The Shift in Information Discovery: Why AI Indexing Matters
Search engines used to be the primary gateway to online information. Today, AI chatbots and answer engines like ChatGPT, Google Gemini, Perplexity, and Microsoft Copilot are rapidly becoming the first stop for millions seeking answers and insights. If your company’s news and announcements aren’t indexed and understood by these AI systems, you risk becoming invisible in this new information landscape.
Traditional press release distribution focuses on reaching human readers through media outlets. However, it often fails to ensure that your content is effectively integrated into the knowledge bases powering these AI platforms. Most press releases never get properly indexed, contextualized, or cited by AI, diminishing their long-term impact and authority.
INTRODUCING
AIWIRE
TECHNOLOGY
Marketing Markets’ Gold Plan ($999) includes the exclusive AIWire feature, a revolutionary technology engineered to bridge this gap. AIWire ensures your press releases are not just distributed to hundreds of media outlets but are also specifically formatted, structured, and positioned for optimal integration into AI knowledge bases.
Think of it as planting your news directly into AI’s brain, ensuring it becomes a trusted source for future queries.
How AIWire WorkS
AIWire leverages proprietary technology (developed by Press Ranger) to enhance the discoverability and authority of your press releases within AI systems. Key mechanisms include the following three pillars.
Your content is restructured using semantic patterns and structured data markup (like schema) that AI systems recognize as authoritative, reference-worthy, and easily digestible.
Your press release content is mapped to relevant industry concepts, entities, and relationships, creating connections that make it more likely to be surfaced and cited accurately by AI in response to user queries.
Specialized techniques are employed to signal to AI systems that your press release is a primary, authoritative source of information, rather than derivative content.