Authority strategy for research and expertise-driven institutions.
Your institution is being described by machines that have never been told who you are.
Ask ChatGPT, Perplexity, or Google’s AI who leads in your field. You’ll get an answer: a name, a summary, a judgment. It was assembled from whatever the systems could piece together: a stale faculty page, a conference bio, a competitor’s better-structured site.
Most institutions have never checked what that answer says. Fewer still have shaped it. Meanwhile, the people who matter most: funders, prospective faculty, partners, journalists, and students are increasingly asking the machine first.
Authority strategy fixes that at the root. Not by chasing keywords, but by making your institution legible, credible, and unmistakable to the systems doing the describing.
Three Ways In
Each tier stands on its own. Most engagements start with the Audit.
1. Authority Audit: The diagnosis. Start here.
A structured assessment of how search engines and AI systems currently understand your institution, and where the gaps between what you are and what they think you are will cost you.
What you get:
- AI visibility baseline: what ChatGPT, Claude, Perplexity, and Google’s AI Overviews actually say about your institution today, captured verbatim and scored, across identity and discovery queries
- Entity analysis: whether the machines hold a coherent, accurate picture of you at all, and what they’re confusing you with
- Structured-data and footprint audit: what your site currently tells machines, and what it fails to say
- Competitive authority map: who currently owns the answers in your field, and where the openings are
- A prioritized roadmap: the specific work that would close the gaps, sequenced by leverage
Who it’s for: Any institution that has never checked what AI systems say about it, which is nearly all of them.
Outcome: You stop guessing. You know exactly what the machines believe about you, and what it’s costing you.
Investment: From $4,000
2. Authority Build: The implementation.
Establishing the foundation that makes your institution legible and credible to both human audiences and AI systems. This is the work the Audit prescribes.
What you get:
- Authority definition: what, precisely, your institution should be known for, scoped tightly enough to be defensible and owned
- Entity architecture: the structured data and knowledge-graph work that lets AI systems understand and represent your institution accurately instead of guessing
- Corroboration layer: the citations, associations, and cross-references that turn your claim into a recognized fact
- Topical foundation: the content architecture that demonstrates depth in the field you’re claiming
- Faculty and researcher visibility: making your people’s expertise machine-legible, not buried in a PDF
Who it’s for: Institutions ready to build the position, not just measure it.
Outcome: When someone asks an AI who leads in your field, your institution is in the answer, accurately and on your terms.
Investment: From $10,000
3. Authority Engine: The Ongoing Work
Authority isn’t a project you finish. The systems keep re-reading you, your field keeps moving, and competitors keep building. The Engine keeps the position growing and proves it’s working.
What you get:
- Continuous AI visibility monitoring: how ChatGPT, Perplexity, Google AI Overviews, and Gemini describe you over time, tracked and reported
- Authority reporting: a dashboard showing recognition, citation, and visibility trends, not vanity metrics
- Ongoing entity and content development: extending topical depth and corroboration month over month
- Strategic guidance: a standing thinking partner as your field and the systems change
Who it’s for: Institutions treating authority as an asset to compound, not a one-time fix.
Outcome: Authority becomes something you can see, measure, grow and defend in front of a dean or a board.
Investment: From $4,000/month
Built for institutions that live on their credibility.
- Research centers and institutes where recognition shapes grant competitiveness and partnership
- Academic departments where being the place for a discipline drives faculty, students, and funding
- Professional and graduate schools where reputation in a field is the product
- Continuing and executive education programs where the right learners find you by asking who leads
If being recognized as the authority in your field shapes what you win, this was built for you.
What working together actually looks like.
- A conversation. We talk about what your institution should be known for and what it’s currently known for. Those are rarely the same.
- The Audit. Two to three weeks. You get the diagnosis, the baseline, and the roadmap — yours to keep, whether or not we go further.
- The Build. If it makes sense, we implement. Timeline depends on scope.
- The Engine. Optional and ongoing, for institutions that want the position to compound.
You work with me directly. There’s no account layer between you and the person doing the thinking.
Common Questions
What is authority strategy?
Authority strategy is the discipline of making an institution recognized as the definitive expert in its field, to human audiences and to the AI systems that increasingly answer questions on their behalf. It combines entity architecture, structured data, corroboration, and topical depth to shape what search engines and AI models understand and say about an organization.
How is this different from SEO?
Traditional SEO optimizes for ranking on a page of links. Authority strategy optimizes for being the answer: the name an AI system returns when someone asks who leads in a field. SEO asks how to be found. Authority strategy asks how to be recognized. The technical craft overlaps; the goal and the measurement do not.
Can you guarantee we’ll appear in ChatGPT?
No, and be skeptical of anyone who does. AI systems are probabilistic and change constantly. What can be done is measurable: establish a coherent entity, build corroboration, track how systems describe you over time, and improve it. The Audit gives you a baseline so improvement is provable rather than asserted.
How long does this take to work?
AI systems and knowledge graphs re-crawl and re-associate on their own schedule. Meaningful change typically appears over weeks to months, not days. The Audit establishes the baseline that makes movement visible when it comes.
Do you work with the whole university or individual units?
Most often, individual units: a research center, a department, a professional school, where authority in a specific field is the goal and decisions move faster. Institution-wide work is possible but rarely the best starting point.
What is generative engine optimization (GEO)?
Generative engine optimization is the practice of improving how a brand or institution appears in AI-generated answers from systems like ChatGPT, Perplexity, and Google’s AI Overviews. It’s one component of authority strategy: the tactical layer beneath the strategic question of what you should be known for in the first place.
How do AI systems decide who’s an authority in a field?
They synthesize from what they can find and verify: structured data, consistent corroboration across sources, topical depth, and citation. An institution that is coherently defined and consistently corroborated is far more likely to be named than one whose signals are scattered, contradictory, or absent, regardless of actual expertise. Being genuinely excellent is not the same as being legible.
Find out what AI says about you
Every engagement starts the same way: with the truth about how your institution is currently understood by AI. The Authority Audit gives you that in two to three weeks.