Graduate students no longer browse law school websites. They ask AI questions about skills, career paths, and value, such as:

“Which legal master’s program prepares me for compliance roles?” Or “What degree helps me move into policy or regulatory work?”

AI answers, and students build their consideration set from there. For William & Mary Law School’s online Master of Legal Studies program, that shift created a visibility problem. High-intent students were searching for programs that delivered the skills and outcomes W&M Law specializes in, but the online program wasn’t appearing in the AI-generated answers guiding those decisions.

Everspring partnered with W&M Law to rebuild its digital presence for AI discovery—structuring content so AI could clearly understand the program’s value, mapping answers to the questions students ask when evaluating skills and career paths, and aligning messaging to students who arrive already informed by AI.

The result: Within one year, legal master’s enrollment doubled. W&M Law went from nearly invisible in AI-generated responses to consistently cited as a top-recommended program, proving that when institutions adapt to how students actually discover programs, growth follows.

Why it worked: Most programs optimize for Google rankings. by showing up in the AI answers students trust most, then converting the high-intent visitors who followed.

Three moves drove W&M Law’s outcomes:

W&M Law’s web pages weren’t structured for an environment where students ask ChatGPT which programs match their career goals. Everspring rebuilt the program site for machine readability and developed a content strategy with faculty-informed answers mapped to every student query from awareness through decision.

Impact: Visibility in AI answers climbed from 3% to nearly 20% in six months.. W&M Law went from absent to consistently featured in Google’s AI Overviews for high-intent queries.

Everspring replaced aspirational copy with direct, student-centric answers—reflecting how prospects now arrive informed and ready to evaluate programs. One example: changing a lead form headline from “Unlock Legal Brilliance” to “Degree Questions, Answered.” As Amy King put it: “They’re coming with more knowledge. They’re not looking for basic information. They already have that.”

Impact: Lead volume up 44%. Conversion rate improved from 5.82% to 8.04%.

Applicants with zero prior admissions contact rose from 16% to 65%, reflecting an emerging trend: students arriving more informed after researching programs through AI. By the time they reached W&M Law, many already understood the program and were ready to apply.

Impact: Lead quality remained strong. Higher-intent students are converting faster, on shorter timelines.

W&M Law’s growth came from structuring its program content, infrastructure, and messaging around how students search with AI today:

• AI-optimized content architecture built for machine readability and citation
• Full question-chain content strategy mapped to student decision stages
• Technical backend improvements (structured data, metadata, semantic HTML) that help AI understand and surface programs accurately
• Conversion messaging aligned to the behavior of students arriving pre-informed from AI research
• Ongoing measurement of AI citation rate—not just traffic and rankings

AI search is no longer emerging. It’s established. W&M Law moved early and turned this shift into measurable enrollment growth.