The least intrusive way to introduce ads into LLMs is during natural pauses, such as the wait time for a "deep research" query. This interstitial model offers a clear value exchange: the user gets a powerful, free computation sponsored by an advertiser, avoiding disruption to the core interactive experience.

Conversational ads offer an unprecedented one-on-one channel for brands to interact with customers at scale. The resulting data—customer questions, complaints, and feedback—is a goldmine for product development and other business functions, potentially exceeding the value of immediate customer acquisition.

Conventional engagement metrics like likes and shares are often misleading. A more valuable indicator of content quality is dwell time. In an environment where users can easily skip content, their choice to spend more time with an ad is a powerful behavioral signal that the message is resonating.

To evaluate AI's role in building relationships, marketers must look beyond transactional KPIs. Leading indicators of success include sustained engagement, customers volunteering more information, and recommending the experience to others. These metrics quantify brand trust and empathy—proving the brand is earning belief, not just attention.

While AI tools dramatically increase content production speed, true ROI is not measured in output. Leaders should track incremental engagement, conversion lift, and revenue per message. An often overlooked KPI is brand consistency—how often content passes governance checks on the first try.

Open and click rates are ineffective for measuring AI-driven, two-way conversations. Instead, leaders should adopt new KPIs: outcome metrics (e.g., meetings booked), conversational quality (tracking an agent's 'I don't know' rate to measure trust), and, ultimately, customer lifetime value.

The goal for advertising in AI shouldn't just be to avoid disruption. The aim is to create ads so valuable and helpful that users would prefer the experience *with* the ads. This shifts the focus from simple relevance to actively enhancing the user's task or solving their immediate problem.

The next major shift in ad tech is performance-based CTV. This merges the attention of linear TV with the accountability of digital media, allowing advertisers to tie ad spend directly to outcomes like sales—a revolutionary change from traditional television's limitations.

The latest ChatGPT model can analyze a marketing image (like an email or ad) and predict where a human's eyes will go in the first two seconds. This allows marketers to identify visual distractions and optimize layouts for better performance before launch. Initial tests showed a 15-25% increase in click-through rates.