In a landscape dominated by social media, influencer marketing, and streaming platforms, traditional broadcast can seem outdated, expensive to run, inflexible, and disconnected from the fast-paced digital world. But for some modern retailers, AI is quietly transforming broadcast into a powerful, data-driven component of a well-rounded omnichannel strategy.
Reframing Broadcast for a Digital Age
For brands targeting a visual or demonstration-driven sales model, particularly with older demographics, television can still offer a compelling way to tell product stories in depth. The historical barrier has been cost- maintaining a 24/7 shopping channel typically requires a large production team, studios, and significant resources.
This is where AI is shifting the paradigm. Pre-recorded segments, when combined with AI-powered automation tools, can now be dynamically assembled into full-length programming based on real-world variables, like trending products, seasonality, weather, or stock levels. The result is content that feels timely and responsive, without the traditional production overhead.
For business leaders considering this route, the key is not to chase AI for its novelty, but to deploy it where it solves a clear operational challenge. In the case of broadcast, AI can:
- Automate programming decisions based on live data inputs.
- Reduce production costs by dynamically assembling existing assets into fresh content.
- Extend the shelf-life of pre-recorded content by repackaging it for different seasons, times, or audiences.
- Bridge the gap between digital and traditional media, allowing consistent messaging across platforms.
This approach is particularly powerful for businesses already producing strong visual content, as it turns existing assets into long-form programming without significant new investment.
Understanding Audience Segmentation
One of the biggest advantages of integrating AI with broadcast is the opportunity to unlock new or underserved customer segments. While younger audiences may favour social media and short-form content, many consumers still value presenter-led, in-depth demonstrations, especially in categories like home, health, or problem-solving products. For these audiences, television remains a trusted and accessible format.
Rather than replacing digital efforts, broadcast can complement them, creating a fuller customer journey that spans platforms. Businesses can then use insights from each channel, whether it’s high engagement on a Facebook ad or viewer retention on a broadcast segment, to inform and refine messaging across the board.
Creating Consistency Across Channels
Consistency in tone, message, and customer experience is critical in any omnichannel strategy. Regardless of whether a customer first encounters a brand via social media, a website, or a television screen, the core values and experience should remain the same. AI tools can support this by helping to synchronise content scheduling, automate recommendations, and track engagement data across all touchpoints.
Importantly, any AI-driven content strategy must remain human at its core. The technology enables scale and efficiency, but the storytelling, whether through a host on television or a caption on Instagram, must still reflect authenticity, empathy, and trust.
Looking forward, AI will likely push broadcast even further, from segment-based automation to personalised programming tailored by lifestyle, location, or behaviour. While this level of customisation is still emerging, the principle remains the same: using technology to deliver relevant, engaging content where and how audiences prefer to consume it.
For businesses exploring their next step in omnichannel strategy, broadcast shouldn’t be dismissed as a legacy medium. With the right tools and approach, it can become a responsive, cost-effective, and highly engaging channel, especially when integrated with digital insights and powered by AI.
