Interview
92% of AI-Assisted Shoppers Say AI Shapes What They Buy. Is Your Content Keeping Up?
marketing 16 Apr 2026
During the 2025 holiday season, generative AI and AI agents drove an estimated $262 billion in global retail revenue, accounting for roughly 20% of total sales. Traffic from AI search channels like ChatGPT and Perplexity doubled year over year. Shoppers referred from AI-powered search converted at nine times the rate of social media referrals.
What does this mean for how brands reach consumers? I see it playing out on three fronts:
● An evolution of existing channels
● The emergence of new agentic channels
● And the need for new marketing operational models
To gauge how far these shifts have actually reached consumers, Skai surveyed 1,000 U.S. shoppers about how they’re using GenAI throughout their shopping journey.
The implication for marketers is clear: the consumer journey is being rewritten in real time.
The habit gap is your window of opportunity
Consumers know AI can help them shop. 86% are aware they can use ChatGPT for shopping. 55% have knowingly used a retailer AI assistant like Amazon Rufus or Walmart Sparky. Nearly half (48%) used AI for product research in the last 30 days.
But 30% say they simply haven’t considered using AI for shopping. The barrier isn’t skepticism or distrust. It’s just not part of their routine yet.
The advertiser side tells a similar story. Skai and Stratably’s 2026 State of Retail Media survey found that 63% of advertisers are already using GenAI, but only 3% are seeing meaningful impact. Consumer behavior is moving, but advertiser readiness isn’t keeping pace.
That gap between awareness and habit represents an early-adoption window. As AI gets more embedded in shopping platforms and the experience gets smoother, that 30% will decline. Brands need to start building presence, test what increases visibility, and figure out who owns AI discoverability.
92% say AI research influenced their purchase.
When consumers use AI for shopping, they’re using it to get smarter before they buy. The top tasks cluster around information gathering: comparing products or brands (37%), finding deals and discounts (32%), checking reviews and pros/cons (30%), and finding product recommendations (28%).
And it’s working: 92% of those who used AI for product research say it influenced their purchase decision. Nearly three-quarters (73%) take further action after an AI recommendation, whether that’s asking follow-up questions, clicking links, or visiting retailer sites. AI is actively shaping what consumers consider and what they ultimately buy.
With this level of AI influence on purchasing decisions, optimizing for AI-readable content can’t stay a side project. Your product feeds, structured data, and brand information need to be built for machines as well as humans. That’s a workflow change, and potentially a new role. Someone needs to own the intersection of content, data, and AI discoverability.
Two-thirds of consumers click through. 29% of Gen Z buy directly.
The influence goes beyond research. Two-thirds of consumers (65%) have clicked from an AI tool directly to a retailer site. This isn’t passive browsing. Consumers are following AI recommendations to the point of purchase.
Gen Z leads here. They use AI for comparison shopping at 1.5x the rate of Boomers (44% vs. 30%). And 29% of Gen Z have made a purchase directly through ChatGPT’s shopping feature, compared to just 5% of Boomers. Shopping queries on AI platforms are growing faster than any other category, and referral traffic is converting at rates retailers cannot ignore.
In performance terms, AI is behaving like a high-intent referral channel layered above existing retail infrastructure.
That has implications for measurement. Most brands can track paid search, paid social and retail media performance with precision. Far fewer can measure how they appear within AI-generated results, or which product attributes and data signals influence recommendations.
That’s not a media gap. It’s a capability gap.
Replenishment-Heavy Categories Lead, Especially Among Gen Z.
When consumers show openness to AI-driven purchasing, it’s concentrated in predictable categories. Groceries and household essentials lead at 25% comfort with AI auto-purchase, followed by entertainment and media (23%), beauty (20%), and electronics (20%). Replenishment beats consideration. Categories with predictable repeat purchases see higher AI acceptance than those requiring personal judgment.
Gen Z accelerates the timeline. 67% are comfortable with AI auto-buying within set rules, compared to just 19% of Boomers. A majority of Gen Z say they would buy through AI instead of going to a retailer site directly.
Replenishment-heavy categories like grocery and household essentials will see AI-driven purchasing integrated into existing retail platforms first. If you’re in those categories, treat AI optimization with the same urgency you bring to search and retail media today. Start building your agentic playbook in these categories: test formats, learn what influences recommendations, and establish benchmarks.
Conclusion: As the consumer journey is being rewritten in real time, what can advertisers do?
The latest holiday season proved that AI is a present reality contributing hundreds of billions in revenue. Our survey reveals the nuance beneath the headlines: consumers are embracing AI as a research tool while remaining cautious about handing over purchase decisions. But that caution is evaporating fastest among Gen Z, which is a preview of where mainstream behavior is heading over the next three to five years.
The consumer data confirms what the broader market signals have been pointing to. Existing advertising channels are evolving as AI reshapes discovery and research. A new agentic channel is emerging with real, measurable activity. The marketing organizations that will win aren’t the ones bolting AI tools onto existing workflows. They’re the ones rethinking how their teams, data, and media strategies work together across all three fronts.
Building a Thriving Business Without Spending on Digital Ads
marketing 15 Apr 2026
Create High-Value SEO Content
Cultivate Partnerships and Collaboration For Greater Outreach
Connect With Customers Directly, In-Person and Online
Make Your Business as Visible as Possible
Target Niches Where Customers Are Plentiful
Final Thoughts
How AI and Data Are Rewriting B2B Growth Craig Dempster, CEO of Trilliad
marketing 10 Apr 2026
Nearly all organizations have adopted some sort of AI tool (if not multiple), but many say that the ROI isn’t there. Why is this happening? What’s holding back B2B companies from seeing true success with today’s advanced AI tools?
AI doesn’t fix broken systems. It accelerates them.
That’s the core problem. Most organizations are dropping AI into environments that are already fragmented. Disconnected data. Siloed teams. Inconsistent workflows. Leaders expect AI to clean that up. It doesn’t. It amplifies whatever’s already there. If the foundation is messy, AI makes the mess bigger.
The second issue is intent. Too many companies treat AI as a tool to deploy rather than a decision to make about where it can actually move the business forward. So teams automate content, automate reporting, automate outreach, and then wonder why the numbers don’t improve. Automation without alignment isn’t progress. It’s just faster noise.
The organizations seeing real ROI started differently. They got clear on how marketing, sales, and customer data could work together first. Then they applied AI where it could sharpen a process or improve an outcome. That sequence matters.
Your 2026 Growth Imperatives suggest that the issues are not with the AI tools themselves, but the underlying data infrastructure. How can teams make their data as actionable as possible to keep up with modern businesses today?
Stop treating data like a reporting function. Start treating it like a decision engine.
Most B2B organizations aren’t short on data. They’re short on shared data. CRM, campaign platforms, sales tools, customer platforms are all collecting signals, but nobody’s looking at the same dashboard. Marketing interprets results one way. Sales interprets them differently. Customer Success is working from something else entirely. That’s not a data problem. That’s an alignment problem.
Making data actionable starts with one question across every team: which signals actually matter? Which accounts are engaging? What topics are moving buyers? Where is momentum building, and where are deals stalling? When teams agree on those answers and pull from the same source, data starts driving real decisions.
That’s the shift. Shared signals. Shared accountability. One view of what’s working.
How should B2B marketers be rethinking their brand-to-demand strategy to stay relevant and visible, given AI’s role in search?
Here’s the reality: many buyers are encountering a brand inside an AI-generated answer before they ever visit their website. That changes everything about how visibility works.
AI answer engines are now shaping first impressions. So the question marketers need to ask isn’t just “where do we rank?” It’s “is our content structured in a way that AI systems can actually interpret and surface?” If the answer is no, you’re invisible at the most important moment in the buyer’s journey.
Content needs to be clear, authoritative, and built around the exact questions buyers are asking.
And brand and demand can’t keep operating as separate functions. The brands that stay visible are the ones creating consistent, memorable signals over time, so that when a buyer is ready to move, there’s no question about who they think of first.
Your guide emphasizes that sales enablement should move away from sporadic sales training sessions. What should effective sales enablement training look like today?
One-time training creates short-lived energy and very little lasting change. Most organizations know this, and they keep doing it anyway.
The problem is that a standalone event can’t keep pace with how buyers actually behave. Sellers need continuous reinforcement tied to real conversations and real customer signals, not a slide deck from last quarter. Managers need to coach against what’s happening right now in the field, not what was happening six months ago when the last training was scheduled.
Effective sales enablement today is embedded in the operating system of the business. It’s tied to measurable outcomes. It shows up in how deals are reviewed, how feedback is delivered, and how teams are developed week over week. The strongest organizations don’t treat sales development as an event. They treat it as part of how the business runs.
Traditional lead generation models often prioritize volume over engagement. How is the rise of AI and interactive content changing what effective lead generation looks like in 2026?
Lead generation is no longer about volume. It’s about intent.
For years, teams measured success by how many contacts they captured, even when most of those contacts showed no real buying signals. That model is breaking down fast. Buyers expect immediate value and more control over how they engage. Handing over an email address in exchange for a gated PDF isn’t the exchange it used to be.
Interactive content and AI are changing the pattern. When a buyer engages with a conversational tool that gives them something useful right away, that’s a different signal than a form fill. AI helps teams read those signals and separate casual interest from real momentum, so the response can be personalized and timed correctly.
What does it actually mean to “operationalize AI” inside a revenue organization? What are some areas where many companies go wrong?
Operationalizing AI means it’s no longer a side project. It’s how the business actually runs.
In a revenue organization, that means AI is embedded across marketing, sales, and customer success, improving decisions, timing, and execution in real workflows, not just in pilot programs or innovation labs.
Most efforts stall for three reasons: poor data quality, fragmented systems, and a lack of operational enablement. Companies implement AI before the foundation is ready. And without a solid foundation, AI has nothing meaningful to build on.
The other common mistake is letting teams operate against different goals with different measurements. If Marketing, Sales, and Customer Success aren’t aligned on what success looks like, AI can’t bridge that gap. It will just automate the misalignment. Get the foundation right first. Shared goals, shared data, shared accountability. Then AI becomes a real accelerator.
Keeping Humans in the Loop: How Adora Is Turning AI Into a True Performance Engine for Marketers
marketing 7 Apr 2026
You’re stepping into the VP of Revenue role at Adora at a time when AI is rapidly reshaping marketing. What about Adora’s approach convinced you this was the right moment to make the move?
Almost every CMO today is being asked by their CEO how they're leveraging AI both now and in the future. What drew me to Adora is that we give marketers a genuine answer to that question without asking them to abandon what's already working. Adora preserves the marketer's control over performance measurement and brand integrity, while enhancing creative generation and execution to help brands sell more products, more efficiently. It's a tangible, low-disruption path to realizing the benefits of AI and that's a compelling story in a market full of noise.
Many platforms claim to use AI for performance marketing, how does Adora’s model actually give brands more direct control over outcomes, rather than abstracting decision-making away from them?
The key distinction is that Adora keeps the human in the loop by design. Brands retain the ability to approve or reject anything our AI produces, and they define the rules of what success looks like. That combination human intent guiding machine execution is still enormously powerful. AI doesn't replace the marketer's judgment; it amplifies it.
Creative is increasingly being talked about as the primary driver of performance, how is Adora operationalizing creative as a true performance lever rather than just a brand asset?
It starts with being precise about what you want the creative to do. If the goal is a click, the creative needs a reason to compel action an offer, a product launch, a limited-time moment. If the goal is brand awareness, the brief looks completely different. Adora helps brands connect creative decisions directly to business objectives, so every asset is built with a measurable outcome in mind, not just aesthetics.
As AI-driven automation increases, where do you see the balance between human strategy and machine-led execution evolving, particularly for brands focused on growth?
AI performs best when humans provide it with clear objectives and context. The world changes constantly, and AI can't yet anticipate the future on its own. When a brand knows a market shift is coming, or wants to get ahead of a change in consumer behavior, the ability to feed that strategic context into the machine is where the real competitive advantage lies. The brands that win will be the ones who treat AI as a highly capable partner not an autopilot.
From a revenue and go-to-market perspective, what are you prioritizing in your first 6–12 months to scale adoption and demonstrate real business impact for advertisers?
Getting the fundamentals right. We have a clear vision at Adora for where we can genuinely move the needle for the industry, and staying disciplined about that focus is essential. AI is a broad category, and it's easy to get pulled toward solving problems that aren't core to what you're built for especially when early revenue is on the table. But we're building relationships with brands that we intend to last for decades, not months. That means setting them up for real, sustained success from day one, which ultimately sets Adora up for the same.
The Brands Winning Digital Growth Aren't Chasing Attention They're Building Habits
marketing 7 Apr 2026
Digital 100 U.S., Similarweb’s annual ranking of the fastest-growing websites and apps, points to something more structural happening beneath the surface. Across consumer categories, the brands with the most sustained momentum aren't necessarily the loudest ones. They're the ones that have quietly become indispensable.
Dependability Is the New Differentiator
Fashion & Apparel tells the story clearly. The category's standout performers, Comfrt (+330.2%), Editorialist (+246.3%), Quince (+138.5%), aren't built around trend cycles or flash sales. What they share is clarity: clear positioning on value, fit, and everyday relevance. They reduce the friction around the decision itself.
In a market where consumers are more intentional and more cost-conscious than they were three years ago, that kind of dependability is turning into a genuine growth engine. The brands that make it easy to say yes, and even easier to come back, are pulling away from those still chasing the next campaign spike.
Shopping Is Becoming a Tool, Not an Event
On mobile, the story gets more interesting. Overall app downloads in Fashion & Apparel actually fell year over year - yet Whering: Your Digital Closet, Depop, and LTK all posted significant gains. The through-line isn't category or aesthetic, it's function. Whering helps people get more out of what they already own. Depop turns the closet into a marketplace. LTK wraps commerce inside creator recommendations people already trust. They're not destinations you visit when you're in shopping mode. They're tools you reach for as part of an existing routine.
That pattern repeats across the Digital 100. In Beauty & Health, the fastest-growing apps are step counters, running trackers, and nutrition logs, habit-reinforcing by design. In Food, it's quick-service apps that make reordering feel like muscle memory. The platforms pulling ahead aren't interrupting daily life. They're threading themselves into it.
What Loyalty Actually Looks Like Now
For brand leaders, this reframes the question. The real growth metrics aren't just acquisition numbers. They're behavioral: How often do customers come back? How quickly? How much effort does it take them?
Traditional loyalty mechanics, points, discounts, limited-time offers, still have a role. But they're accelerants, not anchors. The deeper drivers are structural: frictionless checkout, preferences that persist, personalization that compounds over time, pricing transparency that builds trust before the first purchase ever happens.
Behavioral loyalty is a product of the experience itself. The second visit should feel easier than the first, and the third easier than the second. And the brands seeing durable growth are the ones engineering exactly that compression - quietly, systematically, visit by visit.
The Shift Worth Acting On
Retail strategy has long been organized around peaks: seasonal launches, promotional events, product drops. These still matter. But the Digital 100 makes clear that the brands accumulating the most durable digital advantage are doing something different in parallel. They're not optimizing for spikes. They're designing for patterns.
That requires a genuinely different kind of investment. Features that improve with use. Value made visible at every touchpoint, not just at the moment of sale. Digital experiences built not as funnels to be managed but as products to be continuously refined.
And perhaps most importantly: an honest reckoning with what friction costs. Every abandoned cart, every confusing size guide, every extra step in checkout is a reason not to return. In a market defined by choice overload and decision fatigue, convenience isn't a feature, it's a retention strategy.
The New Growth Edge
The brands growing fastest in the Digital 100 aren't doing it through hype cycles. They're doing it by making the next visit feel inevitable rather than effortful. Comfrt didn't grow 330% on the back of a single campaign. Depop didn't reach 5 million monthly active users by going viral once. These outcomes are the product of systems – digital experiences that make returning easier than starting over.
In an era of economic scrutiny and attention scarcity, that's the real competitive advantage. Not who captures the moment. Who becomes part of the routine.
Corporate Event Engagement Has a New Baseline
marketing 6 Apr 2026
Two signals make the shift hard to ignore. Freeman found that 64% of attendees say immersive experiences are the most important element of the event experience. Meanwhile, research firm GitNux reports that 62% say personalized communication around events increases their loyalty. Immersion and personalization are not “nice to have” line items anymore. They are the standard people compare every event against, whether they are in healthcare, finance, manufacturing, or SaaS.
That’s why event technology hasn’t just evolved; it’s transformed. Today, event technology supports more than logistics. It links the attendee experience directly to revenue, retention, and growth.
Connected Experiences Need Connected Data
The biggest engagement gap today is not what happens on site. It’s the disconnect between the event and everything around it.
A single customer might register from an ad, attend two sessions, book a meeting, and spend fifteen minutes in a product workshop, only to receive a follow-up email that treats them like a total stranger. This erodes customer trust and wastes the richest signal available to most marketing teams, which is what actions a person took in real-time, when marketers had the chance to lean in. Ignoring a customer's real-time engagement is a significant oversight.
This is why event technology now sits at the center of the marketing and sales ecosystem. When event data lives on an island, it stays stuck as a recap deck and a lead list. When it is integrated with the rest of the martech stack, it becomes usable. It can trigger the right next message, route the right lead to the right team, and shape the next experience based on what worked.
Measurement changes too. Instead of debating whether an event “felt successful,” teams can see what content drove meetings, what sessions influenced the pipeline, which segments were engaged with most, and where drop-off happened. That clarity is what leaders want when budgets tighten. It is also what event teams need to defend investment and improve with each cycle.
Personalization is the bridge between engagement and outcomes. If 62% say personalized communication increases loyalty, the takeaway is simple. Follow-up should reflect what people actually engaged with. And the more connected the data, the easier that becomes.
Building Engaging Experiences
When attendees say they want immersion, they are not asking for more gimmicks. They are asking to feel pulled into something that makes sense for them. It might be a hands-on lab, a demo that solves a real problem, a roundtable with peers who share their challenges, or a guided personalized path through content that matches their role. The common thread is intention.
The problem is that intention is hard to scale when every event is built from scratch. Teams end up spending energy on rebuilding pages, emails, registration flows, session frameworks, and reporting, instead of spending that energy on improving the moments that matter.
This is where repeatability becomes a strategic advantage. When teams templatize what should stay consistent, like branding, key data capture, standard journeys, and core workflows, they buy time back. They can focus on the parts that should be dynamic, like audience-specific messaging, regional preferences, and the immersive elements that make each experience feel alive.
Having the foundation of a data strategy connected to the martech stack helps drive templatization into a reliable and standardized framework. This type of consistency and intentionality makes it easier to tie back to business goals and objectives.
Templates also protect the attendee experience. When registration and communications are familiar and frictionless, people spend less time figuring things out and more time engaging. Consistency does not have to mean sameness. Done right, it creates reliability that makes personalization easier, not harder.
Events Are Becoming the Most Measurable And Memorable Form of Human Connection
Engagement expectations are rising because people are overwhelmed with digital noise and increasingly protective of their time. They want immersive experiences that feel real, and they reward brands that communicate with relevance.
Modern event technology is what makes that possible at scale. It helps teams design connected experiences across the customer journey, standardize what should be repeatable, personalize what should be personal, and prove what worked. The organizations that win will be the ones that stop treating events as isolated moments and start treating them as measurable, connected experiences that build relationships and move the business forward.
The Emergence of Vibe Marketing
marketing 6 Apr 2026
Vibe Marketing is a new era of marketing shaped by generative AI creativity, speed, and intelligence enabling marketers and executives to automate marketing campaigns from client brief to concepts, campaigns to optimization.
The concept draws inspiration from the software engineering world, where “vibe coding” describes using natural language and AI-powered tools to accelerate development, especially for users who do not know how to code. In marketing, the idea is similar: generative AI allows teams to quickly create, test, and iterate on campaigns that once took weeks or months to produce. And, vibe marketing enables professionals with no marketing experience to create brilliant campaigns. AI removes the traditional barriers of production budgets, technical language requirements, and long lead times, allowing challenger brands to act with the speed of a startup and the production value and sophisticated analytics of a global leader.
Searches for “vibe marketing ”increased nearly 700% in the past year, and Forrester found that 50% of B2B marketing decision-makers are already experimenting with or currently using generative AI.
To make Vibe Marketing work, it requires human intellect and artificial intelligence working in concert to create an accurate and comprehensive data foundation, sophisticated modeling, generative audiences and creative production, and a scalable method for measuring impact. The result, authentic, relevant experiences that deliver real ROI.
Smarter decisions about audiences, channels, and creative experiences.
Vibe marketing is not about letting AI do everything; it’s about augmented intelligence where AI accelerates insights and recommendations, while humans act as the compass. According to a recent EMARKETER survey, about 91% of marketers called human involvement "critical" or "very important" in evaluating or generating AI-driven creative.
Vibe marketing enables marketers to act on subtle shifts in consumer sentiment that occur before a trend fully breaks. What a marketer needs is the ability to see how their audience’s engagement changes before their conversion patterns change.
By analyzing unstructured data with the right queries and dashboards through tools like BigQuery, AI can surface those contextual signals and build “intent cohorts” automatically, simply prompting humans for approvals. When these insights are paired with Looker Dashboards or Adobe Customer Journey Analytics (CJA), marketers gain the ability to see the "why" behind these shifts in real-time, allowing them to instantly how their AI models have bridged the gap between raw data and a live customer experience faster and frictionlessly.
Clustering users by intent cohorts and understanding the why behind their structure then makes it easier for marketers to allow AI tools to create personalized, dynamic content. A strong data foundation ensures that their "vibe" is backed by the reality of what their audience actually wants not just today, but tomorrow, too.
Test cultural resonance before you spend
Vibe marketing can also help balance the tension between speed and effectiveness. By creating digital twins of intent cohorts, marketers can simulate how specific personas might react to new creative directions in seconds rather than weeks. This allows companies to test and optimize campaigns in a sandbox environment, ensuring that they scale with the strongest, most authentic content.
Measure what actually moves the needle
The final piece of the puzzle is measurement. Because vibe marketing often triggers rapid content shifts across multiple channels, a linear funnel view won't cut it.
For a truly holistic view, practitioners are increasingly turning to marketing mix modeling (MMM) with tools like Google Meridian. Meridian’s near-real-time calibration capability means you can use it to sense channel efficiency shifts as cultural moments occur, not six weeks later. For marketers making fast creative decisions, knowing in near-real-time that connected TV (CTV) is outperforming paid social this week changes where you put the next dollar.
Coordinate the entire stack for speed
The "possible" outcomes of vibe marketing are only achievable if martech and adtech stacks are properly integrated and flexible enough to handle real-time shifts. In 2026, the focus has shifted from simple automation to autonomous, intelligent systems that empower marketers to move from being task-doers to strategic thinkers.
A successful agentic engine requires a seamless loop:
- Ingest and aggregate: Centralize your web and app data into a warehouse like Google Cloud to get a clear view of your marketplace coverage.
- Analyze and cluster: Use machine learning models to identify high-propensity intent cohorts across BigQuery or Adobe Customer Journey Analytics.
- Synthesize and QA: Use generative AI to iterate with multiple creative variations, using humans as the final quality check for brand safety.
- Activate and attribute: Serve dynamic content and use closed-loop attribution to feed results back into the model.
Drive smarter decisions and faster execution
Vibe marketing is an incredible opportunity to connect with audiences on a human level while scaling your marketing team’s productivity. But most marketers are stuck somewhere in between understanding the “possible” and not knowing how to achieve it because their adtech and martech tools are configured for the world that existed two years ago. The technical foundation is the key to turning these "vibes" into a true marketing engine.
NRF 2026: Biggest Takeaways for B2B Marketers to Stand Out Amongst a Sea of Tradeshow Vendors
marketing 6 Apr 2026
While flashy exhibits turn heads, espresso martinis draw a crowd, and the smell of freshly popped buttery popcorn certainly helps attract booth traffic, the standouts now are those building community, personalizing engagement across the full event lifecycle, and reinforcing their activations with integrated technology that provides actionable data.
NRF creates the blueprint for how marketers and brands can connect one-time engagements directly to long-term, measurable business outcomes and deeper customer relations, backed by technology solutions.
NRF as an Industry Ecosystem
NRF illustrates how a trade show can function as a year-round industry ecosystem, rather than a one-time activation. While the show happens across only three days, its ongoing virtual sessions, in-person meetups, and other available gatherings around the world extend meaningful dialogues beyond the show floor. This sustained engagement creates a common platform where relationships deepen, and ideas evolve over time.
This year’s NRF delivered on its theme of “The Next Now.” The focus was preparing retailers for the future that is unfolding around agentic AI, human-centered experiences, unified experiences, the physical transcending to experiential hubs, and insights.
Because NRF convenes retailers alongside tech providers and other partners, conversations also naturally reflect the interconnected nature of the retail industry today. The activations that resonated most this year were not isolated product showcases, but those that acknowledged the broader landscape and positioned brand narratives and offerings as contributors to an ongoing industry conversation. By embracing this ecosystem mindset, marketers and brands can better signal relevance, credibility, and long-term commitment.
Community as Competitive Differentiator
In a crowded exhibition center stacked with immersive activations and flashy AI tools, attendees this year gravitated toward experiences that offered true substance. The most effective activations weren’t the largest, they were the most intentional.
Brands that hosted smaller group discussions, curated demos, and targeted networking sessions, created space for practical conversations around shared challenges. These interactions inspired more valuable engagement and positioned companies as true partners versus one-time vendors.
For example, brand booths this year tapped cultural touchpoints, with several exhibitors incorporating World Cup fan zones or sports activations such as SAP’s tennis and pickleball themes, and HP/Intel’s sports jersey displays, to draw attention and create immersive physical spaces. These activations worked because they tapped into passions attendees already share like sports, competition, and global events, creating natural gathering points on the show floor. Instead of simply drawing foot traffic, they gave strangers an easier entry into conversation.
The takeaway from NRF 2026 is clear: foot traffic is no longer the primary measure of success. Meaningful dialogue and sustained connection are what differentiate brands, and what can turn event moments into lasting business relationships.
From Ecosystem Engagement to Sustained Momentum with AI
As conferences and trade shows surge back to pre-pandemic scale, the pressure is on to create experiences that are more personalized than ever. But the real question remains: how can marketers implement NRF’s sustained ecosystem and community-based approaches at the same time? The answer lies in technology and data-backed strategies.
By leveraging AI, teams can look beyond isolated actions from one event like booth traffic, engagement metrics, or survey feedback, to understand how attendee experiences impact future pipeline, revenue, and relationships. Traditionally, marketers have relied on surface-level metrics such as number of booth visits, but counting vanity metrics falls short when it comes to understanding how touchpoints over time, or your brand’s ‘ecosystem,’ is influencing business impact.
AI can also boost personalization at the event itself, further inspiring the community-based approach that NRF excels in. While conventional AI relies on human input, AI agents, for example, act independently, functioning as a real-time ‘concierges’ that can tailor suggestions at an event based on user behavior and demographics. This can help to put like-minded attendees in the same group or same session, sparking conversations and insightful discussions. With Gartner projecting that 40% of enterprise applications will include task-specific AI agents by the end of 2026, personalization is becoming embedded and expected infrastructure in events.
Overall, in 2026, high-impact events will be defined by their ability to operate as connected ecosystems powered by integrated data and AI, converting engagement into sustained momentum, rather than isolated activity.
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