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| Patti Trainor-Wrazej |
AI engines are the new intermediaries between brands and consumers. Yet most brands who monitor their coverage and pay for brand reputation management have no idea what LLMs are saying about them.
The real challenges of managing a company’s presence and reputation in the AI era is that unlike Search Engine Marketing, one can’t easily inspect what data is influencing the results of queries about one’s company across the thousands of Large Language Models (LLMs) currently active.
By 2028, AI will be generating 94% of content. How will you support marketers who are paying you to manage their reputation and ensure the integrity of their brand’s content and presence on the LLMs?
Even if one could influence their brand’s results in ChatGPT, there are still thirty-odd other LLMs, and that number will increase before the inevitable industry consolidation.
With the lion’s share of the internet’s content being generated by AI, it creates an ever-evolving digital ecosystem. And the information that is being generated today will be used to train tomorrow’s AI engines.
As we know, AI engines, with their inherent biases and occasional ‘hallucinations’, often distort brand messaging, leading to misinformation.
As marketers try and get their hands around this emerging technology, there's a significant gap in monitoring and influencing the AI-generated (LLM) narrative around brands.
There are no quick solutions with LLMs
If you think that you can hack your way to a better brand reputation in LLMs, then there's a bridge I can sell you. With LLMs, you need to do the work by running thousands of prompts per month, addressing every potential topic and angle that can impact your brand’s reputation and presence. And you’ll need to do this monthly for all the leading LLMs to ensure that you’re achieving optimal reach.
And this is only the beginning. Marketers need to conduct continuous AI content analysis because new sources of content are being created by AI, with challenges that are different from human-generated content.
Marketers will also need to conduct sentiment analysis to identify biases in the content, searching for potential risks and opportunities.
Finally, to fix the identified problems, marketers will need a technology solution that will be a remediation solution in order to fix the identified problems.
And this also must be done on a continuous basis as the content is updated and user queries change.
LLM usage is growing
After a relatively flat growth curve through the first few months of 2025, since May, the growth curve for ChatGPT has turned upwards, according to data compiled by First Page Sage. It increased from 603 million monthly users in May to 812 million monthly users in August 2025 (after increasing from 481 million monthly users in January 2025 to 541 million in April 2025) ChatGPT’s share of LLM usage remains flat in 2025, and indicates a growth for LLM usage across the board.
OpenAI CEO Sam Altman recently announced that ChatGPT-6 will arrive faster than the gap between ChatGPT-4 and ChatGPT-5, and that it won’t just respond to users but will adapt to them. These changes are bound to impact the LLM brand reputation solutions.
The PR industry must advocate for the development of proactive brand protection solutions for the AI era that enable the safeguarding of brand reputation and sentiment across the 20+ most-used LLMs.
PR agencies are going to need to find the technology partners that will help them support their clients. And they’ll need an internal team with the technical know-how to value the technology that is being pitched to them today and in the future.
LLMs are generating new and more challenging issues for marketers responsible for managing brand reputation and sentiment. Given the aforementioned growth in LLM adoption, we as an industry need to start addressing the risks of this emerging AI technology today.
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Patti Trainor-Wrazej is COO of InfluenceAI.ai.
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