In this uncertain world, we can count on two truths.

The first is that Super Bowl 60 is coming. The second is that brands are increasingly focused on whether and how they’re appearing in generative search engines like OpenAI’s ChatGPT, Anthropic’s Claude, or Google’s AI Mode. 

That’s why ADWEEK is partnering with Emberos on the day of the Super Bowl to power the first-ever Real Time AI Influence Index. 

Emberos is a startup whose tech is designed to help brands control how they show up in AI search results, focusing on ChatGPT, Gemini, Claude, Perplexity, and Grok.

On the day of the 2026 Super Bowl, the AI Influence Index will appear on the right sidebar of the ADWEEK.com homepage to reveal the top 7 Super Bowl advertisers, based on whether they’re showing up in AI queries. Expect big swings as brands capture and lose momentum throughout the Big Game, depending on whether their ads make a splash… or not.

Emberos will look at a variety of factors to determine the top advertisers, including how often specific ads are named when people ask AI about Super Bowl commercials; whether ads gain or lose visibility as the conversation changes; whether the ad is showing up in the public discourse that feeds the AI systems; whether the AI systems clearly and accurately describe the ads; and whether the ad appears consistently across multiple generative search engines. 

The day after the Super Bowl, we’ll reveal the top 20 brands that dominated the Generative Search conversation during Super Bowl week. And we’ll Monday morning quarterback with some insights into why those brands dominated, the nature of the discourse, and how big moments—like celebrity cameos, controversy, and surprise drops—translated into AI visibility. 

We’ll also reveal some insights into the generative search engines themselves, like which ones saw the most queries, which platforms had the most consistent brand recall, and where the engines disagreed, diverged in interpretation, or surfaced inconsistent details.

So not only will our post-game analysis reflect how the Super Bowl advertisers did, we’ll be able to show you how five different generative search engines performed as well, and what it means as they compete for AI mindshare.

The aim is to help the ad industry understand which commercials broke through, and show the growing influence AI search systems have on recall, conversation, and discovery during huge cultural moments.

In the meantime, be sure to check out our Super Bowl 60 ad tracker here.

OpenAI’s recent launch of Atlas marks a pivotal moment for digital marketing, and for the evolution of the internet itself. Atlas showcases the rise of the agentic web, an internet in which AI completes tasks on users’ behalf and actively represents them.

For marketers, this means algorithms will increasingly mediate how people discover, evaluate and interact with brands. The path forward lies in diversification and data: Expanding how we reach audiences and unifying how we measure performance across every screen. 

The Diversification Imperative

First, we have to acknowledge that AI is already reshaping online behavior. Gartner predicts that by 2026, traditional search traffic could decline by as much as 25%, largely due to the proliferation of AI-driven tools and intermediaries. For marketers, this means fewer touchpoints, increased competition for attention and greater urgency to diversify beyond search-centric strategies, as the traditional web is no longer the only (or even the primary) place for digital discovery. 

The good news, however, is that the broader, open internet—which includes mobile, connected TV (CTV), and beyond—is more measurable and performant than ever. 

Take, for example, the fact that consumers spend nearly 90% of their time on mobile within apps (a channel largely shielded from the volatility of search engines), generating more than $935 billion in annual revenue globally. Paired with other, high-attention environments, like CTV and digital out-of-home, mobile can help marketers maintain connection with consumers wherever they spend time. These environments also tend to offer greater engagement and measurement, allowing brands to connect media with storytelling in one continuous loop and build more resilient, diverse portfolios in the process. 

Data as the Demand-Side Advantage

Of course, diversification without data is just more noise. From the perspective of a demand-side platform like Nexxen, the most effective advertisers are going a step beyond diversifying channels and integrating data to inform every decision, including bid optimization and creative conquesting. 

To identify quality environments, track incremental reach, and optimize for outcomes that matter most to their businesses’ bottom lines, brands need to start crafting open, privacy-led data strategies that link mobile, CTV, and other channels into one cohesive framework. Put differently, we need to treat data as the connective tissue and infrastructure, rather than a campaign byproduct, to excel. 

Ultimately, by approaching campaigns with diversification and data top-of-mind, we can turn disruption into discovery—building brand value in places algorithms can’t define. The rules of online engagement may be changing, but we now have the chance to rewrite them on our terms, for good. 

In this episode of TechMagic, hosts Cathy Hackl and Lee Kebler unpack the realities behind today’s AI headlines. 

They explore OpenAI’s shift toward advertising, the growing human bottleneck in data center expansion, and why the AI conversation is moving beyond productivity toward physical and human-centred systems. 

The discussion dives into the surprising earning power of skilled trades, how XR is transforming workforce training, and why the metaverse was never just about VR headsets. 

From VRChat to The Sims, Cathy and Lee reveal where the spatial web is quietly taking shape, and what it all means for the future of work and technology.

Come for the tech, stay for the magic!

Episode Highlights:

From Productivity to Physical Intelligence — Cathy explains that the AI conversation at Davos has moved decisively beyond productivity-focused generative models toward agentic AI, physical systems, and world models. This shift reflects growing awareness that LLMs alone cannot address real-world complexity. Leaders still optimizing for text output risk falling behind as capital flows into robotics, autonomous factories, and AI embedded in physical infrastructure. Reframing AI strategy around how systems act, move, and interact with the real world is now essential for long-term competitiveness.

The Ad-Supported AI Credibility Breakdown — Lee warns that embedding advertising directly into conversational AI undermines the core promise of trust and reliability. When sponsored answers replace optimal solutions, users immediately recognize bias and lose confidence in the system. Short-term monetization creates long-term damage by corrupting AI’s role as a neutral advisor. To preserve credibility, organisations must clearly separate sponsored content from recommendations, treating AI more like a trusted expert than an attention-driven media platform.

Engagement Algorithms vs Truth-Seeking AI — Cathy and Lee explore the unsettling possibility that AI systems could be optimized to provoke debate rather than deliver accuracy. Much like social media, engagement-based metrics may reward slightly incorrect or controversial answers that keep users interacting longer. This reverses AI’s original purpose. Organizations must audit retention incentives and introduce transparency, clearly signaling when responses prioritize confidence and correctness versus engagement, to avoid quietly degrading informational integrity.

The Skilled Trades Bottleneck Behind AI’s Expansion — Cathy and Lee reveal that AI infrastructure growth is constrained not by silicon, but by human labor. HVAC technicians, electricians, and plumbers are now the limiting factor in data center expansion, creating six-figure earning opportunities that most career pipelines ignore. These roles provide job security, geographic demand, and direct relevance to AI’s future. As data centers proliferate, skilled trades become the hidden backbone enabling every AI breakthrough.

XR as the Scalable Knowledge Transfer Engine — Lee Kebler highlights XR platforms like XOI as a breakthrough solution to the expertise drain caused by retiring master technicians. Using AR headsets and live video feeds, one expert can mentor multiple junior workers across sites in real time. This distributed apprenticeship model preserves institutional knowledge while accelerating workforce scaling. XR quietly solves two problems at once: labor shortages and the infrastructure bottlenecks slowing AI deployment.

The Lego Group arrived at CES 2026 with more than an announcement: Lego SmartPlay represents a major evolution, blending physical and digital interaction while keeping imagination in control. 

In this episode of The Speed of Culture, Matt Britton sits down with Tom Donaldson, senior vice president and head of the Creative Play Lab at the Lego Group, to discuss the new platform powered by Lego Smart Brick technology that allows Lego creations to respond to how they are played with. 

From years of R&D product development to kid-led testing and early prototyping, Tom shares how the Lego Group builds conviction, protects creativity, and advances interactive play without screens at global scale.

With a background in engineering, deep technology, and early artificial intelligence work, Tom brings a unique perspective on creativity and AI leadership. At the Lego Group, he enables his teams to take thoughtful risks, turning early ideas into play experiences that resonate with kids, families, and lifelong fans.

Key Takeaways:

[01:33] Lego SmartPlay CES 2026 Adds a New Dimension to System in Play — Tom frames Lego SmartPlay as more than a product moment. It is a new dimension added to the Lego System in Play, where pieces respond to how builders move, combine, and imagine with them. Play becomes more alive. Models change, react, and surprise based on what builders do, making play feel social, expressive, and open-ended while imagination stays firmly in charge.

[02:01] How Lego Smart Brick Technology Works — At the center of Lego SmartPlay is the Lego Smart Brick technology, a familiar 2×4 brick filled with sensors, sound, light, and an onboard synthesizer. Tom explains how it senses movement, color, Smart Tags, and Smart Minifigures, then reacts instantly. Move faster and engines rev. Slide a corner and sounds shift. The experience feels physical and responsive, creating interactive Lego play without screens that rewards exploration rather than instructions.

[03:58] A Layer, Not a Pivot, in Lego System in Play Innovation — Tom is careful to explain that Lego SmartPlay does not change what Lego play is. He compares it to the introduction of the Lego Minifigure, which added storytelling without touching the core of building. SmartPlay follows the same philosophy. It layers responsiveness on top of classic play, letting builds interact and evolve while keeping the simplicity, freedom, and creativity that define the Lego System in Play.

[05:32] Lego R&D Product Development Built Over Years — The work behind the R&D product development for SmartPlay stretched across many years. Tom describes a process shaped by constant learning, from early technical questions to long in-home play tests where kids used the sets freely for months. Early demos helped leaders feel the spark quickly. What followed was patient validation of play value, technology, and business fit. Conviction did not arrive all at once. It was earned gradually, one experiment, one insight, and one brick at a time.

[07:39] Creativity and AI Leadership With Humans at the Center — When Tom talks about creativity and AI leadership, he brings the conversation back to people. He sees AI as access to shared human knowledge, not a substitute for imagination. As routine work becomes easier to automate, the value of curiosity, intent, and taste increases. AI helps shorten the distance between an idea and making it real. What remains human is deciding what matters, what feels right, and when something is truly finished.

[15:23] Leadership Traits That Drive Lego Innovation — Asked what he looks for in future leaders, Tom points to curiosity that extends beyond one’s own expertise, resilience built through long periods of uncertainty, and values that guide decisions when outcomes are unclear. Strong R&D product development depends on collaboration across disciplines and a willingness to invest effort even when success is not guaranteed. For Tom, leadership means creating conditions where people feel supported taking meaningful creative risks.