SEO based search is shifting from matching keywords. It is now also about how well your content aligns with the map AI models use to understand a topic. This can sound more complicated than it is. Nor is it about doing away with SEO completely.
What it means for PR pros is learning to be consistent. Using rich semantics, or simply put, making sure that your content includes context, relationships and meaning. No more 'Leading brand in the country', but exactly how it is that.
PRmoment India speaks to a range of PR pros to understand how to make AI search work for you and what KPIs you need to track AI-based search.
How does AI search work for your brands?
Two parameters you need to consider for AI brand search are the embedding relevance score and Chunk Retrieval Frequency (CRF).
Vivek Rana, managing partner, Gnothi Seauton, explains, "The embedding relevance score shows how close your content is to the core ideas AI associates with an issue. For instance, an article may perform better if it connects naturally to themes like “clean energy transition”, “India policy reform”, or “sustainability governance”, even if it never uses those exact phrases."
Next, AI does not process full pages; it analyses chunks of text. Chunk Retrieval Frequency (CRF) tracks how often these chunks are recalled when AI agents generate responses. If a paragraph from your CEO’s op-ed consistently appears in AI answers around “AI in manufacturing”, that indicates strong retrieval salience.
Together, embedding relevance and CRF define AI discoverability, which is a new measure of how often and how accurately your brand’s thinking shapes AI-generated summaries. We have effectively moved from page rank to concept rank, and that shift is redefining what authority looks like in digital PR."
What is the trust velocity factor for AI search
Upasna Dash, founder & CEO, Jajabor Brand Consultancy, admits that the shift from traditional search to AI-powered platforms has been much faster than anticipated.
She says, "AI has certainly helped raise awareness; it allows brands to reach wider audiences, faster. But what it doesn’t automatically solve is credibility. As AI-generated content becomes more ubiquitous, audiences are questioning what’s authentic.
In this new landscape, brand authority should be measured not just through visibility, but through what I call trust velocity, how quickly and consistently audiences are choosing to believe you."
Is the future of PR measurement about numbers or meaning
Jagriti Motwani, co-founder, Cha-Chi Communications, "The real measure of authority now lies in how accurately and frequently that narrative appears incredible contexts, from AI summaries to conversational search.
As AI agents begin to summarise and reframe information, PR leaders need to understand the sentiment and accuracy behind those summaries. While AI continues to influence how audiences encounter brands, our goal is to read between the lines, to assess tone, emotion, and relevance across platforms.
The future of measurement will be less about numbers and more about meaning, and that’s where quality engagement truly lies."
Upasna Dash shares a recap of practical ways PR leaders can use AI tools:
- Detect misinformation and ensure narrative accuracy.
- Track how AI platforms are summarising or referencing the brand.
- Map sentiment trends from AI-generated summaries to gauge tone and trust.
However, Upasna asserts that, "Every PR effort must tie back to a tangible business goal. That is the real measure of success, not just within algorithms."
Pair vector analytics with advanced reputation intelligence
Vivek Rana, Gnothi Seauton, advises that PR leaders need to pair vector analytics with advanced reputation intelligence, "The goal is to understand not just how often content appears, but how it is interpreted and reused by AI systems. That means tracking when AI models cite or paraphrase your material, monitoring sentiment shifts within AI-generated summaries, and benchmarking the consistency of your core narrative over time."
He adds, "The next generation of tools will merge AI observability with real-time media intelligence. This will allow communicators to measure representation quality alongside reach. The teams that learn to optimise for meaning, context, and narrative accuracy rather than pure volume will lead the next phase of digital communications."
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