With artificial intelligence (AI) reshaping the B2B marketing landscape, staying ahead of emerging trends is no longer optional—it’s essential. AI is redefining how brands connect with audiences, from the collapse of traditional demand generation funnels to the rise of AI-mediated discovery.
As consumer behavior shifts toward passive discovery and AI-driven recommendations, marketers face both opportunities and challenges. The 2026 Media Trends Report from AI Digital highlights the need for unified customer data, cross-channel orchestration, and a reimagining of success metrics to thrive in this evolving environment.
Mary Gabrielyan, Chief Strategy Officer at AI Digital, sat down with us to discuss with us the findings of the report, including the rapid evolution of AI in programmatic advertising, the challenges of consolidating tech stacks, and the metrics that matter most in omnichannel campaigns.
Demand Gen Report (DGR): What was the most surprising trend or insight you uncovered while compiling this report?
Mary Gabrielyan: What caught us off guard wasn’t that AI is influencing discovery— we expected that. It was the sheer speed and magnitude of the impact. Organic click-through rates are down from 34% to 64%, not because interest has disappeared, but because AI is increasingly resolving questions without sending users anywhere at all.
In effect, the consideration funnel is collapsing. Traditional demand generation paths are being skipped, not optimized. If a brand isn’t represented inside the AI response itself, it never enters the buyer’s mental shortlist — effectively invisible at the moment of decision.
DGR: How do you see the role of AI evolving in programmatic advertising beyond 2026?
Gabrielyan: I see AI moving from optimization to orchestration. Today, most AI in programmatic is focused on bidding and placement, but in the coming years, it will manage full customer journeys across channels, dynamically shifting budget, creative, and messaging based on real-time intent signals.
The bigger shift is AI systems talking to other AI systems: brands optimizing for visibility in AI-mediated discovery, while programmatic platforms optimize delivery to AI-informed audiences. Ultimately, the winners will be the brands with the cleanest, most actionable first-party data feeding those systems.
Biggest Challenges
DGR: What are the biggest challenges marketers face in adopting the trends highlighted in the report? How do you anticipate consumer behavior will shift in response to these emerging trends?
Gabrielyan: The biggest challenge is overcoming inertia. Most teams are still measuring success with old-school metrics like CPMs, clicks, and last-touch attribution— metrics that no longer tell the full story. Embracing these trends often requires rethinking measurement and reorganizing teams around unified customer data instead of operating in separate channels.
On the consumer side, behavior is shifting toward passive discovery. The days of endlessly swiping feeds, hopping between apps, and manually comparing options are starting to fade. Instead, people are increasingly asking AI for recommendations and shortlists. That means fewer brands are considered, but engagement now comes with much higher intent.
DGR: Regarding cross-channel unification, what are the key steps marketers can take to overcome siloed execution?
Gabrielyan: The first step is always identity, not channels. To execute across channels effectively, you need a single, consistent view of the customer, which means investing in CRM and CDP systems before worrying about campaign orchestration.
The next step is agreeing on shared success metrics— not just clicks or impressions, but business outcomes like lifetime value and conversion rates. And governance matters. Cross-functional teams need shared budgets and accountability, as without that, the structural incentives that create silos never go away.
DGR: What are the most common pitfalls organizations face when consolidating their tech stacks?
Gabrielyan: The most common mistake is consolidating for efficiency before clarifying strategy. Teams end up with fewer tools but if your data is still fragmented or your measurement is off, the gaps remain unresolved. Another pitfall is overvaluing feature lists and undervaluing how well systems integrate. A consolidated stack only works if systems actually share clean, reliable data in real time.
Finally, organizations tend to underestimate the change management required. Tech stack consolidation fails more often due to internal resistance, not because of the technology itself.
Measures of Success
DGR: What metrics should marketers prioritize when measuring the success of omnichannel campaigns?
Gabrielyan: To measure success in omnichannel campaigns, focus on unified customer behavior, not just channel activity. Metrics like customer lifetime value, cohort-level conversion rates, and incremental contribution by channel reveal more than reach or frequency alone.
It’s also important to check your share of AI visibility because that’s increasingly where demand is being shaped — are you appearing in AI-generated recommendations and search results? Pay attention to signal quality: is your targeting based on strong first-party data, or on degrading third-party signals? Clean, reliable data is the best predictor of long-term performance.
DGR: Which emerging channels (e.g., CTV, DOOH, in-game advertising) show the most promise for full-funnel strategies, and why?
Gabrielyan: Right now, CTV and retail media stand out as the most effective full-funnel channels. CTV gives brands near-universal household reach and, increasingly, the ability to connect exposure to real outcomes, not just awareness.
Retail media is compelling for a different reason. With spend approaching $69B, it offers true closed-loop measurement built on first-party purchase data. You can see the impact from the impression all the way through to sale.
DOOH and in-game advertising are interesting, but they’re still largely upper-funnel plays until measurement improves. Audio and podcasts are often overlooked, yet they combine high engagement, low clutter, and rapidly improving attribution.
DGR: What do you see as the next big disruption in programmatic advertising after AI?
Gabrielyan: I see the next big disruption happening around privacy and identity. With third-party data disappearing, marketers who can leverage first-party data while keeping it private will have a huge advantage.
Retail media networks are another area to watch. They’re essentially building walled gardens with richer data than traditional publishers, which could shift programmatic spend away from open exchanges toward closed ecosystems anchored in actual purchase behavior.
Strategies Moving Forward
DGR: How do you expect the balance between creative quality and data-driven optimization to evolve?
Gabrielyan: Creative quality and data-driven optimization are converging, not competing. AI can test at scale, but the data shows that high-quality creative matters more than ever because attention is limited. The future isn’t about choosing between creative and data; it’s about using data to understand what truly resonates, then giving creative teams the freedom to do what they do best: craft original and compelling work.
Brands that treat creative as just a variable to optimize, rather than an art to perfect, will fall behind. Data should guide creative strategy, not replace creative judgment!
DGR: What advice would you give to marketers looking to future-proof their strategies for the next five years?
Gabrielyan: If you want to stay ahead over the next five years, focus on three things: your data, your visibility, and trust. Invest in first-party infrastructure— unified CRM, CDP, and clean-room capabilities are table stakes now. Second, shift from chasing traffic to earning presence in AI-mediated discovery, and third, treat transparency and verification as performance levers, not compliance chores.
Brands that focus on durable relationships and clean, actionable data will outlast those chasing the latest tactical hack.
