GWI’s Connecting the Dots 2026 report cuts through the noise with a reality check. AI has become table stakes, but the insights it’s producing are increasingly generic. At the same time, social hasn’t lost relevance, it’s become the dominant attention layer shaping how people discover, validate, and ultimately decide what to buy. When every brand has access to the same AI tools and the same platforms, advantage no longer comes from adoption. It comes from how well you connect AI, consumer data, and social influence into a single, insight-led strategy.
For brands planning 2026, this isn’t about doing more. It’s about doing smarter: understanding where attention is earned, where confidence is built, and where demand is actually formed. Below we break down the two most critical insights from GWI’s report and what they mean for how brands should be planning next.
AI Isn’t Your Advantage in 2026: Your Data Is
If you’re heading into 2026 thinking AI alone will unlock growth, the Connecting the Dots 2026 report has a reality check for you. Yes, AI is everywhere. Yes, it’s fast. And yes, it’s already baked into most marketing workflows. But here’s the uncomfortable truth: AI without high-quality, structured consumer data is making marketing insights worse, not better.
GWI’s research, built on millions of global respondents across consumer, professional, and youth panels, makes one thing clear: brands that rely on generic, web-scraped AI outputs are converging on the same audiences, the same strategies, and the same media plans. Differentiation isn’t coming from the tool anymore. It’s coming from what you feed it.
At Code3, we operate with the understanding that for our clients, this is the moment where AI-powered marketing strategy stops being about speed and starts being about substance.
AI Is Everywhere. Strategic Advantage Is Not.
Let’s start with the headline stat everyone’s quoting: 84% of U.S. marketers are already using AI professionally, making it the third most-used input in decision-making, ahead of traditional research tools like whitepapers and social listening platforms.
On paper, that sounds like progress. In practice, it’s creating a new problem. AI isn’t giving brands better answers, it’s giving everyone the same ones.
Most AI tools today pull from open-web sources that have potential to be:
- Outdated
- Unsegmented
- Biased toward majority audiences
- Frozen in time
GWI shows how this plays out in the real world. AI-generated “insights” default to predictable conclusions: Gen Z cares about sustainability and TikTok, everyone should be on every channel, and the target audience looks suspiciously middle-aged and generic.
That’s not insight. That’s consensus.
What This Means for Code3 and Brands
At Code3, we don’t view AI as a strategy. We treat it as an accelerant. The advantage isn’t using AI, it’s connecting AI to trusted consumer, retail, and commerce data so it can surface what humans miss.
When AI is layered on top of:
- Retail media performance data
- First-party customer signals
- Audience panels like GWI
- Category-specific behavioral nuance
…it stops producing average answers and starts revealing non-obvious growth signals.
This is why at Code3, our approach to AI-enabled strategy prioritizes insight-led planning over execution-only media plans. Faster doesn’t matter if you’re running in the wrong direction.
The Intent vs. Behavior Gap Is the Real Growth Engine
One of the most powerful sections of GWI’s report tackles a long-standing marketing blind spot: consumers rarely do what they say they’ll do. Despite widespread acknowledgment of how important consumer insights are, nearly 50% of business decisions are still made without them. Why? Because insights are often slow, fragmented, or difficult to operationalize.
AI changes that, but only if it’s connected to real data.
The Myth of “Impulse”
What Marketers often label as “impulse buying” isn’t spontaneous behavior, it’s latent demand finally being activated.
GWI analysis across major categories makes this clear:
- Over half of consumers globally make impulse purchases online at least once a month
- 1 in 5 tech buyers and 1 in 10 travel buyers report impulse purchases: categories we typically think of as high-consideration
- In luxury, 50% of buyers who say they’re “always impulsive” already had a specific product in mind
The takeaway? The traditional funnel—awareness → consideration → conversion is breaking no longer reflects how people actually buy. Demand is always on. Purchases happen when confidence peaks, not when intent is declared.
What This Means for Brands
For brands planning 2026 budgets, this has serious implications:
- Lower-funnel efficiency alone won’t capture demand
- Mid-funnel influence needs to start earlier and stay on longer
- Media strategies should assume the consumer is always in-market
At Code3, we use data-driven audience segmentation and AI-powered insight models to identify when confidence spikes through social proof, timing, value perception, and cultural relevance, not just when someone clicks “add to cart.”
That’s how latent demand becomes revenue.
Social Isn’t Dying. It’s the Attention Layer.
Every year, someone declares social media dead. GWI’s data says the opposite.
Globally, consumers spend:
- 7+ hours per week on social platforms
- 6.5+ hours per week on short-form video
Combined, time spent on social and short-form video exceeds TV, streaming, and radio combined. For Gen Z, that number climbs to nearly 18 hours per week. But here’s the shift brands need to understand: social has become less social and more entertainment-first. People are posting less, but consuming more.
Why This Matters for Brands
Social isn’t just discovery anymore, it’s validation.
Across categories:
- Health & Beauty relies on education, peer proof, and trust
- Retail & Fashion sees trend discovery and in-feed shopping accelerate purchase decisions
- Home categories use social inspiration and aesthetic to fuel consideration cycles
This means social can’t be treated as a support channel. It’s a primary driver of confidence and conversion. Our POV: creative relevance beats frequency. Winning on social in 2026 requires culturally aligned creative, not more impressions.
Gen Alpha Is Not Gen Z (And Brands Can’t Miss Again)
If there’s one audience brands consistently get wrong, it’s the next one.
Gen Alpha (the cohort born roughly between 2010 and 2024) turns 16 in 2026. And GWI’s data shows they’re already influencing real spend:
- Over 50% of kids aged 8–11 help decide purchases across gaming, food, clothing, and apps
- Among 12–15s, that number jumps to 75%+
- Over 20% of 12–15-year-olds globally make online purchases weekly, peaking at 25% in the U.S.
This is not “mini Gen Z.”
What Makes Gen Alpha Different
- Parents are more intentional about screen time
- Kids are balancing digital fluency with IRL experiences
- Gaming is social, creative, and communal, not isolating
Over three-quarters of Gen Alpha regularly game, using platforms like Roblox and Fortnite to build, collaborate, and socialize.
For brands, your Gen Alpha strategy must be category-specific:
- Retail & Fashion: identity, creativity, and co-shopping
- Health & Beauty: early affinity via parents + peer influence
- Home: indirect influence on household decisions
Additionally, if brands want to avoid the Gen Z déjà vu, they must ground next-gen audience strategy in real behavioral data, not assumptions.
The Bottom Line
The biggest takeaway from GWI’s 2026 research isn’t about any single trend, it’s about connection. AI needs better data to produce meaningful insight. Social needs stronger creative relevance to earn attention. And consumers need brands to show up before, during, and long after the moment of purchase.
When those pieces work together, strategy stops being reactive and starts driving growth. For Code3 and our clients, that’s the opportunity ahead: using insight-led, AI-enabled strategies to uncover what others overlook, and turning that understanding into real results.
The brands that win in 2026 won’t be the ones with the flashiest tools. They’ll be the ones asking better questions, and feeding AI the data it actually needs to answer them.