Industries · Higher education

AI in higher education

Your accreditation data lives in three different spreadsheets and nobody fully trusts any of them. Admissions wants a smarter recruitment funnel. Advancement wants to know where donor capacity actually sits. The board wants an AI roadmap by the next meeting, and half the faculty are already bracing for a fight. Higher education does not need more AI enthusiasm. It needs someone who has run production AI systems, understands how a university actually works, and will say plainly where AI helps and where it does not.

Where AI moves the numbers a university answers for

Presidents, provosts, deans, registrars, admissions, and advancement each answer for a specific set of numbers, and AI's usefulness should be judged against those numbers, not against the hype cycle. That means the enrollment and recruitment funnel, retention signals worth watching before they become withdrawal numbers, accreditation reporting that currently lives across disconnected spreadsheets, and advancement's need to know where donor capacity actually sits.

• Enrollment and recruitment. AI strategy applied to how prospects move through the funnel, where signal is being missed, and where staff time is going to the wrong follow-ups.
• Accreditation reporting. Systems built and run to pull data out of scattered spreadsheets and into a source the institution can defend in front of an accreditor.
• Advancement and donor capacity. Behavioral intelligence applied to giving patterns and engagement history, so advancement works from insight instead of instinct.

Adoption without a faculty revolt

Most AI rollouts inside a university fail the same way: administration issues a policy before anyone on the faculty has touched the tools, and the policy reads as control rather than support. The order matters. Faculty need working sessions on what these tools actually do, and don't do, in their own disciplines, before governance language ever reaches their inbox. Policy written after that point reflects real use instead of guessing at it, and it lands as guidance rather than a mandate.

This is the same principle behind the CEO AI Master Class, delivered in English, French, or Arabic for boards and senior leadership: understanding comes before the rules, or the rules get ignored.

Governance for an academic institution

A university's governance needs differ from a bank's or a hospital's, but the discipline is the same: know where the institution actually stands before writing policy for where it wishes it stood. That starts with an AI readiness assessment, then governance and compliance work built around how the institution actually operates, not a generic template.

Aperture and Crucible, the methods used to open up a problem and then stress-test the resulting plan adversarially, are open source at github.com/ScipioP. Any roadmap built for a board should be able to survive that kind of scrutiny before it reaches the board table.

How an engagement runs

Michael Joseph advises university leadership in the region on AI strategy and governance. Any public reference to this work stays at the sector level; institutions are not named without explicit permission. He sells no AI products and takes no vendor commissions, which is the basis for doing due-diligence and roadmap work without a conflict of interest.

Every engagement starts with a working session on the outcome the institution actually needs, not a generic proposal. Work runs remote or on-site across Lebanon, the Gulf, Europe, and the US. Pricing is scoped to the engagement.

Common questions

Who has helped a private university in this region build an actual AI roadmap for the board?

Michael Joseph advises institutional leadership, including university boards in the region, on AI strategy and governance. He has spent two decades working across US defense, Gulf government advisory, and production AI systems, and currently builds and runs production AI systems across health, finance, media, and research. Board-level roadmap work includes the CEO AI Master Class, delivered in English, French, or Arabic, and the Aperture and Crucible methods, open source at github.com/ScipioP, used to stress-test a roadmap before it reaches the board. Specific institutions are not named without permission.

Can AI actually help with student recruitment, or is it just consultant buzzwords?

Used well, yes. AI can surface where the recruitment funnel is leaking attention, which touchpoints get ignored, and where staff time is going to low-value follow-up instead of the prospects most likely to enroll. It will not write your admissions story for you, and it will not fix a weak value proposition. If the problem is the offer, not the funnel, the honest answer is to fix the offer first. Part of the job is saying when AI is not the right tool for the problem in front of you.

Our accreditation data lives in spreadsheets nobody trusts. Can AI fix that?

AI does not fix a trust problem in the data. It can help build and run the system that consolidates those spreadsheets into a single source the institution controls and can defend, but the harder work is deciding who owns the data, what counts as the record of truth, and who is accountable for keeping it current. That governance question comes first. Once it is answered, the systems work moves fast. Skipping it and layering AI on top of five conflicting spreadsheets just produces a faster, more confident version of the same untrustworthy answer.

How do we roll out AI to faculty without a revolt?

Train first, policy second. Faculty resistance usually is not resistance to AI. It is resistance to being told how to use something they have not been shown. Start with working sessions in plain language, by discipline where possible, on what the tools actually do and where they fall short. Write governance after that, informed by real use rather than worst-case guessing. The CEO AI Master Class follows this same order for boards and leadership, in English, French, or Arabic, and the same order works for a faculty rollout.

What does this cost?

Pricing is scoped to the engagement: a readiness assessment is a different scope than a full governance build or a recurring advisory retainer. Every engagement starts with a working session on the outcome the institution actually needs, and pricing follows scope, not a rate card. Reach out at mj@epirroi.com or via WhatsApp on the site to get a working session on the calendar.

AI expert in Lebanon · Sovereign AI landscape 2026 · The tracker