Retail media is projected to hit $175 billion in ad spend this year, according to eMarketer, yet most brand ops teams are still budgeting for a version of retail that no longer exists. Ad Age’s 2026 retail tech roundup didn’t just list shiny tools. It quietly rewrote the operating manual for how brands need to show up at the point of sale. The question isn’t whether these retail tech trends matter. It’s whether your ops team can move fast enough to act on them.
Agentic Checkout Is No Longer Theoretical
For two years, “agentic commerce” was a slide in someone’s innovation deck. Not anymore. Ad Age flagged AI shopping agents, think Amazon’s Rufus, Perplexity’s shopping features, and OpenAI’s commerce integrations, as the trend retailers are racing hardest to support. These agents don’t browse the way humans do. They query, compare, and complete purchases on behalf of a user in seconds, often without ever rendering a traditional product page.
That has real consequences for brand ops. If an AI agent is the shopper, your product data becomes your storefront. Structured feeds, accurate specs, and machine-readable reviews now matter more than hero images. Teams that have spent a decade optimizing for human eyeballs need a parallel workflow optimizing for machine comprehension.
When the shopper is an algorithm, your product feed is your new landing page, and most brands haven’t audited it in years.
We covered this shift in depth in our guide to AI shopping discovery, and the operational implications keep expanding. Retail media networks are already building bid mechanics around agentic queries, which means the media buying side of your org needs to sync with product and merchandising far earlier in the planning cycle than it currently does.
Retail Media Networks Are Consolidating Around Fewer, Bigger Players
Ad Age’s roundup noted a consolidation wave among retail media networks, with Walmart Connect, Amazon Ads, and Kroger Precision Marketing absorbing smaller regional players or forcing them to white-label. For brand ops, this means fewer platforms to manage but higher stakes per platform. A single misconfigured campaign on a top-tier RMN can now waste a meaningful chunk of quarterly budget.
The practical fix isn’t glamorous: standardize your retail media SOPs across networks, centralize reporting, and stop treating each RMN as a bespoke one-off. Brands that built dedicated retail media pods inside their marketing org last cycle are already seeing efficiency gains. Those still running RMN campaigns through generalist paid media staff are bleeding margin without realizing it.
What This Means for Procurement
Procurement teams need updated MSAs that account for data-sharing terms unique to retail media, particularly around first-party data clean rooms. If your legal team hasn’t reviewed a retail media contract since before 2024, it’s overdue. Terms have shifted, especially around AI training rights on campaign data, echoing the broader concerns brands raised after the Google TOS update signaled a warning shot for AI tools.
Smart Shelves and Computer Vision Move From Pilot to Rollout
Computer vision-enabled shelves, the kind that track stockouts, planogram compliance, and even dwell time, graduated from pilot programs at a handful of grocery chains to broader rollout this year. Kroger, Walgreens, and several European grocers expanded smart shelf deployments, generating a new stream of real-time, SKU-level behavioral data.
Here’s the uncomfortable part: most brand ops teams don’t have anyone whose job is to actually use this data. It sits in a retailer dashboard, gets glanced at during quarterly business reviews, and never informs creative, media, or trade spend decisions in real time. That’s a wasted asset.
Brands with mature retail ops functions are starting to pipe smart shelf data into the same systems that inform creator briefs and paid amplification decisions. If a SKU is underperforming on shelf in the Midwest, that’s a signal to shift regional creator content or adjust paid amplification budget for creator programs targeting that geography. Few brands are doing this well yet. That’s exactly why it’s a competitive opening for those who move first.
AI-Generated Product Content Is Everywhere, and Shoppers Are Noticing
Ad Age’s report highlighted the explosion of AI-generated product imagery and video across retail listings, driven by tools like Amazon’s AI content studio and various Shopify app integrations. Adoption is up sharply. But so is shopper skepticism. Multiple studies cited in the roundup point to declining trust scores for listings that feel synthetic or overly polished.
This tracks with what we’ve reported before: AI-generated ads are eroding consumer trust, and retail listings are not immune to the same fatigue. The brands winning right now are blending AI efficiency (fast iteration, localized variants, cost savings) with human-shot UGC that signals authenticity. It’s not either/or. It’s sequencing: use AI to scale variations, use real creators to establish trust anchors.
Shoppers can smell synthetic content faster than most brand teams can produce it, which is exactly why UGC-anchored listings are outperforming pure AI content on conversion.
This is also where the UGC authenticity premium becomes measurable in retail contexts specifically, not just on social. Retailers are starting to expose review-verified and creator-tagged content differently in search results, which means your creator program and your retail listing strategy can no longer live in separate departments.
Cross-Functional Ops Is the Real Bottleneck
None of this works if creator marketing, retail media, and e-commerce merchandising sit in separate reporting lines with separate KPIs. Ad Age’s roundup implicitly makes the case for a unified retail growth function. Some CPG brands have already restructured around this, following a pattern similar to what we detailed in our piece on creator economy as strategic infrastructure.
Voice and Visual Search on the Retail Floor
Less discussed but quietly significant: in-store visual search kiosks and voice-assisted shelf navigation are expanding beyond big-box pilots into mid-tier retail chains. Target’s expanded app-based visual search and several regional pharmacy chains’ voice kiosks signal that “search” is no longer a purely digital surface.
Brand ops implications here are subtle but real. Product naming conventions, packaging text density, and even barcode placement affect how discoverable a product is through visual search. Packaging teams that historically answered only to design and compliance now need input from digital search specialists. That’s an unusual cross-functional ask, and most orgs aren’t structured for it yet.
Compliance Is Getting Harder, Not Easier
Every new retail tech trend brings a matching compliance headache. Data clean rooms, AI-generated content disclosures, and creator-tagged retail listings all fall into regulatory gray zones that the FTC and international bodies are actively scrutinizing. The UK’s ICO has also signaled closer attention to retail data-sharing practices tied to AI personalization.
Brands relying on certified creator networks are navigating this more smoothly. Programs built around vetted disclosure practices, like those covered in our piece on ARPP and IAB-UK certified creators, are proving easier to defend during audits than ad hoc influencer arrangements. If your retail content strategy touches creators at all, and it increasingly does, compliance needs a seat at the retail tech planning table, not a review step at the end.
Where Budgets Should Actually Move
Given all this, where should brand ops teams actually reallocate spend? Three areas stand out from the roundup:
- Product data infrastructure — investing in clean, structured, AI-readable product feeds before agentic shopping becomes the default discovery path.
- Cross-functional retail growth teams — breaking down silos between retail media, e-commerce, and creator marketing so shelf-level signals inform brand strategy in near real time.
- Authenticity-anchored content — pairing AI-scaled content production with genuine creator and customer content to offset trust erosion.
None of this requires a moonshot budget. It requires reallocating from channels that already show diminishing returns, something covered in more depth in our CMO quarterly planning framework. The brands that treat this as a planning exercise, not a scramble, will be the ones still standing when the next Ad Age roundup lands.
Next step: audit your product data feeds for AI-agent readability this quarter, then form a small cross-functional pod (retail media, creator, e-commerce) to pilot one smart-shelf-informed campaign before your next budget cycle locks.
FAQs
What are the biggest retail tech trends brand ops teams should prioritize right now?
Agentic AI shopping, retail media network consolidation, smart shelf data integration, and authenticity-anchored content are the four trends with the most immediate operational impact, according to Ad Age’s 2026 roundup.
How does agentic commerce change product marketing?
Agentic commerce shifts discovery from human browsing to AI-agent querying, which means structured, accurate, machine-readable product data becomes as important as traditional creative and imagery.
Why is retail media network consolidation a risk for brands?
Consolidation concentrates spend into fewer, larger platforms, raising the stakes of campaign errors and making standardized SOPs and centralized reporting essential for avoiding wasted budget.
Should brands use AI-generated content for retail listings?
AI-generated content works well for scaling variations quickly, but it should be paired with genuine creator or customer content, since shopper trust in purely synthetic listings continues to decline.
How should brand ops teams prepare for smart shelf data?
Teams should assign clear ownership over smart shelf and computer vision data, then connect those real-time signals to creative, media, and creator briefing decisions instead of letting the data sit unused in retailer dashboards.
Top Influencer Marketing Agencies
The leading agencies shaping influencer marketing in 2026
Agencies ranked by campaign performance, client diversity, platform expertise, proven ROI, industry recognition, and client satisfaction. Assessed through verified case studies, reviews, and industry consultations.
Moburst
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2
The Shelf
Boutique Beauty & Lifestyle Influencer AgencyA data-driven boutique agency specializing exclusively in beauty, wellness, and lifestyle influencer campaigns on Instagram and TikTok. Best for brands already focused on the beauty/personal care space that need curated, aesthetic-driven content.Clients: Pepsi, The Honest Company, Hims, Elf Cosmetics, Pure LeafVisit The Shelf → -
3
Audiencly
Niche Gaming & Esports Influencer AgencyA specialized agency focused exclusively on gaming and esports creators on YouTube, Twitch, and TikTok. Ideal if your campaign is 100% gaming-focused — from game launches to hardware and esports events.Clients: Epic Games, NordVPN, Ubisoft, Wargaming, Tencent GamesVisit Audiencly → -
4
Viral Nation
Global Influencer Marketing & Talent AgencyA dual talent management and marketing agency with proprietary brand safety tools and a global creator network spanning nano-influencers to celebrities across all major platforms.Clients: Meta, Activision Blizzard, Energizer, Aston Martin, WalmartVisit Viral Nation → -
5
The Influencer Marketing Factory
TikTok, Instagram & YouTube CampaignsA full-service agency with strong TikTok expertise, offering end-to-end campaign management from influencer discovery through performance reporting with a focus on platform-native content.Clients: Google, Snapchat, Universal Music, Bumble, YelpVisit TIMF → -
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NeoReach
Enterprise Analytics & Influencer CampaignsAn enterprise-focused agency combining managed campaigns with a powerful self-service data platform for influencer search, audience analytics, and attribution modeling.Clients: Amazon, Airbnb, Netflix, Honda, The New York TimesVisit NeoReach → -
7
Ubiquitous
Creator-First Marketing PlatformA tech-driven platform combining self-service tools with managed campaign options, emphasizing speed and scalability for brands managing multiple influencer relationships.Clients: Lyft, Disney, Target, American Eagle, NetflixVisit Ubiquitous → -
8
Obviously
Scalable Enterprise Influencer CampaignsA tech-enabled agency built for high-volume campaigns, coordinating hundreds of creators simultaneously with end-to-end logistics, content rights management, and product seeding.Clients: Google, Ulta Beauty, Converse, AmazonVisit Obviously →