Industry Perspectives | AI and Audience Strategy: Brands’ Next Competitive Advantage

The advertising industry is entering a phase of structural transformation, where AI, privacy, and organizational change are reshaping how brands build and activate audiences. As these shifts accelerate, long-standing models are breaking down. AI is moving upstream, from execution to decision intelligence, while privacy is redefining data use in a future that won’t rely on fragile IDs. Siloed media and measurement models are also becoming harder to sustain.

We caught up with Ryo Matsumoto, Country Director, Japan at Ogury, to explore what this means for brands in the region and where competitive advantage will come from.

Many CMOs are under pressure to demonstrate clearer business impact. But what does ‘impact’ actually mean now?

In today’s risk-averse market, every dollar spent needs to be tied to clear business outcomes. As a result, brands are focusing more on mid- and lower-funnel KPIs, with impact no longer defined by reach or channel presence alone. 

At the same time, many still build separate audience strategies for each channel, from CTV to retail media, social, and gaming, which weakens overall coherence. True impact comes from a more unified approach, where planning is anchored around a consistent audience strategy. In this model, channels become distribution choices, while the core audience remains stable across touchpoints.

What key trends are you seeing in Japan when it comes to audience strategy and AI? 

Brands are looking to build a more complete understanding of their audiences. Initiatives like the dentsu persona hub, developed in partnership with Dentsu, combine our proprietary data with their consumer insights to build in-depth personas that can be activated across video, social, and the open web. This helps align campaigns with real consumer interests and deliver more relevant campaigns across channels.

When it comes to AI, automation has optimized media buying, but performance still depends on who you reach. If the audience isn’t right, automation won’t fix it. Our Persona Intelligence turns scattered signals into clearer insights into behaviors and motivations, making audience selection the real differentiator.

How can brands maintain a consistent audience strategy across such a highly fragmented media landscape?

Most organizations still manage each channel independently, with separate KPIs, measurement methodologies, and data sources that trap valuable insights within individual platforms. This means advertisers are left with a fragmented view, where data from one channel rarely informs another.

To address this, brands need to move beyond siloed approaches and build a more unified view of their audiences. This enables better coordination across channels, reduces duplication of efforts and spend, and allows for more effective frequency management.

Beyond efficiency gains, how do you see AI influencing decision-making for marketers over the next few years?

Chatbots and AI assistants are shifting where influence occurs. As they guide purchase decisions, the signals shaping recommendations originate from media coverage, creative campaigns, influencer endorsements, and public conversations across communities and creator platforms.

In the AI era, large language models act as cultural aggregators, absorbing news, reviews, and other public signals. For brands, showing up in these recommendations means showing up in the culture, and that starts with creativity. While digital advertising has historically focused on precision targeting, research consistently shows creativity drives roughly half of campaign outcomes. 

As data privacy expectations continue to evolve globally, how are brands and agencies adapting their approach to audience data and targeting?

For years, digital marketing operated on the premise that the more data you could collect, especially deterministic data, the more effective your advertising would be. This approach fueled an era of identity graphs, cross-device tracking, and large-scale behavioral profiling. But that model is now reaching its limits.

Privacy expectations and public pressure have forced brands to be more selective about the data they collect and how they use it. In parallel, new approaches like the dentsu persona hub are demonstrating that relevance doesn’t require surveillance.

As data privacy expectations continue to evolve globally, how are brands and agencies adapting their approach to audience data and targeting?

From AI-driven optimization to data clean rooms, an increasing number of tools are enabling brands, agencies, and tech partners to collaborate more closely and share insights securely. For brands, this means relying on trusted partners, as many of these capabilities are complex and difficult to build in-house.

At the same time, a key challenge remains the gap between planning and activation. Each platform has its own audience definitions, creating fragmentation and making it difficult to stay true to a campaign’s strategic intent. Bridging that gap, with consistent personas from planning through execution, is how agencies and technology partners can help brands move forward.