As digital platforms flood advertisers with more video, more creators, and more ambiguity, brand suitability has quietly become one of marketing’s hardest technical problems. Zefr thinks it has found a better way to solve it—and the U.S. Patent and Trademark Office agrees.

The brand suitability and media intelligence company has been granted a new U.S. patent for its AI-driven approach to content annotation and model distillation, a system designed to dramatically improve how digital content is analyzed, classified, and ultimately deemed safe (or risky) for advertisers.

This is not just another incremental AI filing. The patent formalizes how Zefr combines large language models (LLMs), AI agents, and targeted human review to tackle one of the industry’s most persistent challenges: understanding context at internet scale without sacrificing nuance.

Why content annotation still breaks at scale

Most content classification systems today fall into one of two camps. On one side are heavily manual operations, where large reviewer teams label content with human judgment—but at a cost that doesn’t scale with YouTube, TikTok, or emerging video platforms. On the other side are fully automated systems that scale beautifully, right up until they misclassify satire as harm, fiction as reality, or cultural references as violations.

Zefr’s newly patented approach aims to close that gap.

Instead of using humans to annotate everything—or machines to decide everything—the company deploys AI agents to scan massive video datasets and actively look for uncertainty. Ambiguous cases, underspecified scenarios, or content that sits at the edge of policy definitions are flagged and escalated for human review. Clear-cut cases are handled automatically.

The result is a system that focuses human expertise where it matters most, rather than wasting it on obvious calls.

Teaching machines when they don’t know enough

At the core of the patent is the idea that AI shouldn’t just classify content—it should understand when its own confidence breaks down.

Zefr’s system uses LLMs to query and explore large volumes of video content, surfacing examples that challenge existing policy boundaries. These edge cases are then reviewed by human experts, whose decisions don’t just resolve individual annotations but are fed back into the models through a process known as model distillation.

In practical terms, this means the AI gets smarter over time—not by brute-force labeling, but by learning from the hardest, most instructive examples.

It’s a sharp contrast to traditional annotation pipelines that rely on volume rather than insight, and it reflects a broader shift across enterprise AI toward more deliberate, human-guided learning loops.

Context over keywords—and why advertisers care

One of the most compelling aspects of Zefr’s approach is its ability to distinguish between content that looks similar on the surface but means something very different in context.

A fictional crime scene in a TV show trailer is not the same as footage of real-world criminal activity. A news report discussing extremism is not extremist propaganda. For advertisers, those distinctions determine whether campaigns appear next to content that aligns with brand values—or sparks backlash.

By combining automated discovery with human policy guidance, Zefr’s system can make these finer distinctions consistently, at scale. That translates into more confident media buying decisions, fewer false positives, and less blunt exclusion of entire content categories.

In an era where advertisers are demanding both reach and responsibility, that balance is increasingly non-negotiable.

A signal of where brand safety tech is heading

Zefr’s patent arrives at a moment when brand safety and suitability are being reshaped by three converging forces: the explosion of short-form video, the growing use of generative AI, and increased scrutiny from regulators and brand leaders alike.

Competitors across the ad verification and media intelligence landscape are racing to incorporate AI, but many still rely on opaque models or legacy taxonomies that struggle with modern content formats. Zefr’s emphasis on transparency, explainability, and peer-reviewed research positions it differently—closer to an AI lab with commercial instincts than a traditional verification vendor.

“This patent represents another major step forward in our mission to bring transparency and trust to the digital ecosystem,” said Jon Moora, Chief AI Officer at Zefr, pointing to the company’s focus on accountability as much as automation.

That framing matters. As AI increasingly governs where ads appear, advertisers are asking tougher questions about how decisions are made—and who is responsible when systems get it wrong.

Building an IP moat around responsible AI

The newly granted patent is Zefr’s eighth overall and its second specifically focused on AI, adding to a growing intellectual property portfolio that spans content understanding, brand suitability, and machine learning systems.

More importantly, it signals a strategic commitment to defensible, responsible AI development at a time when many ad tech players are bolting generative models onto existing workflows without rethinking the fundamentals.

Zefr’s approach suggests that the future of brand suitability won’t be fully automated or fully manual, but intentionally hybrid—machines handling scale, humans providing judgment, and systems designed to know the difference.

For marketers navigating an increasingly complex media landscape, that may be less flashy than pure automation, but it’s far more useful.

Get in touch with our MarTech Experts.

As the gambling and iGaming market matures—and competition intensifies—visibility alone is no longer enough. Brands now have to balance growth with trust, regulation, and reputation across an increasingly fragmented digital landscape. That’s the opportunity 5W is aiming to capture with the expansion of its gambling PR and digital marketing services.

The independently owned U.S. PR firm announced it is broadening its offering for iGaming operators, sports betting platforms, casinos, esports brands, and gaming studios, positioning itself as a full-spectrum partner as the industry looks toward 2026. The move reflects a wider shift in the sector: gambling brands are investing less in isolated campaigns and more in integrated strategies that combine PR, performance marketing, and brand safety.

A bundled approach to growth and credibility

At the core of 5W’s expanded offering is integration. Rather than treating PR, digital marketing, and reputation management as separate disciplines, the firm is packaging them into a single, coordinated strategy designed to drive both awareness and measurable growth.

The services span traditional media relations and influencer partnerships alongside digital-first tactics such as SEO, content creation, social media campaigns, email marketing, and event promotion. Online reputation management and crisis communications are also central to the offering—a critical component for gambling brands operating under regulatory scrutiny and public trust concerns.

For iGaming and betting companies, this approach addresses a long-standing challenge: how to grow aggressively without triggering backlash from regulators, platforms, or consumers. By aligning earned media with search visibility and social credibility, 5W is betting that trust will become as important a performance metric as acquisition.

Digital PR takes center stage

One notable emphasis in the expansion is digital PR, which 5W positions as a way to strengthen credibility across both search and social platforms. As Google continues to reward authoritative, trustworthy content—and social platforms tighten policies around gambling promotion—earned coverage and high-quality backlinks have become increasingly valuable.

For gambling brands, digital PR also plays a defensive role. Strong brand narratives and consistent visibility can help offset sudden policy changes, ad restrictions, or algorithm updates that often disrupt paid acquisition channels. In that sense, PR is no longer just about headlines; it’s part of the growth stack.

This aligns with a broader MarTech trend: brands are blending PR and SEO more closely, treating media coverage as both a reputation asset and a performance lever.

Preparing for a tougher 2026

The timing of the expansion is telling. As the industry moves toward 2026, operators face tightening regulations in several markets, higher customer acquisition costs, and a crowded competitive field that includes global sportsbooks, local operators, and digital-native gaming studios.

Standing out now requires more than promotional spend. It requires consistent messaging, strong partnerships, and the ability to respond quickly when issues arise—whether that’s a compliance concern, a platform crackdown, or a public relations crisis.

“Our expanded gambling and gaming PR and digital marketing services are designed to help brands enter 2026 with momentum,” said Ronn Torossian, Founder and Chairman of 5W. His emphasis on integration reflects a growing realization across the sector: fragmented marketing efforts are no match for an ecosystem where trust, transparency, and brand perception directly impact revenue.

Why this matters for MarTech leaders

For marketers in gambling and gaming, 5W’s move underscores a larger shift in how growth is being approached. Performance marketing alone is becoming less predictable, while brand-led strategies—supported by data, content, and reputation management—are gaining renewed importance.

It also highlights how PR firms are evolving. No longer confined to press releases and media outreach, agencies like 5W are repositioning themselves as hybrid partners that sit at the intersection of communications, MarTech, and growth strategy.

As gambling, esports, and iGaming brands look ahead, the firms that can combine reach with responsibility—and visibility with trust—are likely to be the ones that endure.

Get in touch with our MarTech Experts.

As AI reshapes how people search, discover, and decide, marketing agencies are being forced to rethink both their tools and their footprint. Interact Marketing is making a bet on both. The agency has opened a new office in Jamestown, New York, expanding its regional presence while sharpening its focus on AI-driven search and performance-led media strategies.

The new office is located in the top-floor suite of the historic Fenton Building, a space with an unusual pedigree: it once housed the office of U.S. Supreme Court Justice Robert H. Jackson. The move coincides with Interact Marketing entering its 19th year in business—a milestone that reflects both longevity and adaptation in an industry defined by constant change.

A physical expansion tied to digital disruption

At first glance, opening a new office might seem like a traditional growth move. In Interact Marketing’s case, it’s tightly linked to how search and media are evolving.

The Jamestown location supports the agency’s expanded capabilities around AI-driven search platforms, including Google AI Overviews, Google AI Mode, ChatGPT, and other emerging AI-powered discovery tools. These offerings are not experimental add-ons; they are the result of technology and workflow investments the agency has been building over the past two years.

As search engines increasingly answer queries directly—and as large language models become part of the discovery journey—brands face a new challenge: visibility is no longer just about ranking blue links. Interact is positioning itself to help clients adapt to that shift, optimizing for how AI systems interpret, summarize, and surface content.

Why SEO still sits at the center

Despite the expansion into new media formats, Interact Marketing is clear about what anchors its strategy: search engine optimization.

The agency continues to treat SEO as more than a traffic channel. Instead, it uses search data to map purchase intent, inform media planning, and improve efficiency across paid and owned channels. In a fragmented media environment, search insight acts as connective tissue—linking awareness, consideration, and conversion.

That philosophy explains why SEO remains central even as the agency expands into geofence advertising, streaming TV, podcast advertising, and social media retargeting. These channels benefit from search intelligence, particularly when budgets are under pressure and marketers need clearer signals about intent and timing.

This approach reflects a broader MarTech trend: SEO is increasingly being used as a planning layer, not just a performance metric.

Expanding reach across the Great Lakes region

The Jamestown office also strengthens Interact Marketing’s regional footprint across Western and Central New York and nearby markets, including Buffalo, Erie, Pittsburgh, and Cleveland. While the agency has served national clients since its founding, the expansion reflects ongoing demand for local accessibility.

For many mid-market and enterprise brands, proximity still matters—especially for strategy sessions, quarterly planning, and complex integrations that benefit from in-person collaboration. Interact’s move suggests that even as marketing becomes more digital, relationships remain stubbornly human.

“This expansion opens up significant new market opportunities for us across Western New York and the Great Lakes region,” said CEO Joe Beccalori. His comments point to a reality many agencies are rediscovering: hybrid models—national scale combined with local presence—can be a competitive advantage rather than a contradiction.

An agency model built for what comes next

Founded in 2007, Interact Marketing has spent nearly two decades navigating algorithm updates, platform shifts, and now, the rapid rise of AI in search and advertising. Its reputation has been built on technical SEO, data-driven strategy, and performance-focused media planning—disciplines that are being tested, but not replaced, by AI.

The Jamestown expansion signals confidence that the next phase of growth won’t come from chasing every new channel, but from integrating emerging technologies into a coherent strategy. AI-powered search, connected TV, and location-based advertising are not standalone tactics; they’re components of a broader system informed by intent, data, and long-term client relationships.

In an industry often obsessed with speed and scale, Interact Marketing’s move suggests a different kind of maturity: investing in infrastructure, deepening expertise, and expanding thoughtfully—both digitally and geographically.

Get in touch with our MarTech Experts.

Integral Ad Science is making a clear statement about where ad verification and optimization are headed. The company has announced IAS Agent, a new AI-powered assistant designed to help marketers activate campaigns faster, uncover deeper insights, and optimize performance at scale—without surrendering control to a black box.

Set to debut publicly at CES 2026, IAS Agent will roll out globally in early Q1 2026 at no additional cost to customers. That pricing decision alone signals how seriously IAS views AI assistance as a baseline expectation rather than a premium upsell.

An AI assistant built for marketers, not data scientists

IAS Agent is positioned as a natural-language interface layered directly into the IAS platform, allowing marketers to interact with campaign intelligence conversationally. Users can chat with the agent to streamline pre-campaign setup, adjust brand safety and suitability settings, and surface insights without needing technical expertise or manual dashboard analysis.

What differentiates IAS Agent from many AI tools flooding the ad tech market is its foundation: more than 15 years of proprietary IAS data across viewability, fraud, brand safety, and suitability, applied at omnichannel scale. Rather than relying on narrow or synthetic training sets, the assistant draws from what IAS describes as the industry’s most comprehensive dataset.

That matters in a market where AI recommendations often feel disconnected from real-world media complexity. IAS Agent’s outputs are grounded in historical patterns across publishers, platforms, and formats—not just recent signals.

Explainable AI, not opaque automation

The most pointed critique of AI in advertising has been its opacity. IAS is leaning directly into that concern with what it calls “explainable AI.”

Every recommendation surfaced by IAS Agent includes transparent self-reporting. Marketers can hover over suggestions inside the IAS UI to see what’s being recommended, why it’s being proposed, and what data signals informed the guidance. Users retain full control: they can customize, override, or adopt recommendations based on their own judgment and client requirements.

This design choice reflects a broader industry shift. As AI systems increasingly influence media spend, advertisers need to justify decisions internally—to legal teams, brand leaders, and regulators. Tools that can’t explain themselves are becoming liabilities rather than advantages.

Faster insights, fewer manual workflows

Beyond transparency, IAS Agent is built to reduce one of the most persistent drains on media teams: time.

According to IAS, early tests show efficiency gains of up to 50 percent in areas like brand safety and suitability configuration. The agent can recommend protection settings with minimal user input, allowing teams to scale governance across all investments without rebuilding rules for every campaign.

IAS Agent also continuously scans data across IAS dashboards to detect trends and patterns automatically. Instead of analysts hunting for signals across multiple reports, the agent surfaces what’s working—and what isn’t—up to five times faster than manual analysis.

In an environment where campaigns are increasingly fluid and omnichannel by default, that speed advantage could be decisive.

From campaign setup to real-time optimization

IAS Agent’s utility spans the full campaign lifecycle. During activation, marketers can use natural language prompts to get AI-assisted guidance on settings and configurations. Once campaigns are live, the agent highlights performance drivers, surfaces risk signals, and suggests optimizations in real time.

Crucially, IAS frames the tool not as a replacement for human decision-making, but as an advertising compass—guiding teams through complexity rather than automating judgment away.

Srishti Gupta, Chief Product Officer at Integral Ad Science, emphasized that IAS Agent is only the beginning. Future iterations are expected to expand agentic capabilities across supply path insights, tagging activation, and campaign settings assistance, further reducing friction across the media workflow.

Why agencies are paying attention

For agencies managing large, distributed media buys, the appeal is immediate. Jeff Omoregie, EVP of Unified TAAG at Publicis Media, highlighted the tool’s potential to reduce ad waste and speed action across complex environments.

That endorsement underscores a critical point: verification and optimization are no longer separate steps. They’re converging into a single intelligence layer that informs planning, activation, and optimization simultaneously.

IAS Agent positions IAS closer to that role—less a post-bid watchdog, more an always-on decision engine.

Responsible AI as a competitive differentiator

IAS is also using the launch to reinforce its stance on responsible AI. The agent is built using Databricks Agent Bricks, enabling enterprise-grade governance and observability—two requirements that are quickly becoming non-negotiable for large advertisers.

IAS notes it is the only company to hold all three major AI certifications relevant to the industry: TrustArc Responsible AI, ISO 42001, and Ethical AI certification from the Alliance for Audited Media. In a landscape where AI claims often outpace accountability, those credentials are meant to signal credibility.

A glimpse at the future of ad verification platforms

IAS Agent reflects a broader transformation underway in MarTech and AdTech. Verification platforms are evolving from compliance tools into intelligence systems—ones that don’t just flag problems, but actively guide better outcomes.

As AI assistants become embedded across marketing stacks, the winners will be those that combine scale, transparency, and trust. IAS is betting that explainability—not just automation—will be the feature that determines adoption.

For marketers facing tighter budgets, higher scrutiny, and increasing complexity, an AI assistant that can explain itself may be exactly what the industry has been waiting for.

Get in touch with our MarTech Experts.

Supply chains are no longer just about moving goods efficiently—they’re about orchestrating data, decisions, and partners across increasingly complex ecosystems. That shift is reflected in TraceLink’s latest recognition. The company has been named a Leader in the IDC MarketScape: Worldwide Multi-Enterprise Supply Chain Commerce Network 2025 Vendor Assessment, a nod to its growing influence in how large, regulated industries connect and collaborate digitally.

For TraceLink, the designation validates a long-term strategy centered on building an open, industrial-grade digital network rather than another point solution. At the heart of that strategy is OPUS, its Orchestration Platform for Universal Solutions, which IDC highlights as a foundational enabler for multi-enterprise collaboration.

Why OPUS matters now

Traditional supply chain systems were designed for internal optimization. They struggle when processes span dozens—or hundreds—of trading partners, each with different systems, standards, and regulatory requirements. IDC’s assessment points to OPUS as a response to that limitation.

According to the report, OPUS is an open platform that supports low-code application development, allowing both TraceLink and third parties to build multi-enterprise applications. In practice, that means companies can create digital networks that connect organizations, people, processes, and systems around shared business outcomes, rather than stitching together brittle integrations.

This approach aligns with a broader industry trend: enterprises are moving away from linear supply chains toward network-based operating models. In life sciences and healthcare especially, compliance, traceability, and real-time coordination are no longer optional—they are operational requirements.

From standalone solutions to network effects

TraceLink’s portfolio includes established offerings such as MINT, POET, and track-and-trace solutions, each delivering value on its own. What IDC’s recognition underscores is how those tools gain disproportionate impact when unified on OPUS.

When deployed together, these solutions enable faster issue resolution, higher data quality, and stronger compliance across global partner networks. Instead of managing fragmented workflows and disconnected data, organizations can operate on a shared digital foundation that scales across partners and geographies.

This “network effect” is increasingly important as supply chains face persistent disruption—from regulatory changes and geopolitical pressure to labor shortages and demand volatility.

Agentic orchestration enters the supply chain

TraceLink is also pushing OPUS beyond connectivity into orchestration. The platform is evolving to support agentic automation, allowing companies to deploy AI-powered digital teammates using no-code tools.

These agents are designed to monitor processes, reconcile data, and manage exceptions in real time, while keeping humans in the loop for oversight and accountability. For industries governed by GxP and other regulatory frameworks, that balance between automation and control is critical.

Shabbir Dahod, President and CEO of TraceLink, framed OPUS as a shared digital foundation built on trust and clarity. He argues that with agentic orchestration, organizations can link data, decisions, and partners in ways that fundamentally change how supply chains operate—moving from reactive coordination to proactive, network-wide intelligence.

Integrate once, collaborate everywhere

IDC also called out TraceLink’s Business-to-Network Integrate-Once™ architecture, which addresses one of the most persistent friction points in multi-enterprise systems: integration overhead.

Rather than requiring separate, point-to-point integrations for every trading partner, TraceLink’s model allows companies to integrate once and interoperate across the entire network. That dramatically reduces onboarding time, improves interoperability, and enables real-time visibility across shared processes.

In an environment where speed and responsiveness are competitive advantages, this model stands in contrast to legacy approaches that scale complexity faster than value.

Analyst perspective: orchestration over optimization

IDC analyst Reid Paquin noted that as organizations accelerate toward digitally connected supply networks, orchestration at scale has become essential. TraceLink’s platform approach—combining no-code tools with multi-enterprise process capabilities—maps closely to what enterprises now need: modern collaboration, shared visibility, and faster response across ecosystems.

That framing reflects a subtle but important shift in how supply chain technology is evaluated. The question is no longer just how well a system optimizes internal operations, but how effectively it enables collaboration across company boundaries.

The bigger picture

TraceLink’s placement as a Leader in the IDC MarketScape highlights a broader evolution in enterprise platforms. Supply chain networks are becoming programmable, intelligent, and increasingly autonomous—yet still governed and auditable.

By positioning OPUS as an open, no-code, agent-ready platform, TraceLink is signaling where it believes the market is headed: toward shared digital infrastructure that supports continuous improvement across entire ecosystems, not just individual enterprises.

For life sciences and healthcare organizations navigating regulatory pressure, operational complexity, and the push for resilience, that vision may be less about innovation for its own sake—and more about survival at scale.

Get in touch with our MarTech Experts.

If CES has become the annual proving ground for AI ambition, Zeta Global is using CES 2026 to make a pointed case: the future of marketing software won’t be dashboards—it will be agents.

Zeta Global (NYSE: ZETA) announced a full slate of CES 2026 activity centered on Athena by Zeta, its conversational, “superintelligent” AI agent designed specifically for enterprise marketers. The company will host private demos, executive conversations, and a high-profile fireside chat featuring tech analyst Dan Ives and Zeta co-founder and CEO David A. Steinberg, all aimed at reframing how marketers interact with data, decisions, and AI.

The message is clear: Zeta doesn’t see AI as a feature layered onto marketing clouds. It sees AI as the interface.

Why Athena matters in a crowded AI marketing market

The marketing technology landscape is already saturated with AI claims. Nearly every major platform now promises smarter targeting, automated insights, and predictive performance. What Zeta is pushing with Athena is a different idea—that marketers shouldn’t have to navigate complex tools at all.

Athena by Zeta is positioned as a conversational AI agent that sits on top of the Zeta Marketing Cloud, allowing marketers to ask questions, get recommendations, and take action using natural language. Instead of toggling between analytics dashboards, campaign managers, and segmentation tools, Athena is meant to collapse those workflows into a single, intelligent interaction layer.

That approach mirrors a broader enterprise trend. As AI agents become more capable, vendors across SaaS categories are racing to replace traditional UIs with conversational systems that reduce friction and speed decision-making. Zeta’s CES presence suggests it believes marketing is ready for that shift now—not in five years.

A CES fireside chat focused on outcomes, not hype

Zeta’s headline CES event takes place Tuesday, January 6, from 4:00 to 5:30 PM PT at the company’s Athena suite inside the ARIA Resort & Casino. Dan Ives, one of Wall Street’s most visible technology analysts and Chairman of Eightco, will lead a fireside chat with Steinberg focused on the future of Athena and AI-powered marketing.

According to Zeta, the discussion will explore how conversational intelligence is changing the marketer–technology relationship, removing operational friction and improving ROI. That framing is deliberate. As CMOs face mounting pressure to justify AI investments, the conversation is shifting away from experimentation toward measurable business impact.

The session will be recorded and shared on Ives’s X account the following morning, extending its reach beyond CES attendees and into the broader enterprise and investor audience.

Trust and transparency enter the AI conversation

One notable theme emerging from Zeta’s CES programming is trust. While many AI platforms emphasize speed and automation, Zeta is aligning Athena with enterprise-grade governance and accountability—an increasingly important differentiator as brands deploy AI deeper into customer engagement.

“As Chairman of Eightco, our mission is clear: put trust at the center of enterprise AI,” said Ives, framing the discussion around outcomes and long-term value rather than novelty. That perspective resonates in a market where marketing leaders are wary of opaque AI systems that can’t explain decisions or comply with data governance requirements.

For Zeta, positioning Athena as both powerful and responsible may be key to adoption among large brands that need AI to scale—but can’t afford reputational or regulatory missteps.

Demos, media exposure, and the C-suite audience

Beyond the fireside chat, Zeta will use CES to keep Athena in near-constant rotation. As an official CES sponsor, the company will host daily demos and client meetings in its Athena suite throughout the week, giving marketers hands-on exposure to the platform.

Steinberg will also appear at CES C Space on Tuesday, January 6 at 2:45 PM PT in an interview with James Kotecki, a media executive known for translating complex technology stories into executive-level conversations. The interview will be live-streamed across CES’s YouTube, X, LinkedIn, and Facebook channels, then archived on CES.tech and YouTube.

Later in the week, Steinberg is scheduled to speak at ADWEEK House on Wednesday, January 7, where he’ll walk through the evolving AI-enabled marketing landscape and deliver an exclusive Athena demo. That appearance puts Zeta squarely in front of brand marketers and agency leaders who are actively evaluating how AI will reshape campaign execution and customer engagement.

Reading the strategic signals

Zeta’s CES strategy reveals more than just a product showcase. It signals how the company sees the next phase of MarTech competition unfolding.

First, AI agents are becoming the front door to enterprise platforms. Vendors that fail to simplify complexity risk being sidelined by tools that do.

Second, thought leadership matters again. By anchoring its CES presence around conversations—not just demos—Zeta is betting that CMOs want context, clarity, and conviction as much as features.

Finally, timing matters. With budgets tightening and scrutiny on AI ROI increasing, Zeta is making its case early that Athena isn’t experimental—it’s operational.

Whether that vision resonates will depend on how effectively Athena delivers on its promise of higher ROI and lower friction. But CES 2026 will make one thing hard to miss: Zeta wants to lead the conversation about what AI-powered marketing actually looks like in practice.

Get in touch with our MarTech Experts.

For more than a decade, local visibility followed a familiar playbook: optimize listings, manage reviews, publish local content, and climb the rankings. That playbook is breaking down. As AI-driven search and answer engines increasingly decide which businesses get surfaced—and which get ignored—brands are discovering an uncomfortable truth: they’re optimized for keywords, not for AI.

Uberall is stepping directly into that gap.

The location marketing platform has launched GEO Studio, which it describes as the industry’s first Generative Engine Optimization (GEO) solution. Built in partnership with AthenaHQ, the platform is designed to help multi-location brands remain visible, accurate, and recommended as AI systems replace traditional search results with synthesized answers.

The timing is deliberate. As AI agents filter choices based on confidence, completeness, and consistency—not just relevance—many brands are finding themselves invisible in the very systems consumers now trust most.

The AI visibility problem no one planned for

Uberall frames GEO Studio as a response to what it calls the biggest visibility crisis brands have faced in a decade. According to the company, roughly 68% of local businesses appear incorrectly in AI-generated results due to missing, outdated, or inconsistent data.

That matters because AI doesn’t just retrieve information—it judges it. When AI systems generate answers about nearby services, they weigh trust signals, data consistency, and contextual clarity. If a brand’s location data is fragmented across platforms, AI confidence drops—and so does visibility.

Traditional SEO tactics don’t solve this problem. Keywords, backlinks, and long-form content are increasingly secondary when AI agents summarize, compare, and recommend businesses without ever showing a list of links.

In that environment, “AI-ready” has become a new baseline requirement.

What GEO Studio actually does

Uberall’s pitch is straightforward: GEO Studio makes every location “AI-eligible.” Instead of treating AI visibility as an abstract concept, the platform operationalizes it through three core capabilities.

First, GEO Studio monitors AI visibility itself. Brands can see exactly how AI systems describe them, whether that information is accurate, and how they compare to competitors—at both the brand and individual location level. This is a notable shift from traditional rank tracking, which measures placement rather than perception.

Second, the platform includes a generative content engine built specifically for AI readability. Rather than producing generic blog posts, GEO Studio generates structured, locally relevant content that AI systems can easily interpret: FAQs, location pages, social posts, review responses, snippets, and more. The emphasis is on clarity and structure, not volume.

Third, GEO Studio automates distribution across the places AI looks for signals. That includes Google Business Profiles, local landing pages, social channels, blogs, and third-party directories. The goal is consistency at scale—one of the hardest problems for multi-location brands to solve manually.

Taken together, these capabilities turn AI optimization into a repeatable workflow rather than a guessing game.

Why this is different from “AI SEO”

The distinction Uberall is drawing between SEO and GEO is more than semantic.

SEO is built around search engines indexing pages and ranking results. GEO assumes that AI systems act more like decision engines, synthesizing information from multiple sources and making recommendations based on confidence signals.

In that model, being “correct” matters as much as being “relevant.” A business with perfect keyword optimization but inconsistent hours, mismatched addresses, or thin local context may lose out to a competitor with cleaner, more structured data—even if that competitor has weaker traditional SEO.

Uberall’s advantage is its heritage. The company already manages location data, listings, reviews, and local pages for enterprise brands. GEO Studio extends that foundation into the AI era, rather than bolting AI optimization onto a content tool.

Early signals from pilots

Uberall says GEO Studio has been piloted with a limited set of customers, with early access brands reporting meaningful lifts in AI-driven visibility. While the company hasn’t shared specific benchmarks, customer feedback suggests the real value lies in visibility itself—finally being able to see how AI systems interpret a brand.

Audika’s Digital Marketing Manager, Dylan Paul, described the platform as the first tool that provides clear insight into AI-generated answers and competitive positioning. The ability to analyze prompts, identify gaps, and generate brand-aligned content “in seconds” highlights a key benefit: speed.

In AI-driven discovery, delays can be costly. If incorrect data propagates through AI systems, fixing it weeks later may be too late.

A broader MarTech signal

GEO Studio reflects a broader shift underway across MarTech and local marketing. As generative AI reshapes discovery, new categories are emerging alongside familiar ones. Just as SEO once professionalized website optimization, GEO is positioning itself as the discipline for AI-era visibility.

Uberall’s partnership with AthenaHQ underscores that this isn’t just about content generation—it’s about enterprise-grade optimization at scale. Producing locally relevant, on-brand, AI-readable content for hundreds or thousands of locations has historically been impractical. Automation makes it feasible, but only if it’s grounded in accurate data.

For multi-location brands in retail, healthcare, hospitality, and services, the implications are significant. AI is rapidly becoming the front door to local discovery, and brands that can’t see—or influence—how AI represents them risk becoming invisible by default.

The next battleground: AI recommendations

Perhaps the most important subtext in Uberall’s announcement is the word “recommended.” AI systems don’t just surface options; they often narrow them down. When consumers ask for the “best” nearby option, AI agents increasingly act as gatekeepers.

GEO Studio is designed to influence that recommendation layer by strengthening the signals AI uses to make decisions: accuracy, relevance, trust, and context at the local level.

That’s a higher-stakes game than ranking tenth versus fifth on a results page. In AI-driven experiences, there may be only one answer.

Uberall is betting that brands are ready to treat AI visibility as a first-class marketing channel. If that bet pays off, GEO may soon become as foundational as SEO—just optimized for a very different kind of engine.

Get in touch with our MarTech Experts.

Consumers aren’t searching the way they used to—and that shift is already rewriting the rules of digital marketing.

According to NP Digital Canada’s newly released 2026 Digital Marketing Predictions, discovery has moved almost entirely off the traditional website-and-search-results path. Instead of browsing pages or comparing links, consumers are increasingly relying on AI tools, social communities, influencers, and real-time recommendations long before they ever land on a brand’s site—if they land there at all.

For marketers still optimizing for the old funnel, the consequences are already visible: declining traffic, weaker trust signals, and revenue pressure that’s hard to explain using legacy analytics.

The warning from NP Digital Canada is blunt: this isn’t a future trend. It’s happening now.

Discovery has decoupled from websites

NP Digital Canada describes today’s reality as a Decoupled Discovery Journey—a fundamental shift in how Canadians research, evaluate, and choose brands.

Instead of starting with search engines, consumers are making decisions across Reddit threads, large language model chats, influencer videos, and social feeds. By the time they reach a brand’s website, the research phase is over. The visit is short, direct, and transactional.

That creates a dangerous illusion. From an analytics perspective, it looks like a clean, efficient journey. In reality, most of the persuasion happened elsewhere, leaving traditional attribution models blind to the moments that actually influenced the decision.

This blind spot is growing just as AI becomes central to buying behavior. NP Digital Canada points to Forrester’s 2024 Buyers’ Journey Survey, which found that 89% of B2B buyers now use generative AI as a core source of self-guided information across every stage of the purchase process. Discovery is no longer owned by search engines—it’s being mediated by machines.

“The challenge for brands isn’t just standing out, it’s being understood in an environment where discovery is fragmented and context is constantly lost,” said Ronnie Malewski, Managing Director at NP Digital Canada.

Why 2026 raises the stakes

Several forces are colliding at once. Campaign automation is accelerating execution. Technology democratization is allowing challenger brands to scale faster than ever. Budgets are under scrutiny. Meanwhile, content volume has exploded across AI-powered feeds and social platforms, fragmenting attention even further.

The result is a zero-margin-for-error environment. Consumers aren’t spending more time with brands—they’re spending less. AI systems are acting as filters, deciding which brands get considered and which never make the cut.

In that environment, visibility is no longer about ranking first. It’s about being trusted, cited, and recommended in places brands don’t control.

Human creativity becomes the real differentiator

One of NP Digital Canada’s strongest predictions for 2026 is that human-led storytelling will outperform AI-generated sameness.

As generative tools flood the market with fast, efficient content, much of it has become indistinguishable. Younger audiences, especially Millennials and Gen Z, are quick to spot automation and disengage. Emotional depth, originality, and cultural relevance—qualities AI still struggles to replicate—are becoming competitive advantages.

At the same time, platforms and publishers are tightening authentication and credibility standards. From restricted crawling to stricter verification, the industry is signaling that authenticity and expertise matter more than output volume.

AI will remain essential for scale, NP Digital Canada argues—but brands that outsource their voice entirely to machines risk blending into the noise.

Conversational commerce changes how buying happens

Another major shift heading into 2026 is conversational commerce. Consumers are increasingly using AI assistants not just to research products, but to compare options, confirm availability, and even complete transactions.

Google’s agentic commerce tools—such as “Let Google Call” and “Agentic Checkout”—offer a preview of what’s coming. AI agents can already contact stores, verify pricing or stock, and authorize purchases automatically when conditions are met.

For brands, this creates a new channel they don’t fully control. If AI assistants can’t clearly understand or trust a brand’s product data, that brand may never be recommended at all.

GEO moves from concept to necessity

NP Digital Canada also points to the rise of Generative Engine Optimization (GEO) as a structural shift in search strategy.

As tools like ChatGPT and Google’s AI Overviews reshape discovery, visibility depends less on rankings and more on recognition. Brands win by being cited, referenced, and trusted inside AI-generated answers.

That means structured data, factual accuracy, FAQs, comparison tables, and sentiment matter more than keyword density. GEO, in this model, becomes a core extension of SEO—not an experiment.

Brands that operationalize GEO early are likely to dominate AI-mediated discovery while others compete for clicks that never come.

First-party data only matters if it drives revenue

With privacy regulations tightening and third-party cookies disappearing, first-party data is one of the few defensible assets brands truly own. But NP Digital Canada cautions that collection alone isn’t enough.

Most brands are sitting on vast amounts of login data, purchase history, app behavior, and engagement signals. The differentiator in 2026 will be how effectively that data is activated—predicting needs, personalizing journeys, and removing friction before customers notice it.

The future belongs to brands that turn data into authority and revenue, not dashboards.

AI + humans, not AI alone

NP Digital Canada’s outlook isn’t anti-AI. It’s anti-autopilot.

The firms winning in 2026 will use AI to accelerate research, generate variations, and streamline workflows—while keeping humans responsible for strategy, creativity, and cultural relevance. Hybrid content models are becoming the default, not the exception.

That balance is especially critical as trust becomes the currency of visibility across AI systems and social platforms alike.

What brands need to do now

NP Digital Canada’s recommendations are pragmatic:

Use AI to increase output, but keep humans accountable for emotional and cultural connection.
Prepare product data and content so AI agents can clearly understand and recommend your brand.
Shift from keyword obsession to citation authority as GEO reshapes search.
Treat first-party data as a strategic asset, not a storage problem.
Adopt hybrid workflows that combine AI speed with human craft.
Use digital PR as a growth engine—authority mentions now influence both AI and social credibility.

The underlying message is hard to miss. Discovery has already moved. AI is already deciding. And brands that don’t adapt their strategies now won’t just lose traffic—they’ll lose relevance.

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