Could AI Get Students Into College? Considerations For Building AI Educational Consultants
By Joash Lee, Forbes Councils Member.
As Published on Forbes: Feb 12, 2026, 07:00am EST
Joash Lee is the Founder and CEO of Sedifly, a global EdTech firm democratizing access to education.
Over the past decade, a wave of educational consulting firms have sprung up aiming to help students navigate one of the most consequential decisions of their lives: getting into college. Educational consultants typically advise students on their school selection, academics and extracurricular activities.
As an increasing number of applicants vie for the same slots at colleges, getting accepted to some schools has gotten harder. Coupled with this, many colleges now place a greater emphasis on holistic evaluation than pure academics, contributing to growing demand for educational consultants. However, access has largely been a luxury reserved for wealthier families. I've noticed rates at many traditional consultancies starting in the mid-five-figures for a year-long package, and climbing into the millions for multi-year-long preparation packages.
Today, solutions aimed at the “sandwich class”—students who aren’t served by nonprofits but can’t afford traditional consultants—are changing that. These upstarts represent a classic case of disruptive innovation: While each student pays less than they would at a traditional consulting firm, the size of this middle segment creates a larger total addressable market over time.
The Barriers For AI In Educational Consulting
Yet despite advances in AI, we haven’t seen a winning AI educational consultant yet. Why, exactly, is that so?
1. Unsustainable Unit Economics
It's tough to grow the topline substantially when operating in a high churn industry with low average revenue per user (ARPU), and consequently, low lifetime value (LTV). This is because once students get into college, they never need to use the tool again, and charging anything more than $10 to $20 a month under a software-as-a-service (SaaS) model, or more accurately, AI-as-a-service model, seems like a rip off.
AI is a commodity as a result of the significant amount of VC funding poured into the space, and consumers aren’t willing to pay premiums for such tools with the plethora of AI models available at low-to-no cost. So SaaS models in this sector hardly, if ever, work, unlike for services that lock users in sticky ecosystems.
2. Small Total Addressable Market
The total addressable market (TAM) for AI educational consultants is currently small as a result of the low ARPU and LTV. Though the number of students applying to colleges annually is large and the broader educational consulting market is growing fast, I've noticed most revenue is generated at the top. This makes it tough to build a venture-backable AI educational consultant.
3. Challenges In Scaling
Many startups have adopted a consumer-facing go-to-market strategy using social media platforms, but this funnel is hard to nail, and building a winner could require unrealistic levels of adoption given the unit economics. Compounded with the inevitable hurdles that come along with an AI educational consultant, such as students dropping out post-application or admission, upstarts building in the space have struggled to find true product-market fit.
But is there a way out?
Key Questions For Entrepreneurs
Some key questions emerge when entrepreneurs think about building an AI educational consultant:
1. Would consumers be willing to pay a premium for an AI educational consultant that can do the job better than a general tool, like ChatGPT? In other words, could you increase ARPU over the long run?
2. Could you scale beyond the essay-tool-and-cheap-subscription model? In other words, increase LTV and grow the TAM by integrating more deeply into a student’s lifecycle (from school-fit to application, decisions, enrollment and post-enrollment retention), rather than a single-point service?
3. What would be required to successfully bring the solution to market? In other words, what’s the winning distribution strategy?
Breaking The Value And Awareness Barriers
Having had a full circle journey with educational consultancies—from being a student to now founding an educational consulting firm—here are my answers to these questions:
1. Increasing ARPU
My thesis is that the cost of generic AI models will exponentially decrease, ultimately to zero over the coming years or even months. However, over the next two to three years, I think tools serving niche markets, such as an AI educational consultant, will come at premiums, and consumers will be willing to foot the bill.
This is not unlike how Google is free today, and generic data is available at no-cost on Google, but firms still pay top dollar for market intelligence tools or data providers like Bloomberg Terminal, Crunchbase and Statista. In fact, we’ve already seen this happening, with tools like Rogo.ai serving investment banks. What differentiates the next generation of application-layer tools from an off-the-shelf AI wrapper could be the upstart’s ability to build advantages around data, distribution and user interfaces.
2. Scaling Beyond A Single-Point Service
Beyond an AI educational consulting tool that helps students get into their dream school through essay insights, extracurricular recommendations, sample profiles and acceptance rate calculators, significant value could be accrued through the addition of supporting services that extend past “termination day.”
For instance, an AI tool helping students navigate college life, clubs and careers might prove useful and be something consumers would be willing to pay for, past merely getting into college.
3. Building Awareness
A B2C approach works fine and well for traditional consultants, given the high margins and fees they charge, resulting in relatively fewer students they serve to make the business case. I've noticed the Pareto principle applies to the revenues of many educational consultancies: around 20% of clients make up about 80% of a firm’s revenue.
However, AI educational consultants must explore other means of penetration, such as B2B or B2B2C, to attain critical mass quicker as a sole B2C approach likely won’t work given the unit economics.
Reframing The Question
Ultimately, the question as to whether one can build a winning AI educational consultant can be reframed to a question as to whether founders can rethink value, scope and distribution from first principles. I think the failures we see today stem from business models that underestimate how hard it is to escape low ARPU, short lifecycles and consumer-only funnels.
Though I don’t believe the opportune moment to build an AI educational consultant is here yet, it probably won’t be long before the “sandwich class” finally has a seat at the table. So yes, AI could one day get students into college.
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