Your campus deployed AI. {Can you prove it's working?}
Most institutions are implementing AI. Very few can show a trustee, an accreditor, or a faculty senate what it's actually changing. Alex Goryachev builds AI readiness assessments and impact measurement frameworks grounded in the largest AI readiness dataset ever produced for a public university system.
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What separates an AI readiness assessment from a dashboard.
Most institutions are implementing AI. Very few can prove what it's changing. Here is the difference between evidence your board can act on and a usage report.
Big-Firm Consulting
EdTech Vendor Dashboards
Alex Goryachev
Concrete outputs, not dashboards nobody trusts.
Every engagement produces evidence your board, your accreditor, and your faculty senate can act on. The format varies; the standard does not.
AI Readiness Assessment
A structured baseline of where your institution stands — infrastructure, governance, faculty capability, student access — benchmarked against data from the largest readiness study in public higher education.
Impact Measurement Framework
The metrics that survive faculty scrutiny: learning outcomes, competency attainment, adoption rates, equity gaps, and institutional ROI — defined with your institutional research office, not imposed on it.
Accreditation-Aligned Reporting
Pre/post deployment evaluation structured so the same evidence serves your board, your accreditor, and your budget process — answers instead of anecdotes.
How an engagement works.
The same evidence-first process Alex runs inside the largest AI deployment in U.S. public higher education. Engagements range from a one-time readiness baseline to recurring board-ready reporting.
Scoping conversation
A direct conversation about what your leadership needs evidence for — a board, an accreditor, a budget request. That determines what gets measured. No intake decks, no pre-work forms.
Baseline and benchmark
Readiness data collected across faculty, staff, and students, then benchmarked against system-scale data. Alex does this work — not a survey vendor reporting up to a partner.
Findings working session
A working session with your leadership team that turns findings into decisions — plus the measurement framework your institutional research office keeps long after the engagement.
The playbook came from building inside universities.
As Cisco's Managing Director of Innovation Strategy, Alex built global innovation centers and programs inside universities and research institutions across 14 countries — a $1.1B portfolio, innovation tracks for three Olympic Games, and partnerships from Imperial College London to Keio, NUS, University of Toronto, and UNSW Sydney. That operating history is what his assessments measure against.
Countries
University-anchored innovation centers built with partners including Imperial College London, Keio, École Polytechnique, and UNSW Sydney.
Portfolio managed
Innovation strategy at Cisco run with the same discipline these assessments bring to campus: governance, measurement, ROI.
Olympic Games
Three Olympic Games — innovation programs delivered live on the world stage, with immovable deadlines, global partners, and zero tolerance for failure. That's the operating standard behind every campus engagement.
In five years every institution will claim AI transformed it. Accreditors will ask {which ones can prove it}.
What would you measure first?
Accreditation evidence, board reporting, equity gaps, ROI — tell Alex what your leadership needs proof of.
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Frequently asked questions
What is an AI readiness assessment for a university?
A structured evaluation of whether your institution can adopt AI effectively — governance, infrastructure, faculty capability, student access, and culture. Alex Goryachev's assessments add the dimensions generic frameworks miss: shared governance, academic integrity, and equity — benchmarked against the largest AI readiness dataset in public higher education.
How do you measure the impact of AI in higher education?
Define outcomes before the rollout: learning outcomes, competency attainment, faculty adoption, time savings, equity gaps, and cost. The most common mistake is deploying first and hunting for metrics later. Alex builds the measurement framework with your institutional research office, so the evidence survives faculty scrutiny.
What is the ROI of AI for a university?
It depends where you deploy it: operations — enrollment, advising, administrative workflows — typically show measurable ROI before the classroom does. Alex Goryachev helps institutions build the ROI case trustees and CFOs will accept, grounded in data from a $17M, 22-campus deployment.
How should universities prepare for accreditation questions about AI?
With evidence, not policy statements: pre/post deployment evaluation, documented learning-outcome impacts, and equity monitoring, structured so the same evidence serves your board, your accreditor, and your budget process. That reporting framework is a standard output of Alex Goryachev's measurement engagements.
How much does an AI readiness assessment cost?
Assessments are scoped to institution size and depth — from a single-campus baseline to system-wide benchmarking — with an exact quote within one business day. Because Alex Goryachev sells no platform, the assessment's only agenda is accuracy.
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