How reputations form before the click

Last night’s Midtown Business Club event at SEC Newgate centred on a simple but increasingly relevant idea: our online footprint is no longer just something people browse; it is something systems summarise. 

As generative AI platforms become a more common starting point for research, whether that’s via the platform chat features or AI overviews in search, they are forming first impressions on our behalf. And this is not by creating new information, but by stitching together whatever already exists. 

A recent piece from Search Engine Land (Semrush) has described this shift as a new reputational risk, noting that AI search tools now compress multiple sources into a single narrative, often flattening nuance and surfacing confident‑sounding summaries before a user ever clicks through to original material.  

To explore what that looks like in practice, we invited several of yesterday’s event attendees to test their own digital footprint. What emerged wasn’t one single result, but a recurring pattern. 

What happens when the data is clear, thin, or fragmented 

In some cases, AI tools produced coherent and broadly accurate summaries. Where individuals had a clear corporate profile, consistent mentions across credible sources and up‑to‑date professional information, the outputs made sense. AI platforms were simply clustering and compressing strong, consistent information. 

Elsewhere, information existed but was outdated or fragmented. In these instances, generative tools attempted to join the dots themselves – extending previous roles, inferring expertise or making assumptions to create a complete narrative. The outputs were polished and plausible, but certainly not all correct. 

Both scenarios pointed to the same underlying behaviour. AI systems do not slow down when information is incomplete; they summarise what’s out there and fill the gaps. 

From search results to summaries 

This reflects a wider change in how reputation now forms online. Traditionally, search results offered a set of links and left interpretation to the reader. Increasingly, AI performs that interpretation upfront. 

As a result, the summary itself becomes the experience. In many cases, it is the only thing seen. 

That shift is now being widely recognised in reputation and brand research. Writing earlier this year, the Forbes Communications Council noted that audiences are increasingly evaluating organisations and leaders through AI‑curated summaries and trust signals, rather than through individual web pages or paid visibility alone.  

The implication is not that AI decides what is true, but that it decides what is most legible based on the material available. 

Why gaps matter more than they used to 

One point that came up repeatedly during our event is worth reinforcing. In this environment, silence is not neutral. 

Where information is missing, AI fills space with adjacent information – company descriptions, historical content, third‑party commentary or patterns learned elsewhere. Where information is present but outdated, it’s still presented because it is still visible. 

This doesn’t introduce entirely new reputational challenges; it accelerates existing ones. The same issues that have always undermined professional reputation (lack of clarity, inconsistency, neglect) now surface more immediately. 

A useful test 

One question raised at the end of the session offers a helpful way to frame all of this. 

If someone formed an early view of you or your organisation through an AI summary alone, would it broadly reflect reality? 

This question is about understanding how reputation is now translated by embedded AI platforms, even when we’re not present in the conversation. 

And increasingly, that’s where first impressions are formed.