Author
Rich Mehta
In our work with law school clients we’ve recently been looking into how website users are using AI to find content.
It’s clear that students are already using AI in their coursework, with 92% using AI in some form or another according to research from Higher Education Policy Institute (HEPI) – but what about before they enrol?
Although data around GEO (Generative Engine Optimisation – the practice of optimising for visibility in AI responses) is in its infancy, tools do exist that allow us to review real world AI queries (like SEMRush and Scrunch) and see which websites are cited.
Students aren’t researching the same way
The traditional “search journey” for a prospective student typically involved comparison sites, reviewing prospectus materials, and institutional websites. AI can compress this into a conversational experience, which may shape an individual’s preferences prior to reviewing anything else. If AI suggests that an institution is better suited to a specific need, it’s possible that other institutions, rightly or wrongly, stand to miss out.
During our own testing, we observed AI systems responding to prompts such as:
- What law schools provide the best all-around preparation for an uncertain and evolving legal job market?
- Which law schools are favoured by top impact litigation firms working on environmental and civil rights cases?
- Which law schools openly share data about debt, salary outcomes, and loan repayment support?
These are nuanced, highly contextual questions – the kind prospective students previously answered through extensive independent research.
AI, especially those based on older models (like those often used in free plans), can be prone to oversimplification, hallucinations, and omitting information. Institutions omitted early in an evaluation process may not be effectively considered.
AI is simplifying complex institutional reputations
AI systems can reduce complex institutional reputations into simplified narratives. A law school may become strongly associated with one area of expertise (such as public interest litigation or BigLaw placement) while equally strong programmes, research areas, or student experiences receive little visibility. Our research has found examples where law schools with strong reputations in particular legal specialisms weren’t strongly surfaced in related AI-generated recommendations.
It’s also possible that AI will cite other factors that might deter applicants. When looking at one particular law school, we found instances of AI emphasising negative aspects, such as a high cost of living.
AI sometimes gets it wrong
AI systems do not “understand” institutions in the same way humans do. Broadly speaking, they identify patterns across large volumes of content and use those patterns to generate responses.
That means visibility in AI-generated answers is often shaped by broader signals such as:
- Media coverage
- Third-party commentary
- Research visibility
- Online discussions (on sites such as Reddit)
- Blog articles
- Consistent institutional messaging
- The clarity of publicly available information
Strong reputational signals tend to become amplified. Equally, areas that are poorly articulated or inconsistently communicated may become less commonly cited.
This creates a particular challenge for law schools, where messaging is often fragmented across departments, research centres, admissions teams, and marketing channels. An institution may have world-class expertise in a specific area of law, but if that expertise is not clearly connected to the wider institutional narrative across various sources, AI systems may struggle to recognise it.
AI also creates new opportunities for differentiation
AI-driven discovery may create challenges for institutions with unclear positioning, but it also presents opportunities.
Historically, prospective students often relied heavily on broad rankings and “prestige” when researching law schools. AI tools potentially allow students to search in more nuanced and personalised ways, and for less prestigious (but better equipped) institutions to gain visibility in key niches.
What this means for law schools
Clear positioning and consistent messaging, both on and off-site, becomes increasingly important.
For one law school we researched, Google AI Mode leaned heavily on third‑party sources rather than the school’s own authored research (favouring instead blogs and Reddit guides). This limited their visibility, and their ability to affect the narrative on certain topics relating to the school.
Institutions may need to think carefully about:
- How they articulate areas of expertise
- Whether their differentiators are consistently represented across channels
- How accessible and understandable their content is
- What topics their prospective students are asking AI about
- Whether their digital presence genuinely answers the questions prospective students are asking
For law school marketing and leadership teams, this shift is significant. Traditional digital recruitment strategies around search engines, rankings, social media, and institutional comparison sites still matter, but AI introduces a new channel institutions can use to reach prospective students. This also means a new set of tools and new skills to monitor and optimise for meaningful AI queries.