Amperity is taking aim at one of marketing’s most persistent problems: the gap between insight and action.

The AI-powered Customer Data Cloud company has introduced its Customer Data Agent, positioning it as the first enterprise AI agent designed not just to analyze customer data, but to act on it. Built on unified, trusted customer profiles, the agent allows marketers to move from questions to live segments and journeys in hours instead of weeks.

In an era where AI tools are plentiful but impact is uneven, Amperity’s message is clear: AI only works in marketing when it’s deeply connected to customer data and embedded directly into daily workflows.

From AI Insight to Activation—Without the Wait

For many marketing teams, access to customer insights remains a bottleneck. Data lives across systems, insights require specialized queries, and activation often depends on engineering backlogs. The result is slow decision-making and missed opportunities.

The Customer Data Agent is designed to eliminate that friction. Using conversational, natural-language prompts, marketers can explore unified customer data, generate insights, and immediately turn those insights into activation-ready segments and journeys—without translating questions into SQL, tickets, or dashboards.

“This marks an important step forward for the category,” said Tapan Patel, Research Director at IDC. “It shows how AI can move from simply providing customer insights to actually helping marketers decide what to do next.”

A Different Model for Enterprise AI

Unlike generic AI assistants layered onto fragmented datasets, Amperity’s Customer Data Agent is built on the company’s patented identity resolution technology, giving it a complete and accurate view of the customer across channels and touchpoints.

That foundation enables a different kind of enterprise AI—one that can be trusted to support decisions, not just surface patterns.

With this release, the Customer Data Agent:

• Operates on unified, real-time customer profiles, not system-level records

• Orchestrates specialized AI agents for segmentation, journey design, and analytics

• Compresses the timeline from insight to revenue impact from weeks to hours

This approach reflects a broader industry shift: AI is no longer judged by how impressive its outputs look, but by how effectively those outputs translate into measurable business results.

AI That Matches How Marketers Actually Work

Rather than forcing teams to adapt to new technical interfaces, the Customer Data Agent is designed to work the way marketers already think and communicate.

Teams can ask plain-language questions such as:

• “Build a segment of high-value customers likely to repurchase this quarter.”

• “Design a journey for first-time buyers with declining engagement.”

• “Show which customer groups are driving the most incremental revenue.”

The agent delivers answers and can route them directly into activation, measurement, or optimization workflows—closing the loop between understanding and execution.

“Most AI value gets stuck between the model and the workflow,” said Derek Slager, Co-Founder and CTO at Amperity. “The Customer Data Agent closes that gap by delivering outputs that are immediately usable.”

Why This Matters Now

AI has become central to enterprise marketing strategies, but many organizations still struggle to operationalize it. The challenge is rarely model performance—it’s the lack of clean, unified data and the operational layers needed to act on AI outputs.

Amperity’s Customer Data Agent brings those pieces together: trusted data, applied intelligence, and built-in activation. For consumer brands under pressure to personalize faster, improve ROI, and reduce dependency on technical teams, that combination could be a meaningful competitive advantage.

As AI continues to move from experimentation to expectation, tools that directly connect intelligence to execution may define the next phase of marketing technology.

Get in touch with our MarTech Experts.

Domaine Worldwide is doubling down on experience as the next battleground in ecommerce.

The global Shopify design and development specialist has acquired Pattern, one of the most decorated digital design agencies in the commerce ecosystem, in a move that underscores a broader shift in digital commerce: design is no longer a finishing touch—it’s a growth lever.

The acquisition brings together Pattern’s brand-led, experience-first design capabilities with Domaine’s Shopify engineering, platform migration, and global delivery scale. The result is a combined offering aimed squarely at brands that see digital experience as a competitive differentiator, not a cosmetic upgrade.

Why This Deal Matters

Ecommerce has matured. Performance marketing is more expensive, platform features are increasingly commoditized, and AI-driven personalization is raising customer expectations. In that environment, brands are competing less on who has the fastest site—and more on who delivers the most cohesive, emotionally resonant experience across channels.

That’s where this acquisition lands.

“Experience design has become a defining competitive advantage for commerce brands,” said Marko Bon, President of Domaine. Bringing Pattern into the fold, he noted, expands Domaine’s ability to help clients reimagine their brands while delivering scalable, technology-driven experiences.

In practical terms, Domaine is positioning itself not just as a Shopify systems integrator, but as a full-spectrum commerce partner—from brand identity and UX to platform engineering and AI-ready infrastructure.

Pattern’s Role: Design at Critical Moments

Pattern has built its reputation by partnering with brands at inflection points: rebrands, digital redesigns, and major platform migrations where the stakes—and expectations—are highest.

Its client roster includes digitally native and enterprise brands such as Marine Layer, Framebridge, Bobbie, Image Skincare, and Rothy’s, and its work has earned more than 200 industry awards, including repeated recognition from the Webbys, W3, Glossy, and ADWEEK.

Notably, Pattern and Domaine have already worked together on high-profile projects, including Rothy’s—making this acquisition more of a formalization than a leap into the unknown.

A Unified, Experience-First Commerce Stack

The combined company is targeting brands across the growth spectrum:

• VC-backed startups building digital-first identities

• High-growth brands evolving their ecommerce experience

• Enterprises needing scalable design systems, complex workflows, and AI-enabled efficiencies

Pattern brings deep expertise in brand systems, UX, and storytelling. Domaine adds global delivery, Shopify Plus engineering, and operational scale. Together, they aim to offer something many agencies struggle to balance: craft and scale.

“As Pattern experienced record-breaking growth, finding the right partner to scale with became critical,” said Isaac Newton, Co-Founder of Pattern. Cultural alignment and shared ambition, he added, made Domaine a natural fit.

Shopify, AI, and the Experience Arms Race

The timing of the deal is telling. Shopify is increasingly positioning itself as an operating system for modern commerce, with AI-driven features, composable architectures, and personalization tools baked into the platform.

But technology alone doesn’t differentiate brands.

As AI accelerates content creation and personalization, experience design becomes the filter that determines whether those capabilities feel coherent—or chaotic—to customers. Domaine and Pattern’s shared “one site per customer” philosophy reflects this shift toward deeply personalized, brand-consistent experiences powered by data and automation.

This acquisition also mirrors a broader trend in the MarTech and commerce services market: agencies are consolidating to meet rising client demands for end-to-end execution, rather than piecemeal design or development work.

Competitive Implications

Domaine’s move raises the bar for Shopify-focused agencies, many of which specialize either in design or engineering, but not both at enterprise scale. It also puts pressure on consultancies and systems integrators that have historically deprioritized brand and experience in favor of implementation speed.

For brands, the message is clear: digital commerce partners are expected to deliver strategy, experience, technology, and scalability—all under one roof.

What Comes Next

With Pattern fully integrated, Domaine plans to expand its global footprint and deepen its role in shaping how commerce brands adapt to rapid change across AI, personalization, and platform evolution.

For clients, the promise is simpler: fewer handoffs, tighter alignment between brand and technology, and digital experiences designed to scale—not break—as expectations rise.

In a crowded ecommerce landscape, Domaine is betting that experience-first commerce isn’t just a design philosophy. It’s the next phase of competitive advantage.

Get in touch with our MarTech Experts.

For decades, buying premium video—especially live sports—has been one of advertising’s most manual, time-intensive, and human-dependent processes. It’s also one of the most valuable. Now, NBCUniversal and a group of technology and agency partners are making a bold case that artificial intelligence is finally ready to take on the hardest job in media buying.

NBCUniversal, independent agency RPA, FreeWheel, and Newton Research have announced a new partnership that introduces agentic AI into premium video buying across both linear television and digital platforms. In a first-of-its-kind proof of concept, AI agents can execute and optimize a single premium video investment across NBCUniversal’s linear TV and streaming inventory in seconds—without removing humans from the loop.

The demo may look futuristic, but the implications are immediate: faster execution, fewer manual handoffs, and a fundamentally new way to transact high-value video advertising at scale.

And notably, this isn’t happening in long-tail inventory or test environments. The first real-world execution will include live football playoff games in Q1 2026—marking the first time AI agents have automated live sports inventory on linear television.

From fragmented buying to agent-led orchestration

At the center of the announcement is a shift away from siloed buying workflows. Traditionally, advertisers and agencies plan, negotiate, activate, and optimize linear TV and streaming video through separate systems, teams, and timelines. Even as “converged TV” has become a buzzword, execution has remained stubbornly fragmented.

The new model flips that dynamic.

Using agentic AI, buy-side and sell-side agents communicate directly with one another to orchestrate cross-platform video buying and optimization in real time. These agents span NBCUniversal’s linear networks and streaming properties, with FreeWheel and NBCUniversal deploying AI sales agents on the sell side, while Newton Research—working with RPA—has designed and implemented buy-side agents.

The result is a single, unified investment that can be planned, executed, and optimized across platforms almost instantly.

This is not simply automation of existing steps. It’s a reengineering of the workflow itself—one that replaces sequential, manual processes with parallel, machine-driven intelligence that still defers to human judgment on strategy and nuance.

Why “agentic AI” matters here

The term “agentic AI” is quickly becoming one of the most important—and misunderstood—concepts in enterprise technology. Unlike traditional AI tools that respond to prompts or automate narrow tasks, agentic AI systems can act independently within defined constraints, coordinating with other agents to achieve specific goals.

In this case, those goals include:

• Translating campaign objectives into actionable media decisions

• Negotiating and allocating inventory across linear and streaming

• Optimizing delivery in real time based on performance signals

• Preserving brand, pricing, and placement guardrails set by humans

The agents operate using Model Context Protocol (MCP), enabling agent-to-agent collaboration across different organizations’ systems—a critical requirement for media transactions that involve buyers, sellers, data providers, and measurement partners.

What makes this noteworthy is not just the speed, but the interoperability. Historically, media buying technology has struggled to connect across vendors and platforms. Agent-based systems, if widely adopted, could finally provide a common intelligence layer across the ecosystem.

Live sports: the ultimate stress test

If there’s one category that exposes the limits of automation, it’s live sports.

Live sports inventory is scarce, expensive, time-sensitive, and operationally complex. Ads must be delivered flawlessly, at scale, often during unpredictable moments. That complexity is precisely why sports have remained one of the last strongholds of manual media buying.

By applying agentic AI to live football playoff inventory, NBCUniversal and its partners are signaling confidence that AI can handle the most demanding use cases—not just remnant or digital-only placements.

Mark Marshall, Chairman of Global Advertising & Partnerships at NBCUniversal, framed the move as both symbolic and strategic.

“NBCUniversal is proud to introduce agentic AI into the future of media buying alongside our partners,” Marshall said. “This step forward will redefine how inventory is bought and sold, and what better place to start than within our live sports inventory.”

It’s a calculated bet: if AI can work here, it can work anywhere.

Preserving human expertise, not replacing it

One of the recurring concerns around AI in advertising is the fear of removing human judgment from decisions that require creativity, context, and brand sensitivity. The partners behind this initiative are eager to emphasize that this is not a “hands-off” system.

Instead, agentic AI is positioned as an operational layer—handling executional complexity so humans can focus on strategy.

RPA CEO Jim Helberg described the approach as a way to “hyper-streamline strategic media intelligence and transactions in service of business outcomes,” while freeing teams to focus on higher-value work.

By reengineering manual processes, Helberg said, agencies can redirect human expertise toward strategic planning, marketplace dynamics, and client-specific nuance—areas where AI still struggles.

This framing mirrors a broader trend across marketing technology: AI as a multiplier of human capability rather than a replacement.

What this means for agencies

For agencies, the promise is clear: fewer bottlenecks, faster activation, and greater control over cross-platform investments.

Today, executing a premium video campaign across linear TV and streaming often involves multiple teams, systems, and reconciliations—each introducing delays and inefficiencies. Agentic buying compresses that timeline dramatically.

Newton Research CEO John Hoctor highlighted how intelligent agents can support the full campaign lifecycle, from planning through measurement.

“Alongside humans, Newton’s agents interoperate and collaborate with other agents, data and technology companies to create a cohesive intelligence standard,” Hoctor said—one that could eventually power end-to-end campaign execution and optimization.

If that vision holds, agencies could see meaningful productivity gains at a time when margins are under pressure and clients are demanding more transparency and accountability.

Implications for publishers and broadcasters

For publishers like NBCUniversal, agentic AI represents more than operational efficiency—it’s a competitive differentiator.

As buyers push for faster, more flexible transactions across screens, publishers that can offer unified, intelligent access to premium inventory stand to gain. Automating sales-side workflows could also improve yield management, reduce friction in negotiations, and enable more dynamic pricing strategies over time.

FreeWheel General Manager Mark McKee pointed to the broader impact on connected TV, calling agentic buying a milestone in CTV’s evolution toward automation and outcomes.

“Historically, delivering ads live isn’t easy, especially with large-scale events like sports,” McKee said. “Now…something that seemed unimaginable just a short time ago is real.”

That statement underscores a key industry tension: as CTV grows, expectations around automation and measurement increasingly resemble digital—but premium content still demands TV-grade reliability. Agentic AI could be the bridge between those worlds.

How this compares to existing automation efforts

Automation in media buying is not new. Programmatic advertising has been around for more than a decade, and broadcasters have steadily introduced automation into linear TV through addressable ads and advanced planning tools.

What’s different here is scope and autonomy.

Programmatic systems typically automate bidding within predefined marketplaces. Agentic AI, by contrast, operates across systems, negotiating and optimizing holistically rather than transaction by transaction.

In that sense, this initiative aligns more closely with emerging trends in AI-driven enterprise software than with traditional ad tech. It’s less about auctions and more about orchestration.

Competitors are watching closely. Other major broadcasters and platforms are experimenting with AI-powered planning and optimization, but few have publicly demonstrated agent-to-agent transactions spanning linear and streaming—let alone live sports.

The road ahead: opportunity and caution

As groundbreaking as this announcement is, it’s still an early step.

The current implementation is described as a proof of concept, with a limited number of executions planned. Scaling agentic buying across more advertisers, inventory types, and publishers will raise new challenges around governance, transparency, and trust.

Questions remain about:

• How pricing controls and brand safety guardrails are enforced

• How agencies audit and explain AI-driven decisions to clients

• How measurement and attribution adapt to real-time agent optimization

There’s also the matter of standardization. For agentic AI to truly reshape the industry, more participants will need to adopt compatible protocols and data frameworks—a nontrivial task in a fragmented ecosystem.

Still, the direction is clear. As media operations grow more complex, manual workflows are becoming unsustainable. Agentic AI offers a plausible—and increasingly compelling—alternative.

Why this matters now

This announcement arrives at a moment when the advertising industry is searching for its next operational leap. Linear TV and streaming continue to converge, live sports remain the crown jewel of premium video, and marketers are demanding both speed and accountability.

By applying agentic AI to the hardest problem first, NBCUniversal and its partners are making a statement about where media buying is headed.

If successful, this approach could redefine not just how premium video is bought, but how agencies, publishers, and platforms collaborate in an AI-driven future.

For an industry long weighed down by complexity, that’s a future many are eager to test.

Get in touch with our MarTech Experts.

Independent insurance agencies have spent years modernizing back-office systems, yet the front office—where calls are answered, requests triaged, and service experiences formed—has largely remained manual. HawkSoft and Sonant are betting that voice AI is finally ready to change that.

HawkSoft, a widely used agency management system (AMS) for independent insurance agencies, has announced a new integration with Sonant, a voice AI platform built specifically for the insurance industry. The partnership brings 24/7 conversational AI directly into HawkSoft, automatically logging calls, creating tasks, and writing notes back into the system of record.

The promise is straightforward but significant: fewer missed calls, faster service, less manual data entry, and measurable productivity gains—without forcing agencies to overhaul their existing workflows.

Turning phone calls into structured work

For most independent agencies, phone calls remain the primary entry point for customer interactions. Policy changes, billing questions, certificate requests, and quote inquiries still arrive by phone—often in bursts that overwhelm staff.

Sonant’s voice AI acts as a virtual receptionist designed specifically around property and casualty (P&C) insurance workflows. Unlike generic call bots, Sonant’s agents are trained to understand insurance terminology and intent out of the box. Calls are answered around the clock, triaged in real time, and converted into structured tasks inside HawkSoft.

That means no more scribbled notes, copy-pasting between systems, or delayed follow-ups when staff are busy or unavailable. Each call becomes an actionable item tied to the correct client and policy record.

For agencies already standardized on HawkSoft, the integration keeps everything in one place—arguably the most important factor for adoption.

Why this matters for independent agencies

The insurance labor market remains tight, particularly for service and customer support roles that see high turnover. At the same time, customer expectations are rising, shaped by always-on digital experiences in banking, retail, and healthcare.

This integration directly targets that pressure point.

According to the companies, agencies using Sonant within HawkSoft can reduce hold times, eliminate missed calls, and free staff to focus on higher-value work such as advising clients, handling complex cases, and driving retention.

The efficiency gains are not just about speed. Manual call logging and note-taking are error-prone, often leading to dropped context and inconsistent service. Automating those steps improves accuracy while creating a cleaner audit trail—an increasingly important consideration in regulated industries.

What Sonant brings to the table

Sonant positions itself as insurance-native voice AI, rather than a general-purpose conversational platform. Its feature set reflects that focus:

• Insurance-trained AI agents capable of understanding common P&C service requests

• Warm transfers that route complex or sensitive calls to human staff

• VIP bypass for priority clients

• Past-call memory that preserves context across interactions

• Real-time lookups that connect callers to the correct client and policy records

• Automatic task routing directly into HawkSoft

From an operational standpoint, the key differentiator is that Sonant writes everything back into HawkSoft. Agencies don’t have to manage a separate inbox, dashboard, or CRM just to see what the AI handled.

Practical AI, not experimental tech

One of the most notable aspects of this announcement is its positioning. HawkSoft and Sonant are not framing the integration as a futuristic experiment or innovation lab project. Instead, they emphasize time-to-value.

The solution is designed to show measurable results in weeks rather than months, with governance guardrails and SOC 2 Type II compliance built in. That focus reflects a broader trend in enterprise AI adoption: buyers are increasingly skeptical of abstract “AI transformation” promises and want practical, operational improvements.

For agencies, the value proposition is easy to quantify. Fewer missed calls translate directly into better service and revenue protection. Reduced manual work lowers staffing pressure. Faster resolution improves customer satisfaction.

Keeping humans in the loop

Despite the automation, the system is not designed to replace agency staff. Simple, repetitive requests can be handled end to end by the AI, while more complex scenarios are routed to humans with full context attached.

Rushang Shah, CMO of HawkSoft, framed the integration as a way to balance automation with service quality.

“When Sonant’s virtual receptionist answers calls, it can handle simple tasks while routing more difficult ones to a person, all while documenting the client and policy in HawkSoft,” Shah said.

That hybrid approach mirrors how AI is being deployed across other professional services sectors: machines handle volume and structure, while humans handle judgment and relationship-building.

A signal of where insurtech is headed

The HawkSoft–Sonant partnership also reflects a broader shift in insurance technology. Rather than standalone AI tools, the market is moving toward embedded intelligence within core systems.

Agency management systems like HawkSoft sit at the center of daily operations. Integrating AI directly into those platforms reduces friction and increases trust—two major barriers to adoption in insurance.

Voice AI, in particular, is gaining traction as speech recognition and natural language understanding improve. What once felt unreliable or gimmicky is now being deployed in high-stakes customer interactions, provided it’s trained on domain-specific data.

Competitors across the AMS and insurtech landscape are watching closely. Expect more integrations that bring AI directly into systems of record, rather than forcing agencies to bolt on separate tools.

The bigger takeaway

At a time when “AI” is often overused and under-delivered, this announcement stands out for its specificity. It addresses a real operational bottleneck, integrates into an existing workflow, and targets measurable outcomes.

For independent insurance agencies, the front office has long been a productivity sink. HawkSoft and Sonant are making the case that voice AI—when designed for the industry and embedded correctly—can finally turn phone calls from interruptions into structured, actionable work.

If adoption follows, this may mark a quiet but meaningful shift in how agencies handle customer service in an always-on world.

Get in touch with our MarTech Experts.

As advertisers rethink how to reach multicultural audiences in a post-cookie world, premium context—not personal data—is becoming the new currency. Mundial Media is betting big on that shift.

The AI-powered advertising platform has announced an exclusive U.S. publisher partnership with Grupo Reforma, one of the most influential media organizations in Mexico and Latin America. Under the agreement, Mundial Media will represent Grupo Reforma’s U.S. digital advertising inventory, giving American advertisers brand-safe access to Spanish-language and bicultural audiences through some of the region’s most trusted journalism brands.

The deal brings Grupo Reforma’s premium editorial environments into Mundial Media’s curated publisher ecosystem, strengthening the platform’s position as a go-to partner for advertisers seeking culturally relevant reach without relying on identity-based targeting.

Why Grupo Reforma matters to U.S. advertisers

Grupo Reforma is not a niche publisher. Its flagship titles—Reforma (Mexico City), El Norte (Monterrey), and Mural (Guadalajara)—are among the most respected news brands in Spanish-language media. Importantly for U.S. marketers, these publications attract consistent engagement from U.S. Hispanic audiences who actively seek high-quality news and analysis tied to Mexico and broader Latin American affairs.

That audience is both valuable and difficult to reach. U.S. Hispanic and bicultural consumers are digitally savvy, media-fragmented, and increasingly resistant to intrusive targeting tactics. Many brands struggle to reach them at scale without sacrificing brand safety or relying on outdated demographic proxies.

By acting as Grupo Reforma’s exclusive U.S. digital advertising partner, Mundial Media positions itself as a bridge between premium Spanish-language journalism and U.S. brands looking for trusted environments.

A privacy-first alternative to identity-based targeting

At the heart of the partnership is a shared rejection of traditional identity-driven advertising models.

Rather than targeting users based on inferred demographics, device IDs, or third-party cookies, Mundial Media focuses on cultural context—what people are reading, watching, and engaging with in real time.

Tony Gonzalez, CEO and co-founder of Mundial Media, framed the partnership as a move away from guesswork.

“Grupo Reforma represents a benchmark for trusted journalism in Mexico,” Gonzalez said. “By partnering exclusively, we’re enabling brands to engage audiences in premium environments that are informed by real cultural context rather than inferred identity signals.”

That distinction is increasingly important as privacy regulations tighten and browser-level tracking continues to disappear. For advertisers, the appeal lies in relevance without regulatory risk.

Editorial integrity stays intact

One of the long-standing tensions in premium publishing is balancing monetization with editorial independence. Both companies are keen to stress that this partnership is designed to preserve journalistic standards rather than compromise them.

“Grupo Reforma has long been committed to independence, credibility, and journalistic rigor,” said Javier Andrade, Deputy Director of Digital Media at Grupo Reforma. “This partnership with Mundial Media reflects a shared focus on quality and thoughtful audience engagement, while allowing our journalism to reach U.S. advertisers in a manner consistent with our editorial standards.”

For Grupo Reforma, the deal offers a way to expand U.S. advertising demand without opening the door to low-quality or misaligned ads. For Mundial Media, it reinforces its positioning as a selective partner that prioritizes trust over sheer scale.

The technology behind the deal: Cadmus AI

Powering the partnership is Mundial Media’s proprietary technology platform, Cadmus AI. Unlike traditional contextual tools that rely on basic keyword matching, Cadmus AI is designed to interpret cultural signals at scale.

The system analyzes millions of pages daily across sports, news, entertainment, lifestyle, and emerging multicultural trends. It classifies content in real time, identifying moments of high cultural relevance without using cookies or device identifiers.

These signals feed into dynamic contextual segments that advertisers can activate across display, video, high-impact formats, and custom executions. Contextual intelligence is applied at the page and moment level, helping ensure alignment with brand values and campaign objectives.

In practical terms, this allows advertisers to appear next to content that resonates culturally with Hispanic and bicultural audiences—without needing to know who the individual reader is.

Meeting advertiser demand for clarity and control

The partnership also reflects changing expectations on the buy side.

“Advertisers today want more than reach,” said Alex Haluska, VP of Business Development at Mundial Media. “They are looking for clarity, control, and confidence in where their messages appear.”

Premium publishers like Grupo Reforma offer exactly that: high-quality environments, strong editorial oversight, and predictable audience engagement. Mundial Media’s role is to make that inventory accessible in a way that fits modern media buying requirements, including transparency, brand safety, and privacy compliance.

This approach contrasts sharply with open-web programmatic buying, where ads can easily end up in low-quality or misaligned environments despite brand safety filters.

A selective publisher strategy

Unlike platforms that prioritize scale above all else, Mundial Media works with a limited roster of publishers across news, sports, entertainment, and lifestyle. Each partnership is structured for long-term alignment, with an emphasis on accountability and editorial standards.

Grupo Reforma now joins that growing list, adding significant weight in Spanish-language news and strengthening Mundial Media’s multicultural offering in the U.S. market.

The strategy is deliberate: fewer publishers, higher quality, and clearer value for advertisers. As brands become more selective about where their ads appear, this kind of curated approach is gaining traction.

The bigger picture: cultural context as the new signal

Zooming out, the Mundial Media–Grupo Reforma deal reflects a broader shift underway in digital advertising.

As third-party cookies fade and regulators scrutinize identity-based targeting, cultural and contextual signals are emerging as a scalable alternative—especially for reaching diverse audiences. Rather than asking “Who is this user?”, advertisers are increasingly asking “What is the moment, and why does it matter?”

For Hispanic and bicultural marketing, that shift may be particularly powerful. Cultural relevance is often situational, language-driven, and content-specific—factors that traditional demographic targeting struggles to capture.

By combining premium journalism with AI-driven cultural intelligence, Mundial Media is positioning itself at the intersection of privacy, relevance, and trust.

What to watch next

The immediate impact of the partnership will be felt in the U.S. Hispanic advertising market, where demand for premium, brand-safe Spanish-language inventory continues to outpace supply. Longer term, the model could influence how other international publishers approach U.S. monetization—favoring exclusive, context-first partnerships over broad, commoditized distribution.

For advertisers navigating an increasingly complex media landscape, the message is clear: quality environments and cultural understanding are becoming just as important as reach.

And for publishers like Grupo Reforma, the deal shows that protecting editorial integrity doesn’t have to come at the expense of commercial growth—if the right partner is involved.

Get in touch with our MarTech Experts.

Programmatic advertising has spent the past decade scaling reach, channels, and data. In 2026, that era of expansion is giving way to something more decisive: consolidation.

That’s the central takeaway from StackAdapt’s newly released State of Programmatic Advertising 2026 report, which argues that programmatic is entering a defining transition. Marketers who continue to rely on fragmented tools and siloed execution are falling behind, while those unifying workflows, consolidating technology, and applying AI with intent are pulling sharply ahead.

Based on insights from 484 senior marketers across the U.S., Canada, and the UK, combined with platform data from more than 6,000 global advertisers, the report paints a picture of a maturing channel—and a widening performance gap between leaders and laggards.

The message is blunt: programmatic complexity is no longer a badge of sophistication. It’s a competitive disadvantage.

A market that looks healthy—until you look closer

On the surface, the programmatic market appears to be thriving. According to the report, 75% of marketers expect their budgets to grow, and 84% report stronger year-over-year performance. Optimism is high, spend is increasing, and confidence in programmatic remains strong.

But dig deeper, and the data reveals a growing maturity gap.

Only a subset of marketers—what StackAdapt defines as top performers—are converting that momentum into sustained gains across performance, efficiency, and growth. These marketers report significantly stronger year-over-year results than their peers, not because they’re experimenting more, but because they’re operating differently.

The difference isn’t ambition. It’s execution.

What separates top performers from the rest

StackAdapt’s report identifies three behaviors that consistently distinguish top-performing marketers:

1. Unified channel strategy

2. Consolidated technology stacks

3. Pragmatic, embedded use of AI

Rather than layering new tools on top of old ones, leaders are simplifying. They are bringing creative, data, media, and measurement closer together—often within a single platform—so insights can move faster and decisions can scale.

This shift reflects a broader realization across digital marketing: more tools do not automatically mean better outcomes. In fact, excess tooling often slows teams down, creates data silos, and makes optimization harder, not easier.

As Yang Han, Co-Founder and CTO of StackAdapt, puts it:
“The marketers seeing the strongest gains aren’t adding more tools—they’re consolidating around platforms that can connect channels, data, and AI in one system.”

The hidden cost of fragmented execution

One of the most striking findings in the report is the disconnect between how marketers describe their strategies and how they actually operate.

While 75% of marketers say they run omnichannel campaigns, most lack the infrastructure and workflows needed to consistently act on cross-channel insights. Data may be visible, but it’s not actionable. Learnings remain trapped in dashboards, teams, or channel-specific tools.

The result is a familiar set of problems:

• Fragmented activation across channels

• Inconsistent messaging and creative sequencing

• Delayed optimization decisions

• Wasted spend due to duplicated or misaligned efforts

In other words, omnichannel in name, but not in practice.

StackAdapt’s data suggests that top performers have moved beyond this stage. They aren’t just measuring across channels—they’re executing across them, using shared data and AI-driven optimization to inform decisions throughout the funnel.

AI: from novelty to operational advantage

AI is no longer the differentiator it was just a few years ago. Nearly every marketer now claims to be “using AI” in some form. What’s changed is how AI is being applied—and how uneven that application has become.

According to the report, top performers are not treating AI as a bolt-on feature or experimental add-on. Instead, they’re embedding it directly into execution, where it accelerates decision-making and removes friction from everyday workflows.

That includes:

• Automating optimization across channels

• Identifying performance patterns faster

• Connecting creative signals to media outcomes

• Scaling learnings without manual intervention

Less mature organizations, by contrast, often deploy AI in isolated ways—testing tools without integrating them into core operations. The result is limited impact and growing skepticism about AI’s value.

“Measurement has finally caught up, but execution hasn’t,” Han noted. “In 2026, the advantage will belong to marketers who turn visibility into action.”

Why consolidation is becoming inevitable

The report’s emphasis on consolidation reflects a broader shift across the ad tech landscape.

For years, marketers assembled best-of-breed stacks to handle planning, buying, measurement, and creative across channels. While that approach offered flexibility, it also created operational drag. Each additional platform introduced new workflows, integrations, and learning curves.

As programmatic matured, the cost of that fragmentation became harder to ignore.

StackAdapt’s findings suggest that leading marketers are now prioritizing platforms that can orchestrate multiple channels and functions in one place. Not because specialization has lost value, but because speed, cohesion, and scalability matter more at this stage of growth.

In a market where marginal performance gains can translate into significant revenue impact, reducing latency between insight and action is critical.

The performance gap is widening

Perhaps the most consequential insight in the report is that the gap between top performers and everyone else is growing—not shrinking.

As programmatic tools become more powerful, the upside of using them well increases. At the same time, the penalty for inefficient operations becomes more severe. Marketers who fail to unify workflows and consolidate technology aren’t just leaving gains on the table; they’re actively falling behind competitors who move faster and learn quicker.

This dynamic mirrors what happened in search, social, and ecommerce advertising as those channels matured. Early on, experimentation drove advantage. Later, operational excellence took over.

Programmatic appears to be entering that same phase.

Implications for marketers in 2026

For marketing leaders, the report carries several clear implications:

First, tool proliferation is no longer a growth strategy. If your stack is slowing down decision-making or creating data silos, it’s likely hurting performance.

Second, omnichannel success requires operational change, not just planning alignment. Shared insights only matter if teams can act on them consistently and at speed.

Third, AI value comes from integration, not experimentation. The biggest gains come when AI is embedded into daily workflows and tied directly to outcomes.

Finally, organizational maturity now matters as much as media strategy. Teams, processes, and platforms must evolve together.

What this means for the ad tech market

From an industry perspective, StackAdapt’s report reinforces a trend already underway: platforms are moving from point solutions toward orchestration.

As advertisers demand simplicity without sacrificing sophistication, vendors that can unify channels, data, and AI stand to gain. Those that remain siloed risk being relegated to niche roles—or phased out altogether.

It also raises the bar for differentiation. In a world where “AI-powered” is table stakes, the real question becomes whether technology actually changes how marketers work.

The bottom line

The State of Programmatic Advertising 2026 report doesn’t argue that programmatic is broken. On the contrary, it suggests the channel is stronger than ever—but less forgiving.

Growth is still available. Budgets are still expanding. Performance is still improving. But the rules have changed.

In 2026, programmatic winners will be defined less by how many tools they use and more by how effectively they connect them. The marketers pulling ahead are doing fewer things better—unifying channels, simplifying stacks, and using AI to turn insight into action.

For everyone else, the warning is clear: complexity is no longer neutral. It’s a liability.

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First Brands Group, a major global supplier of aftermarket automotive parts, is officially testing the market.

The company announced it has launched a formal sale process to market and sell its business—either as a whole or in parts—as it works toward emerging from Chapter 11 and transitioning to new ownership. The move is designed to maximize stakeholder value while preserving continuity for customers, vendors, and employees during the restructuring.

The process could reshape ownership of some of the most recognizable names in the automotive aftermarket, including FRAM, Raybestos, Trico, Autolite, and Reese.

A sale process tied to Chapter 11 exit

First Brands’ decision comes as part of its ongoing Chapter 11 proceedings, where the company is seeking a faster and more certain path to stability under new ownership.

According to the company, the sale process is intended to:

• Accelerate emergence from bankruptcy

• Support a transition to long-term ownership

• Position its core brands for their next growth phase

The company said it is exploring a range of outcomes, from selling the business in its entirety to divesting specific segments.

Charles Moore, Interim CEO of First Brands Group, framed the move as a strategic inflection point rather than a liquidation.

“Launching the marketing process represents a decisive step toward positioning our brands for long-term stability under new ownership,” Moore said, pointing to what he described as “significant value across the First Brands portfolio” and strong growth potential in the aftermarket sector.

DIP financing and a potential stalking horse bidder

To support operations during the sale, First Brands is also in discussions with an ad hoc group of lenders about securing additional debtor-in-possession (DIP) financing. That same lender group is expected to serve as a stalking horse bidder for certain business segments once agreements are finalized and approved by the bankruptcy court.

If approved, the financing would allow the company to:

• Maintain supply continuity

• Continue servicing customers across core brands

• Avoid operational disruption during the sale process

Stalking horse bids are often used in Chapter 11 cases to set a baseline valuation and encourage competitive bidding—suggesting lenders see underlying value in specific First Brands assets.

Why First Brands remains attractive to buyers

Despite its restructuring, First Brands controls a broad and strategically valuable portfolio in the automotive aftermarket—a sector that continues to benefit from aging vehicle fleets, higher repair costs, and longer vehicle ownership cycles.

The company’s assets include:

• A global lineup of mission-critical auto parts across brakes, filters, spark plugs, wipers, pumps, lighting, towing, and accessories

• Category-leading brands such as FRAM, Raybestos, Trico, Autolite, and Reese, each with deep relationships across retail and commercial channels

• A global manufacturing and distribution footprint supporting both aftermarket and OEM products

• Strong brand recognition within the estimated $410 billion North American automotive aftermarket

Management also highlighted operational and financial improvements implemented during the Chapter 11 process, positioning the business as more efficient and disciplined than before.

For potential buyers—whether strategic acquirers or private equity firms—the combination of durable demand, brand equity, and operational reset could prove compelling.

Industry context: consolidation and selective bets

The automotive aftermarket has been steadily consolidating, as suppliers seek scale, margin resilience, and portfolio breadth. At the same time, investors have become more selective, favoring assets with strong brand loyalty and defensible market positions.

First Brands’ willingness to sell assets individually reflects that reality. Some buyers may be interested in marquee brands like FRAM or Raybestos, while others may target specific product categories or regional operations.

That flexibility could broaden the bidder pool and help drive value—especially if multiple strategic buyers see synergies within different parts of the portfolio.

What happens next

First Brands expects to file a motion with the bankruptcy court seeking authorization to formally conduct the sale and marketing process under Section 363 of the U.S. Bankruptcy Code. That process is designed to deliver the highest or best bid for the company’s assets.

The company said it plans to move quickly, targeting completion of the sale process in the first quarter of 2026, subject to court approval.

Until then, operations are expected to continue as normal, supported by DIP financing and lender backing.

The bigger takeaway

First Brands’ announcement underscores a familiar theme in industrial and manufacturing restructurings: even amid financial distress, strong brands and essential products retain significant value.

For the aftermarket auto industry, the sale could trigger a reshuffling of ownership among some of its best-known names. For First Brands’ stakeholders, the coming months will determine whether that value is best realized under one roof—or several.

Either way, the process marks a pivotal moment for a company whose brands are fixtures in garages, repair shops, and retail shelves across North America.

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As enterprises race to operationalize AI, one question is becoming impossible to ignore: Who’s actually governing these systems once they’re live? Prodapt wants to make its answer unmistakably clear.

The technology services firm has announced it has been awarded ISO 42001, the world’s first—and currently only—global standard for AI Management Systems (AIMS). The certification positions Prodapt among a small group of providers able to demonstrate formal, auditable governance for AI across strategy, technology, and operations.

In a market crowded with AI claims and pilot projects, ISO 42001 represents something more concrete: proof that AI can be scaled responsibly, not just rapidly.

Why ISO 42001 matters right now

ISO 42001 arrives at a critical moment for enterprise AI. As organizations move from experimentation to AI-driven decision-making, concerns around risk, accountability, transparency, and compliance are intensifying—especially in regulated and high-stakes industries.

Unlike technical model benchmarks, ISO 42001 focuses on how AI is governed, not just how it performs. The standard establishes requirements for managing AI across its full lifecycle, from design and deployment to monitoring, enhancement, and eventual decommissioning.

For enterprises under pressure from regulators, boards, and customers, that governance layer is quickly becoming non-negotiable.

By achieving ISO 42001, Prodapt is signaling that its AI offerings are not only advanced, but operationally disciplined and enterprise-ready.

What the certification validates

The certification, awarded by an independent accredited body, validates Prodapt’s enterprise-grade AI management framework, with an emphasis on accountability and control.

Key areas highlighted in the evaluation include:

• Executive-led AI oversight, ensuring governance is owned at the highest levels

• Risk management and ethical AI practices, embedded into day-to-day operations

• Human-in-the-loop controls, built systematically into AI workflows

• Clear ownership and escalation models, with traceable decision-making

• Transparency and auditability, supported by comprehensive documentation

In short, the standard confirms that AI systems at Prodapt are designed to be responsibly governed throughout their lifecycle—not treated as black boxes once deployed.

Governance beyond the model

One of the most notable aspects of ISO 42001 is its scope. The standard extends well beyond algorithms and models, covering organizational processes, controls, and accountability structures.

Prodapt’s certification recognizes governance across:

• Design and build of AI systems

• Deployment and enhancement as models evolve

• Monitoring and risk mitigation in live environments

• Deprecation and retirement, often overlooked in AI programs

That end-to-end focus reflects a growing industry realization: unmanaged AI technical debt can become just as risky as unmanaged software debt—if not more so.

From theory to large-scale practice

ISO certifications often draw skepticism if they appear disconnected from real-world execution. Prodapt counters that by grounding its governance framework in multiple large-scale enterprise AI implementations already in production.

According to the company, these deployments have helped shape practical controls around accountability, escalation, and continuous monitoring—allowing innovation to scale without undermining trust or compliance.

That experience matters. Many enterprises are discovering that scaling AI introduces new failure modes, from biased outcomes to opaque decisions that are hard to explain internally, let alone to regulators.

Prodapt’s approach suggests governance is being treated not as a compliance afterthought, but as an enabler of scale.

Executive signal: trust as a growth lever

Manish Vyas, CEO and Managing Director of Prodapt, framed the certification as a strategic commitment rather than a symbolic milestone.

“As enterprises transition to AI-driven decision-making, trust and governance become non-negotiable,” Vyas said, describing ISO 42001 as a global benchmark for operationalizing AI responsibly.

The subtext is clear: in the next phase of enterprise AI adoption, trust will differentiate vendors as much as capability. Buyers increasingly want proof that partners can manage AI risk at scale—not just build impressive demos.

How this compares to the broader market

While many technology and services providers talk about responsible AI, relatively few can point to a formal, independently audited management system aligned to a global standard.

ISO 42001 is still new, and adoption remains limited—giving early achievers like Prodapt a potential credibility advantage, especially with global enterprises navigating overlapping regulations such as the EU AI Act, data protection laws, and industry-specific compliance requirements.

As AI governance standards mature, certifications like ISO 42001 may become table stakes. For now, they serve as a strong signal of readiness.

The bigger takeaway for enterprise AI

Prodapt’s announcement reflects a broader shift underway in enterprise AI: success is no longer defined solely by model performance or speed to deployment.

Instead, organizations are asking tougher questions:

• Who owns AI decisions?

• How are risks identified and mitigated?

• Can outcomes be explained, audited, and defended?

• What happens when models change—or fail?

ISO 42001 is designed to answer those questions systematically.

For enterprises looking to scale AI without inviting regulatory or reputational risk, governance frameworks like this are becoming foundational infrastructure—not optional safeguards.

Bottom line

By earning ISO 42001, Prodapt is staking a clear position in the AI services market: scalable AI must be governed as rigorously as it is engineered.

As AI moves deeper into core business decisions, that stance may prove just as valuable as any technical breakthrough.

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