The ITF isn’t out yet. The prospectus is still in progress. The roadshow hasn’t even begun.
And still, opinions about your company are already taking shape. Not because journalists or investors are digging through your documents – but because they’re asking AI.
A potential investor might use ChatGPT to see how your business model stacks up against competitors. A journalist could check Perplexity for a quick sense of your positioning. Someone considering a job offer might turn to Claude to get a feel for your culture. Even potential clients are increasingly relying on AI summaries instead of reading source material.
The catch: those summaries aren’t based on what you want to say. They’re based on what’s out there. That might include an old press release, a half-updated Wikipedia page, or commentary framed by competitors. In some cases, it’s content you didn’t even know existed.
This shift isn’t theoretical anymore. AI-driven discovery is growing fast, and for many users it’s already replacing traditional search. That means your company’s “first impression” is often generated elsewhere – and potentially not based on your input.
Unlike search engines, which mainly rank links, AI tools stitch together narratives. They interpret, compare, and fill in gaps. The result can be a version of your company story that feels coherent – but isn’t necessarily accurate or aligned with your equity story. For companies preparing to go public, that creates a blind spot. If key information is missing, outdated, or inconsistent across sources, AI will still produce an answer. And that answer may not be correct and shape perception long before your official materials are even read anyway.
So, what can you do?
Try to see your company the way others already do – through AI. Ask the questions your stakeholders are likely to ask. Not just the positive ones, but also the uncomfortable ones: past controversies, competitive weaknesses, cultural concerns. The goal isn’t to “game” the answers, but to understand what’s currently being picked up – and where the gaps are.
Be deliberate about how and where your narrative appears. Your positioning, strategy, or business model shouldn’t be buried deep in documents. AI systems tend to prioritize clearly structured, early information. Consistency matters too, especially across languages and markets. And you need to understand which sources these systems rely on.
Don’t assume all AI tools behave the same. They don’t. Results can vary depending on geography, data sources, and the model itself. What shows up in Germany might look different in the UK. And even within the same tool, outputs can shift from one day to the next – the same prompt can produce materially different results depending on when you run it. Testing across tools and markets can reveal inconsistencies before others notice them.
One thing is already clear: your company’s perception is being shaped within these systems – well before your IPO process formally begins. The question is whether you’re actively shaping what those systems find – or whether you’ll only see the result once it’s already influencing perception.
