How AI Groups Law Firms Into Competitor Sets
Too busy to read the full article? Here are the key takeaways at a glance.
TLDR
- AI does not compare law firms the way partners do.
- It groups firms into competitor sets based on shared signals, not reputation.
- Category clarity determines who you are compared against.
- Weak or generic signals pull firms into the wrong competitive pool.
- Being grouped incorrectly is one of the fastest ways to lose visibility.
Key Takeaways
- AI decides who your competitors are before it decides whether to recommend you.
- Competitor sets are formed by patterns, not prestige.
- Firms are often grouped with competitors they would never choose themselves.
- Once grouped incorrectly, firms struggle to break out without structural changes.
- Visibility loss often starts with being compared to the wrong firms.
“Why do our competitors keep appearing where we don’t?”
This is one of the most common frustrations law firms raise when they start paying attention to AI search.
The assumption is usually that those firms are better known, better optimised, or somehow favoured.
In reality, it is happening because AI has already decided who your competitors are and that decision shapes everything that follows.
“Doesn’t AI just compare firms offering the same services?”
Not quite.
AI doesn’t build competitor sets based on service lists or how firms describe themselves. It builds them by looking for patterns across category, entity, trust and discoverability signals, then grouping firms that behave similarly in the data it sees.
From AI’s perspective, competitors are firms that look alike structurally, not firms that believe they compete.
That distinction matters more than most businesses realise.
“What actually triggers competitor grouping?”
Competitor sets form once AI feels confident enough to compare.
At that point, it looks for firms that share similar characteristics, such as:
- how clearly they define their legal category
- how narrowly or broadly they position their services
- how consistent their entity signals are
- how strong and reliable their trust signals appear
- how often they surface across the same external platforms
These patterns matter more than size, history or reputation and if your signals resemble those of generalist firms, AI groups you with generalists. If your signals align with specialists, you are compared against specialists. The grouping happens long before recommendation logic kicks in.
“Why do we get grouped with firms we don’t see as competitors?”
Because AI doesn’t care who you intend to compete with.
It cares who you resemble in the data. This is where vague positioning causes real damage. When a firm presents itself too broadly, AI has no choice but to place it into a wider, more crowded competitor set. Once there, the firm is compared against others with stronger signals, clearer categories or better external reinforcement.
From the firm’s perspective, this feels unfair. From AI’s perspective, it’s logical.
“Can strong reputation override weak competitor grouping?”
No. And this often surprises people.
AI cannot see informal reputation, market perception or word-of-mouth credibility. It can only work with what it can verify and cross-check.
If a highly respected firm sends mixed or generic signals, AI still groups it alongside firms that look similar structurally. Reputation only helps if it is reflected consistently in the signals AI can see.
This is why smaller, clearer firms often appear more frequently in AI recommendations than larger, better-known ones.
“What happens once AI has placed you in a competitor set?”
Once the grouping is established, AI uses it as a reference frame.
When users ask for recommendations, AI doesn’t search the entire market. It typically selects from within the competitor sets it has already formed. Firms outside that set are rarely considered, even if they would be a good fit in reality.
This is why visibility loss often feels sudden. The firm hasn’t disappeared from search entirely. It has simply been excluded from the comparison pool AI is drawing from.
“Why is it so hard to escape the wrong competitor set?”
Because AI looks for reinforcement.
If the same patterns keep appearing, the grouping hardens over time. Updating a single page or profile rarely shifts the picture enough to trigger reclassification. AI needs to see sustained, consistent changes across category, entity and trust signals before it revises its assumptions.
Until that happens, the firm remains stuck competing in the wrong space.
“So how should firms think about competition in AI search?”
Differently is the broad answer!
The goal isn’t to outrank competitors in a list. It’s to be grouped with the right ones in the first place. Once that happens, recommendation becomes much more likely.
This requires deliberate clarity, not aggressive optimisation. Firms that are precise about who they are, what they do and who they serve give AI fewer opportunities to misclassify them.
Competition in AI search starts with classification, not comparison.
An example AI search that exposes competitor grouping
Imagine a user types the following into an AI search tool:
“Which law firms in Manchester are known for complex shareholder disputes?”
From a human perspective, this feels open-ended. You might expect AI to scan the entire Manchester legal market and surface firms with strong experience in shareholder disputes, but that isn’t what happens.
Before generating an answer, AI has already narrowed the field. It selects from the competitor sets it believes are relevant to:
- shareholder disputes
- commercial litigation
- the Manchester market
If your firm has been grouped with general commercial firms, or broadly defined “full service” practices, it may never enter the comparison pool at all, even if it has deep experience in shareholder disputes.
Meanwhile, a smaller firm with clearer category and entity signals around shareholder work may be repeatedly referenced, simply because it sits inside the right competitor set.
The omission isn’t deliberate. It’s structural.
Why this matters
From the firm’s point of view, it feels like invisibility. From AI’s point of view, the firm wasn’t excluded, it just wasn’t considered and this is why firms often say:
“We should be showing up for that.” And AI replies, “No, you shouldn't, you’re not competing in that category!”
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