Google Demonstrates Experimental AI Capabilities at AdTech 2026

Google debuts experimental AI video rendering and chat-based ad formats at AdTech 2026.

At AdTech 2026 in New Delhi, Google discussed the shift towards entertainment and informational formats such as microdramas, AI-led chat experiences, and large-scale live streaming. Sweta Jhunjhunwala, head of large partner solutions and channel partnership at Google India, highlighted the tech giant’s various innovations in enhancing user experience in today’s consumption era. Emphasizing the need to look beyond “old-school programmatic plumbing”, she outlined Google’s efforts in different dimensions to meet the needs of customers with cutting-edge solutions.

First, Jhunjhunwala noted that Google is pushing the boundaries of generative AI by truly integrating ads that no longer interrupt the content. The company’s system identifies “valid surfaces” within video content, including spaces like a parked car, digital billboard, or even a wall, to place creatives. The demo included a “clickable overlay” that allows interaction alongside embedded placements. Second, Junjhunwala revealed that Google is building chat-based ad formats that understand a conversation’s context and display ads at moments of “high intent” to the user. She demonstrated an example of a chat interface that could intelligently analyze a user’s prompts to suggest purchasing ingredients directly.

Third, Jhunjhunwala showcased agentic capabilities that Google is experimenting with. She delineated systems embedded within ad formats that were capable of surfacing signals such as “viewability” and “reach” as well as presenting and deploying possible solutions directly within the workflow. Fourth, she also referred to Google Ad Manager tools such as “AI help centre guide” and a “conversational tool”, features that make manual report building redundant by allowing users to query performance directly using natural language.

Lastly, Jhunjhunwala noted that AI can predict the value of an ad request even before it is served. Citing the example of live sports as a key use case where scale can reach 65 to 70 users concurrently, AI can enable the shift towards evaluating individual ad requests instead of delivering uniformly across inventory. According to CIO Bulletin, these measures facilitate a higher level of AI-powered predictions for granular targeted advertising. They also help decide when to serve more premium creatives and the method of demand allocation across large-scale events.