferro described as the company’s “biggest year ever,” with cultural tentpoles including the Oscars, the Grammys, New Year’s Eve programming, the College Football Championship and — for the first time — a Super Bowl broadcast on both ESPN and ABC. The company expects to see a 55% increase in NFL impressions year over year, according to Ferro, and command 40% of all football impressions across the college and pro seasons. 

“In a marketplace where everyone is racing to assemble what we already have, Disney is in a category of one,” said Josh D’Amaro, during his first upfront presentation as Disney CEO.

Data is key

Aside from sports, all upfronts publishers positioned themselves as strongholds of consumer fandoms that drive engagement for brands using data-driven, artificial intelligence-powered technology. Those assets connect the dots between buying, optimizing and measuring campaigns across linear, streaming and beyond.

Perhaps no company can better stake its claim as the leader in data than Amazon. The tech giant now connects more than 300 million ad-supported consumers in the U.S. across its portfolio, giving Amazon the industry's largest authenticated reach — 90% of U.S. households — and helping reduce waste while generating higher click-throughs and conversions.

“These signals are not modeled. They’re not assumed. They’re built on trust,” said Tanner Elton, vice president of U.S. ad sales at Amazon, on stage at the upfronts. “These signals give us unparalleled precision. That precision drives performance, and that performance delivers outcomes that matter.”

Fox also trumpeted its reach of more than 200 million people every month across over 1 billion devices. It boasted of linear audiences that have increased by double digits over the last four years, a period where industry-wide linear audiences declined 33%. Growth has been spurred by Tubi, which Fox acquired in 2020, while the network in April retooled its advertiser solutions around the Fox AdStudio. The AI-supported offering features a converged audience graph that incorporates billions of data points and a measurement engine that provides reporting via more than 20 data partners.

“Engaged fans are your best customers. They’re 21% more likely to purchase your products and 30% more likely to remember your ads, which is exactly why we launched the Fox AdStudio and its suite of full-funnel measurement solutions,” Fox ad chief Jeff Collins said during the upfronts. “To date, AdStudio has delivered advanced outcome reports for over 1,000 campaigns showing double-digit lifts in key metrics like in-store sales and foot traffic.”

As part of its upfront presentation, Warner Bros. Discovery launched an Always-On Measurement & Attribution Dashboard that provides real-time visibility into campaign performance and enables in-flight optimization towards outcomes. Meanwhile, NBCU, a longtime innovator in data and measurement, said it plans to roll out its previously announced Performance Insights Hub in Q4 2026. The hub integrates measurement from leading firms like iSpot, VideoAmp and EDO and, at the ufpronts, NBCU revealed Instacart is serving as its exclusive CPG outcomes partner.

AI powers dynamic, contextual ads

Unsurprisingly, one of the main applications for data usage by media companies is building out AI-powered tools that look to make the advertising process more efficient and engaging. 

Amazon Ads continued to develop AI tools with the introduction at its upfront presentation of Dynamic TV Creative, a capability that automatically personalizes Interactive Video Ads based on viewer shopping behavior. The tool uses Amazon’s signals plus AI-driven creative optimization and campaign management abilities to adjust format, call-to-action, headline and details depending on where shoppers are in their journeys.

“This moves away from a one-size-fits-all approach, creating a more relevant experience for audiences while streamlining campaign management and execution for brands and helping their marketing dollars work harder,” said Fabrice Rousseau, director of CreativeX at Amazon Ads, in a press statement. 

The capability is currently available to select U.S. advertisers in categories including CPG, fashion and electronics that sell on Amazon via Prime Video campaigns. It will expand to more customers and inventories in Q3 2026, and is already being used by The Hershey Company.

Warner Bros. Discovery continued to build out its suite of solutions and formats for advertisers, even if the company’s acquisition by Paramount represents “the Ellison — I mean, the elephant — in the room,” as Bobby Voltaggio, co-president of U.S. Advertising Sales at WBD, joked during the presentation.

Along with shoppable pause ads that have been become table stakes for streaming services, WBD announced Scene Level Moments, contextual targeting powered by Kerv.ai; Dynamic Creative that adapts ad headlines and visuals contextually; and Agentic Experiences that tap into growing interest in agent-to-agent advertising. 

Likewise, Fox’s Ad Studio includes a contextual engine powered by an large-language model that connects brands to the content moments to provide ad insertion using scene-level targeting. NBCU also announced plans to expand contextual targeting and roll out always-on AI agents, while Netflix noted that its years of experience with AI and machine learning have helped advertisers including DoorDash, Target and TurboTax.

The rollout of AI tools across publishers meets advertisers where they are in their journeys with the technology. Four in 10 advertisers are testing AI creative in 2026 while over one third are exploring AI workflows and operations, per an iSpot report shared with Marketing Dive.

“The 2026 advertising environment is defined by a decisive pivot toward precision. Marketers have moved past the experimentation phase of AI, now integrating full-scale workflow automation to optimize efficiency,” according to iSpot’s 2026 Video Ad Spend and Strategy Report. “While spending forecasts remain cautiously optimistic amid economic shifts, budgets are increasingly concentrated in channels that offer the highest degree of accountability.”

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By Wrike

"Do more with less" is easy to say and hard to operationalize. For most teams, it means finding ways to boost output while cutting the manual tasks and constant context-switching that eat up the workday. Wrike's answer is Wrike agents — a no-code AI system that lets anyone build, deploy and manage automated workflows without writing a line of code.

Wrike first introduced AI agents in beta last October, then opened its agent builder to all users in February. Since then, the company has continued rolling out updates to both the builder and its integration capabilities.

What Wrike agents do

Wrike agents function as configurable digital teammates that handle repetitive, time-consuming work — tagging tasks, checking request readiness, summarizing project status and more — so teams can focus on higher-value work. Drawing on nearly two decades building workflow tools, Wrike ships three ready-made agents out of the box, each customizable to a team's specific needs. Users who want something more tailored can also build a fully custom agent from scratch using the no-code builder.

Built for speed and flexibility

A few features stand out:

No-code builder.

Teams can design their own agents in minutes, setting the actions, triggers, scope and frequency without technical expertise. A newly added conversational builder takes this further — users can simply describe the agent they want in plain language, and it will read the existing workspace (workflows, item types and so on) to build around how the team already operates.

Out-of-the-box agents.

Three preconfigured agents address common pain points: an *intake agent* that flags incomplete requests, a *triage agent* that routes work to the right person or team, and a *risk agent* that monitors project data and alerts managers to emerging issues. Wrike's user community has since built its own library of agents for tasks like resource allocation and stale-task escalation, some of which were showcased at the company's first agent build-off event.

Workflow integration.

Agents can be @mentioned directly inside comments for conversational follow-up, and now pull live project context to coordinate work across Slack, Microsoft Teams, Gmail and Outlook.

Centralized oversight.

A management console gives teams a single view of agent activity — active locations, recent updates, execution counts — making it easier to monitor performance and scale usage across the organization.

Early results from beta users

Feedback from beta customers points to meaningful time savings. One project management leader described the agents as effectively adding team capacity, noting that automating intake across departments cut hours of manual work each week. Other users report saving 10 to 15 minutes daily on tasks like auto-populating fields from task titles, while one team managing more than 50 projects estimated saving roughly 10 hours a week by automating status updates.

Users have also pointed to transparency as a differentiator — several noted that seeing the logic behind an agent's actions made the technology easier to trust, addressing a common concern that AI tools can feel like a black box. Wrike says it has incorporated this kind of feedback into recent releases, including new multi-action capabilities and interface refinements.

The bigger picture

By removing the technical barrier to building automation, Wrike agents extend a capability once reserved for IT teams to anyone managing a workflow. The aim is straightforward: fewer missed details, less manual triage and more time for the work that actually requires human judgment. For teams juggling growing workloads and shrinking bandwidth, that shift in who gets to build automation — not just who gets to use it — may be the more consequential change.

Adopters of artificial intelligence tools like OpenAI’s ChatGPT and Google Gemini are starting to set more of their brand preferences within chatbots. In the grand vision of technology developers, agentic AI will eventually identify relevant products, seek them out online and even shop, all with relatively little direct user input. That poses significant challenges to building and maintaining brand loyalty, according to new findings from the Gale agency.

The AI shift means marketers need to keep a closer ear to the ground with their communities while delivering experiences that have as little friction as possible to avoid putting off fickle customers. Over half, 56%, of surveyed consumers are now comfortable delegating the entirety of their communications with a brand through AI while nearly one-third have instructed an assistant to prioritize certain brands over others. 

“That’s pretty alarming,” said Gale CEO Andrew Noel. “They’re saying, ‘I will trust the [large-language model] to be my filter between me and a brand.” 

The agency’s report, titled “The Preference Economy,” envisions a world where a growing cohort of AI-savvy consumers architect the entirety of their commercial reality through a reliance on AI, raising existential questions around the role both marketing and loyalty play. Roughly a quarter of respondents indicated they will regularly set brand preferences with AI within the next year, but the potential addressable market for what Gale calls AI-native loyalty could balloon quickly as the technology becomes more ubiquitous.   

“You’re looking at 60% to 70%, in the next two to three years, [who] are going to instruct the LLMs to set their preferences, meaning I only want to really talk to these four or five [brands] because I prefer them,” said Noel. “If you’re brand side and you think about the technical implications of that, I think you’ve got a lot to think about.”

Great expectations

The AI disintermediation problem compounds an already volatile market for loyalty, including widespread feelings of indifference. The average consumer is enlisted in four to six loyalty programs, per Gale, but a meaningful chunk do not actively participate, making them “ghost members.” Gale surveyed 3,000 consumers in the U.S. and U.K. for its research.

Millennials and Gen Z represent the most meaningfully engaged loyalty cohorts but are also some of the pickiest. Younger consumers put a premium on seamless experiences and are quick to abandon brands that don’t deliver on this front. Among those aged 25 to 34, 61% dumped a brand for a competitor because of a superior loyalty experience, even though the actual rewards from the competitor’s program were worse.

“The expectations that millennials and Gen Z have, in particular when they interact with brands, is really high,” said Noel. 

Gen Z and millennials also happen to be leading the charge on AI adoption, but the AI conundrum isn’t contained to a certain age demographic. Across all respondents to Gale, including non-AI users, 47% trusted AI as a method for starting brand and product research while 16% expressed willingness to act on an AI’s recommendation without further debate. About a quarter of those surveyed were comfortable with AI learning about their brand preferences versus 20% who said the same for cookies and 17% for social media. Privacy concerns were more prevalent with older consumers while 27% of 25 to 34 year olds were not worried about the subject at all. 

“[A]mong the youngest consumers surveyed, the most common response wasn’t hesitation or resistance; it was that they simply hadn’t thought about it yet,” the Gale report reads. 

Breaking through 

The need to break through an increasingly automated world may lead marketers to again double down on first-party data following the cookie deprecation push of the early 2020s. A more direct understanding of customers’ behavioral patterns means brands will be able to better feed AI systems, according to Gale.   

“You’ll hear most CMOs today say we sit on a treasure trove of data, but not a lot of insights from it,” said Noel.

Strategies to adapt to the AI economy vary by category — a QSR will require a different approach than a big-box retailer — but Noel pointed to understanding community as a key differentiator. That could entail closer social listening on platforms like the chat app Discord to identify trends bubbling up in a community, or investing more in traditional tactics like surveying shoppers in the aisle for businesses with a large brick-and-mortar footprint. 

Harnessing those insights to inform personalization efforts will help maintain brand relevance as control of other aspects of the loyalty pipeline are taken over by AI. Prior Gale studies reveal that nearly 70% of consumers are more likely to join a loyalty program with an active community while 30% feel a stronger connection to a brand due to the social aspects of its loyalty offering. 

“You’ve got to be really dialed in on … the community management side of it. How do you really make people feel that they’re known and special to the brand?” said Noel.

At a time when marketing budgets are broadly under pressure due to macroeconomic volatility, and with more consumers trading down, another consideration is maintaining spend on loyalty programs. Too many marketers treat loyalty as a one-off discount program when AI is reinforcing the need for dynamism.      

“Just like you would with your media budget, the ongoing investment into the experience, into the mechanics and into the technology often that supports [loyalty] is a line item that I would encourage brands to think hard about more,” said Noel. 

Google has frequently emphasized how generative artificial intelligence is making search habits more winding and complex, transforming a channel that remains the core pillar of its business. A wide-ranging suite of advertising and commerce products announced at the company’s Marketing Live summit in May 2026 show how the tech titan is adapting brand experiences to better gel with a more conversational era for search while reducing friction between AI agents and purchases. Some of these new tools also enable advertisers to tap into agentic marketing capabilites underpinned by Gemini for more seamless campaign creation, management and reporting. 

Take Ask Advisor, which rolls out later in 2026 and is positioned as providing a unified entry point for in-product agents across Google Ads, Google Analytics, Google Marketing Platform and Google Merchant Center. A haircare brand that wants to identify a new set of customers could tap Ask Advisor to draw up product details from Merchant Center and launch a Google Ads campaign in one swoop, explained Dan Taylor, vice president for global ads at Google. Similarly, Ask Advisor could automatically compile a performance report based on data from both Google Ads and Google Analytics without the marketer needing to do a deep dive into each platform individually.  

“On the back end, our agents talk to one another and carry each other’s content, creating a continuous thread of intelligence,” said Taylor of Ask Advisor during a virtual press briefing ahead of Google Marketing Live.  

Google is also updating Asset Studio, a hub for creative asset generation that entered beta in August 2025, with fresh Gemini Omni horsepower. Other digital platforms like Amazon are similarly building out one-stop shops for advertising that pose a threat to traditional marketing services providers.

“Brands can now use natural language to describe their goals and upload their marketing brief directly in Asset Studio,” said Taylor. “This means marketers can instantly create a range of high-quality, on-brand assets across text, images and video all at once with a few words or a full marketing brief.”

The Marketing Live bonanza followed Google’s I/O event for consumer products earlier in May, where it debuted a revamped search experience that makes AI a higher priority, including through new customizable “information agents,” and further deprecates the traditional 10 blue links approach. These tweaks come as Google faces stiffer competition from AI startups like OpenAI and Anthropic, and is expected to be surpassed in ad revenue by Meta Platforms for the first time in 2026, according to some industry analysts. 

Adapting search for AI interfaces

Roughly a year after first integrating ads to AI Mode, Google detailed two new explainer advertising formats, Conversational Discovery and Highlighted Answers, that it purports are better tailored to how consumers engage with the feature focused on in-depth chatbot conversations. AI Mode, which has over 1 billion monthly users, will now be powered by the more advanced Gemini 3.5 Flash model globally, Google said at I/O. 

Conversational Discovery assesses the context of involved, specific user queries — for example, “How to make a house smell like a high-end spa in a low-maintenance way?” — and spins up custom ad creative from relevant businesses. Highlighted Answers generates a list of curated recommendations based on searches like looking for the best language-learning app for an upcoming trip. An advertiser can slot into that list assuming it is relevant, and Google emphasized that any sponsored picks will be clearly labeled as such.    

“These formats are rethinking not only how the ads look, but also the value they provide, because ultimately the best ads are just answers,” said Taylor.

In the core search experience, Google is rolling out AI-powered Shopping ads for high-consideration purchases that include explainers about why the advertiser’s product is the right choice. AI-powered Shopping ads will be available in the U.S. later in 2026. 

Another new AI format that tries to go deeper on complex searches is called Business Agent for Leads, which is now in beta in the U.S. A student exploring the right university to attend could click on an ad to instantly chat with an agent that is trained entirely on the advertiser’s website, removing the need to fill out a static form. 

“These ads show when relevant not just to the person’s query, but also the AI Overview response,” said Taylor. 

Tying AI to transactions

Google I/O saw the unveiling of an agentic Universal Cart shopping tool that will be available across multiple Google platforms, including search, YouTube and Gmail. A theme running through Marketing Live was helping merchants create incentives that could encourage transactions while shortening the window to checkout.

For example, Google is expanding Direct Offers, which entered a pilot in January 2026 as a way for retailers to present deals directly in AI Mode ads. Direct Offers will now allow advertisers to upload a variety of discounts, giveaways and coupons and leverage Gemini to match or combine the most relevant offers into a relevant bundle based on a user’s search. The format, which has already been used by brands including Chewy, Gap and L'Oréal, will soon expand to travel platforms like Expedia and Booking.com.  

“Direct Offers are fundamentally different from Shopping ads because they use the deep context of an AI Mode conversation to serve a tailored deal when someone's ready to buy,” Taylor explained.  

To ensure consumers can easily claim these offers, Google is also implementing a native checkout experience within AI Mode, meaning users do not have to leave the feature to complete a purchase. Native checkout is available to merchants using Google’s Universal Commerce Protocol, its open standard for agentic commerce that was unveiled at the start of 2026 in collaboration with partners like Walmart, Target and Shopify.  

“UCP solves a very core challenge of scaling agent e-commerce across the entire web by defining a common language which allows agents to connect to businesses securely and seamlessly,” said Ashish Gupta, vice president and general manager of merchant shopping at Google.

UCP is broadening in several other ways, including through multi-item checkout so merchants can receive larger order value; a buy-now, pay-later option supported by Google Pay; and an upcoming checkout capability in YouTube ads so viewers can more easily buy items they see either on mobile or connected TV. For consumers who do not want to complete purchases through Google’s services, they can also now transfer items directly to the merchant site. 

“Regardless of how and where the customer completes their purchase, the retailer always remains the merchant of record with UCP,” said Gupta. 

Procter & Gamble is emphasizing its strengths in data and artificial intelligence as the packaged goods giant contends with a fragmented “new media reality,” executives said on a call discussing earnings in January 2026. The owner of brands like Tide and Downy is working to redefine its brand-building framework to deliver more relevant marketing and better capitalize on emergent channels like retail media that are rewriting the CPG advertising playbook.   

“Retailers are becoming media platforms and media platforms are becoming retailers. In summary, the consumer path to purchase is changing every day, is nonlinear and littered with millions of possible distractions,” said P&G President and CEO Shailesh Jejurikar on the call with financial analysts. “We expect an even more intense pace of change in the next three to five years. We will adjust to and leap ahead of these disruptions to invent the CPG company of the future.”

The executive, who took over the top spot from Jon Moeller at the start of 2026, underlined P&G’s “enormous wealth of consumer data” as a competitive advantage. P&G’s data touchpoints include some traditional methods, including product and shopper research, but also sources like social media posts and fan websites for particular brands. 

The CPG is mining those areas to inform product innovation and marketing campaigns, among other functions, according to Jejurikar. In addition, P&G is turning to AI to get a better understanding of what consumers are looking for and to leverage those insights to make its brands more memorable. 

“AI and [generative] AI capability help our teams discover consumer-relevant insights at every step of the consumer path to purchase, grounded in a unifying brand idea,” said Jejurikar. “These ideas are activated in claims, demonstrations [and] visuals that communicate the performance and value of the brand across connected and broadcast TV, online video, social media, e-commerce sites and in stores.”

Jejurikar’s comments were delivered around P&G’s earnings for its fiscal Q2 2026, a period that saw net sales inch up 1% compared to the year-ago period to $22.2 billion, with sluggishness in the key U.S. market. P&G upheld guidance that sales growth should land between 1% to 5% for its full fiscal 2026 year, which ends in June. Jejurikar also said he would expand further on how he is preparing P&G to be a CPG company of the future at the CAGNY conference in mid-February.  

Agencies are racing to prepare for the artificial intelligence era of advertising, enacting significant restructurings and acquisitions while standing up scaled AI solutions. Some analysts are skeptical about how far these bets can really go, stoking fresh uncertainty for an agency sector that is betting the farm that AI will reignite growth.

Half of agencies’ proprietary AI platforms will either wind down or become obsolete by 2029, researcher Gartner predicts. That’s because agency-built offerings need to contend with the rise of open-source AI platforms developed by what are known as hyperscalers — the Googles and Amazons of the world — that can service functions beyond marketing, according to Gartner. Open-source platforms are expected by Gartner to support more than 75% of enterprise AI deployments by 2028, gaining traction for their level of customization and favorable cost compared to proprietary platforms.

“I don't hear [agencies] talking about those platforms, whether it’s [WPP] Open or Omni or anybody else, being an enterprise-wide AI platform,” said Jay Wilson, vice president, analyst at Gartner for Marketers. “That’s the big disconnect or the big risk to agencies right now. They’re still kind of thinking at the marketing level, at the advertising level, maybe getting into CX.”

The threat of hyperscalers is tied up in the broader organizational influence, or lack thereof, CMOs wield on the client side of the business. While many marketing decision-makers have been early adopters of AI for tasks like content creation, chief information officers and related roles will more likely make the final call on what AI tools brands choose to adopt across the enterprise, according to Wilson. 

“Essentially, we believe that at an enterprise-wide level, the CIO is going to own that enterprise AI strategy, and a CMO who’s basically embedding with a WPP or an Omni or a Dentsu or whatever, is likely going to get disintermediated from that discussion,” said Wilson.

Weighing the risks

Agencies currently provide a lot of value in helping brands navigate AI disruption, per Wilson, including through upskilling, speed to market and drawing on knowledge from a wide client base and global reach. 

“What an agency provides that is not tech-dependent — meaning cannot be as easily commoditized — is that outside-in perspective on a client's business,” said Wilson.

Still, Gartner recommended that CMOs not become overly reliant on agency-built AI platforms, since agency relationships are liable to churn over time. Similarly, the costs and complications of migrating to different agency AI platforms could be cumbersome. The researcher suggested CMOs avoid locking into long-term contracts related to AI and instead push for initial proofs of concept and the right to terminate agreements without incurring penalties. 

Meanwhile, agencies need to consider how they can differentiate as the technology category at large becomes more democratized, commoditized and open source. The push from the ad-holding groups to master AI has dovetailed with a painful period of contraction, inclusive of heavy rounds of layoffs and the elimination of some legacy agency brands. The hit to the talent pipeline now could spell more trouble down the line, as qualitative capabilities and a degree of human discernment may be more important in the long run. 

“The agency value goes back to what the traditional agency values have been, which have been creativity, innovation and customer insight,” said Wilson. “Agencies can still provide value in applying the art on top of the science of AI.”

Since OpenAI released ChatGPT in November 2022 and kicked off the modern era of artificial intelligence in media and marketing, brands and agencies are increasingly shifting from asking the “whys” about the technology to answering the “hows." The challenges that advertisers face as AI increasingly impacts their businesses were a topic at the Interactive Advertising Bureau’s annual Public Policy & Legal Summit in March 2026.

“AI has already staked its claim on the digital advertising industry, promising to streamline and disrupt how we have typically done business,” IAB CEO David Cohen said in opening remarks.

In an example of AI-driven transformation, WPP has spent the last few years moving from tapping AI to drive efficiencies in certain use cases to undertaking larger organizational moves to centralize the technology. Through its WPP Open initiative, the ad-holding group has united AI efforts across creative, production and media teams and realized iterative improvements.

“The tools have been out there for a few years,” said Michael Palmer, vice president and transformation lead in North America at WPP Media, during a panel at the summit. “As an organization, we can finally leverage them in a coordinated and actually even manner across the board, and that muscle has been the real story.” 

WPP has put the onus for AI governance at the holding company level rather than the operating company level as the capital expenditures for AI technology and expertise are too high for its subsidiaries to manage — a pattern that is happening across WPP’s competitors, Palmer said. 

Yum Brands, the parent company of Taco Bell, KFC, Pizza Hut and Habit Burger, has also spent the last few years operationalizing AI across its organization, harnessing its brands’ first-party data to build a so-called “AI factory.” For Nicholas Godlove, global privacy counsel at Yum Brands, it was important to get as many stakeholders to the table as possible by setting up a formalized committee that wasn’t just “legal saying ‘no’ all the time.”

“It needs to be a conversation to get these things in place, much more than a lot of member relationships and a lot of technology,” Godlove said. “It is a conversation [about], ‘Where can I do? When can I do it? What are the guardrails?’”

How AI is and isn’t working

AI has often been billed as a panacea for improving many of the marketing functions that companies like WPP offer, spanning solutions for creative, media buying, analytics and strategy. So far, the technology is working for WPP in many of the expected areas, including shaping creative ideation, building media plans and cutting down the timeline for certain tasks from days to hours. But by the nature of how they work, generative AI tools built on large-language models and transformers cannot generate anything totally novel or unique. 

“A lot of the tools from the last two or three years have made mediocrity cheap, but they have actually made excellence much more prized,” Palmer said.

As for how AI is reshaping the agency workforce, back office and support roles that can be automated have been the first to go, like the legions of media planners and accountants that used to fill floors of holdco offices. That will likely continue amid the rise of agentic AI, but AI-powered systems still need “humans in the loop” to control and contextualize outputs.

“Look for your operational pain point experts and empower them. That’s what we’re doing,” Palmer said of WPP’s AI work. “We’re really looking to push and enable with our expertise — our people are our best asset as an agency — so we are structuring the entire setup internally for us to basically have better, more efficient output from those individuals.”

As a marketer of restaurant brands, Yum has opportunities to use AI across loyalty programs, menu screens and drive-thrus, among other areas. For Gen Z consumers who already blanch at making phone calls or using traditional websites, there could be an opportunity for Yum to collaborate with OpenAI or another provider of agentic AI, Godlove suggested, with some caveats. 

“The question is: Is there a business risk? Yes. Is there reputational risk? Yes. Is there a technical risk? Yes. Is there legal risk? Yes. Where are you comfortable doing that? I think for us, we are really trying to focus on a lot of the operational questions,” Godlove said.

Beyond the levels of risk, operational questions will differ by category and industry. For Taco Bell, it takes a lot of training data to introduce concepts like “chalupa” or “quesarito” into an AI model, Godlove offered as an example.

Where AI is going

AI use at advertisers and agencies also differs by employee age. At WPP, Gen Z employees are at the spear point of experimentation and adoption, and the cohort’s use of the technology is monitored by older managers. While the push is coming from younger ranks, some of the best users of AI are Gen Xers who already have a great sense of tools, bottlenecks and friction points in existing workflows. No matter their age, employees have been encouraged to use internal AI solutions, rather than publicly available ones, so that client data doesn’t go out to general models.

“We’ve gotten quite strict about that,” Palmer said of the AI use policy. “We didn’t want to stop the experimentation or its use, but we basically paid a substantial amount of money, a huge upfront investment, to get those tools. We want to make sure everybody at office is using the proper tooling.”

The next step for AI development is around agentic tools that are fully autonomous and have quickly become the focus of agencies, ad-tech companies and industry bodies. WPP opened 2026 by launching an Agent Hub for client and employee use, and the network will be standing up agentic pilots with several publishing partners in the coming months, Palmer indicated.

“Maybe in five years, maybe 10, we might be advertising to agents… That sounds like ‘Jetsons’ stuff, but we’re definitely going in that direction,” Palmer said. “As a brand, you may have to start placing agent-targeted advertising.”

While AI capabilities have improved in recent years, the rise of agentic AI presents a quandary as to what a corporation is and does when parts of the company are not human or human-controlled. Yum’s Godlove pointed to the possibility of “semi-intelligent, semi-rogue actors” with access to data and the ability to make decisions.

“Skynet,” said moderator Gary Kibel, a partner at Davis+Gilbert LLP, in a nod to the “Terminator” film franchise. “Sounds like a fun world.”