Conversational AI transforms marketers’ toolkits

As conversational AI becomes one of the primary interfaces for product discovery, the rules of engagement are changing fast. Users no longer rely on static search results, sifting through a list of indexed results that may or may not be what they are looking for. Instead, users can now ask questions and receive answers in conversational form — whether looking for trendy new shoes, or doing deep research — without ever having to click on a link. This shift is fundamentally reshaping how brands show up, advertiser participation, and how impact is measured.

Conversational interfaces are reshaping discovery

According to a 2025 study, 84% of advertisers have observed significant shifts in consumer behavior away from traditional search and web browsing, driven in part by the rise of AI-powered answer engines.

The rise of AI tools like ChatGPT, Perplexity, Gemini, and Copilot marks a fundamental shift in user behavior. Instead of typing keywords, people now engage in multi-dimensional conversations that reflect a user’s full intent. These interactions not only generate stronger intent signals, but also bypass traditional ad formats and attribution paths– reports outlining Walmart’s AI shopping agent, Sparky, offer in-market examples of how this may work.

In this new paradigm, data is becoming more valuable than ever. Every query, response, and agent-assisted decision adds to a growing pool of semantic, behavioral, and identity-rich data. Brands that can adapt to this new shift, leverage tools, source data in a trustful and ethical way, and figure out how to do it interoperably will be the winners.

Just as Sparky offers with its summaries, comparisons, and suggestions, think “sponsored suggestions,” embedded calls-to-action, and product recommendations woven into natural dialogue. Conversational AI will make all of these use cases possible, bringing fresh new ways to connect with consumers and deepen engagement.

As advertisers cut display ad budgets by up to 30% as consumers leave the open web (per Forrester), for brand marketers, conversational ads can offer:

• Higher relevance 
• Better engagement via personalized messaging and persistent conversations
• Closed-loop attribution when paired with identity

Why data interoperability is non-negotiable

To thrive in a chat-first world, brands and platforms must align across three pillars:

Activation

Seamless audience onboarding across platforms and agents is essential. Without the ability to link consumers across all of the AI touchpoints they engage with, marketers won’t be able to activate and personalize them in valuable ways. 

To maximize effectiveness, marketers need interoperable, omnichannel activation that reaches not just AI destinations, but everywhere their customers are spending time. At the same time, this transparent understanding of customer journeys will not just help marketers better personalize ads, but also prevent them from redundant or wasted advertising.

Optimization

AI’s ability to provide real-time feedback loops, enabled by interoperability, unlocks powerful optimization.

Solutions like dynamic creative optimization offer unprecedented levels of personalization, testing, optimization, and effectiveness when applied to the explosion of signals and range of different customer journeys as people engage with AI. Interoperability enables marketers to add DCOs to their marketing stack and take advantage of these cutting-edge solutions.

As marketers look for a unified view across all of their investments, interoperability helps shed visibility into how their AI integrations are performing, allowing them to reallocate investments to the most effective ones.

Measurement

Lastly, interoperability is also crucial to measuring the AI-powered ecosystem with accuracy.

The addition of new data types associated with conversational AI – necessitating tools that understand things like semantic relevance and user intent – means marketers will need measurement tools capable of assessing them. These measurement tools need interoperability with the rest of the marketing stack, in order to connect their insights and help marketers make informed omnichannel decisions.

Furthermore, as the universe of customer interactions expands with the proliferation of AI destinations, as well as unique touchpoints within AI conversations, marketers need proper measurement with “multi-turn” interactions. Just as clean room measurement has helped to enable cross-media insights, it also helps power transparency for marketers into these complicated AI journeys, giving marketers the ability to look across every part of the customer journey at once.

Help us shape the future

Through LiveRamp’s solutions, we help to provide a critical layer for conversational AI advertising, providing identity, activation, measurement and more.

As agents become the new interface, LiveRamp will help to govern responsible data collaboration, power agentic delivery, and ensure outcomes are measurable and respect consumer choice. If you’re working on navigating these paradigm shifts, we’d love to hear from you at LiveRampAI@liveramp.com