How generative AI will reshape advertising and ecommerce strategies
From agent-led shopping to interactive ads, marketers face a new playbook
Generative AI is quickly moving beyond content generation into something far more disruptive for marketing: decision-making support, interactive ad experiences, and agent-led commerce. What once looked like a productivity tool is now evolving into a layer that sits between brands and consumers, reshaping how discovery, evaluation, and purchase happen.
At a recent ADWEEK House Possible fireside, InMobi co-founder Abhay Singhal outlined a near-future where AI agents do much of the heavy lifting in consumer research, while marketers compete inside AI-driven environments instead of traditional channels.
This article explores what that shift means for advertising formats, ecommerce experiences, and the economics of scaling AI in marketing.
Table of contents
Jump to each section:
- The rise of agent-to-agent advertising formats
- Why visual AI is becoming ecommerce’s conversion engine
- The economics problem: can generative AI scale in advertising
- What marketers should know about AI-driven consumer behavior
Patrecia Meliana
The rise of agent-to-agent advertising formats
The most immediate shift is structural. According to InMobi’s Abhay Singhal, advertising is heading toward “agent-to-agent interaction” by 2026, where AI systems represent both consumers and brands in decision-making environments.
Instead of users manually browsing products, AI agents will handle research, filtering options based on preferences like price, style, or brand affinity. The consumer still makes the final call, but the journey becomes mediated.
This creates a fundamentally different ad model:
- Ads are no longer static messages
- They become interactive, conversational interfaces
- They behave more like sales assistants than billboards
Current formats are largely linear. A user sees an ad, clicks, lands on a page, and converts or drops off. In an AI-driven environment, that journey compresses into a single interactive layer where discovery, evaluation, and persuasion happen simultaneously.
For marketers, this means optimizing not just for visibility, but for machine interpretation and interaction quality.
Why visual AI is becoming ecommerce's conversion engine
Generative AI is also accelerating a long-standing trend: ecommerce becoming more visual, immersive, and personalized.
Singhal points to agentic commerce platforms like Glance, where AI can generate personalized product visualizations. For example, instead of imagining how a shirt might look, a user can see themselves wearing it instantly.
This shift matters because many high-value ecommerce categories are inherently visual:
- Fashion
- Furniture
- Home decor
- Pet accessories
Historically, these categories underperformed online compared to books or electronics because they required imagination. Generative AI removes that friction.
The impact on performance is already visible. According to Singhal, campaigns leveraging AI-generated visuals are delivering significantly higher return on ad spend, driven by:
- Increased confidence in purchase decisions
- Stronger emotional connection to products
- Reduced cognitive load during evaluation
This is not just a UX improvement. It is a conversion unlock.
The economics problem: can generative AI scale in advertising
Despite the upside, there is a major constraint: cost.
Serving generative AI experiences at scale is expensive, especially in advertising environments where billions or trillions of impressions are delivered monthly. Running AI models for every interaction quickly becomes unsustainable.
InMobi’s proposed solution is pragmatic:
- Use advertising revenue to subsidize AI token costs
- Design ad formats where engagement offsets compute expenses
In early testing, Singhal suggests this model can become net-positive for publishers, meaning the economics could work if engagement remains high enough.
This introduces a new KPI layer for marketers:
- Not just cost per click or conversion
- But cost per AI interaction and token efficiency
The implication is clear. Creative quality and interaction design will directly influence infrastructure viability.
What marketers should know about AI-driven consumer behavior
Generative AI is not just changing tools. It is reshaping how consumers behave.
Here are the key shifts marketers need to prepare for:
1. Research is outsourced, not eliminated
Consumers will rely on AI to shortlist options, but still want control over final decisions. This means brand presence inside AI systems becomes critical.
2. Ads must become interactive experiences
Static creatives will lose relevance. Winning formats will feel like guided conversations, not interruptions.
3. Personalization moves from segmentation to simulation
Instead of targeting groups, brands will simulate individualized experiences in real time, especially through visual AI.
4. Creative and performance teams will merge
When ads become interactive systems, creative, UX, and performance optimization converge into one workflow.
Patrecia Meliana
5. Measurement becomes more complex
Traditional attribution models break down when AI intermediates the journey. Marketers will need new frameworks to understand influence and conversion.
Patrecia Meliana
Generative AI is pushing marketing into a new paradigm where brands no longer just communicate messages. They participate in decision-making environments shaped by AI agents.
The winners in this space will not be the loudest brands, but the most adaptable ones. Those that design interactive experiences, optimize for AI mediation, and rethink the economics of engagement will have a clear advantage.
For marketers, the takeaway is simple but urgent. This is not a channel shift. It is a system-level transformation of how demand is created and captured.
