Wharton | Mr. Social Impact CPA
GMAT 740, GPA 3.5
Chicago Booth | Ms. RA For MBA
GMAT 710, GPA 3.80
Stanford GSB | Mr. Economics To Business
GRE 331, GPA 3.99
INSEAD | Mr. Tesla Manager
GMAT 720, GPA 3.7
Foster School of Business | Mr. Tesla Gigafactory
GMAT 720, GPA 3.0
Harvard | Mr. Financial Services
GMAT 750, GPA 3.8
Stanford GSB | Mr. African Entrepreneur
GRE 317, GPA 2.6
Stanford GSB | Mr. Tesla Intern
GMAT 720, GPA 3.9
Berkeley Haas | Mr. Looking To Learn
GMAT 760, GPA 3.0
Wharton | Mr. Infrastructure
GMAT 770, GPA 3.05
Chicago Booth | Mr. Asian Veteran
GRE 315, GPA 3.14
Stanford GSB | Ms. Artistic Engineer
GMAT 730, GPA 9.49/10
Cornell Johnson | Mr. Emporio Armani
GMAT 780, GPA 3.03
Harvard | Mr. Future Gates Foundation
GMAT 720, GPA 7.92
Harvard | Mr. Amazon Manager
GMAT 740, GPA 3.2
Harvard | Mr. MBB Consultant
GMAT 730, GPA 3.9
USC Marshall | Mr. Utilitarian Mobility
GMAT 740, GPA 2.67
McCombs School of Business | Ms. Second Chances
GRE 310, GPA 2.5
Duke Fuqua | Ms. Account Executive
GMAT 560, GPA 3.3
MIT Sloan | Mr. Data Mastermind
GMAT N/A; will be taking in May, GPA 3.6
London Business School | Mr. Aussie Analyst
GMAT 680, GPA 3.3
Darden | Mr. Sustainable Real Estate
GRE SAT 1950 (90th Percentile), GPA 3.7
Stanford GSB | Mr. Entrepreneurial Bassist
GMAT 740, GPA 3.61
Cornell Johnson | Mr. IT To IB
GMAT 660, GPA 3.60
Harvard | Ms. Lucky Charm
GMAT 690, GPA 3.2
Tuck | Ms. Green Biz
GRE 326, GPA 3.15
Harvard | Ms. URM
GRE 325, GPA 3.6

On the GMAT, Artificial Intelligence Wins

Artificial Intelligence:  The study and design of intelligent agents, in which an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success.

Talk to friends studying for the GMAT, or browse GMAT-related forums, and you’re bound to learn a bunch of if/then rules (many of which are helpful, some of which are counterproductive): “if a question asked uses the word ‘and’, you multiply; if it’s ‘or’, you add”; “if the verbs in a sentence are in different tenses, find the answer that puts them all in the same tense”; “if the word ‘being’ is in a sentence, eliminate it”; etc.

Watch a class go through a challenging problem and you’re bound to hear questions such as “I see that now, but how would I ever know to do that?” and “When a question uses (this word) can I always do that?”

And here’s the sum of most of those conversations: most GMAT students are trying to program themselves as test-takers.

Which is understandable – for most of your academic career you’ve been able – and encouraged – to do that.  See a quadratic equation?  Plug it into the quadratic formula.  What happened in 1492? Columbus sailed the ocean blue.  Need to write a persuasive essay?  Start with a thesis statement, then support paragraphs with examples for each…  You’ve been able to program yourself for academic success with if/then binary logic.  But if high school and even college were Web 2.0, business schools are looking for the future, and as we know from emerging technology the future is more than just binary programming. The future is Artificial Intelligence, which is a great metaphor for what you need in order to succeed on the GMAT.

Artificial Intelligence goes back to that definition – it’s not “if/then” binary statements, but rather an agent (you) that can take actions to maximize its chances of success.  It trains itself to recognize patterns and play probabilities, but to be able to reevaluate when one process looks unlikely to achieve its goal.  As a GMAT instructor, I’ve long felt that my role isn’t to “show you how to do this problem” but much more “to help show yourself how to do problems that you haven’t seen yet”.  Effective GMAT preparation, at least for those seeking the elite 700+ scores, is less about being programmed to solve known problems with known techniques, and much more about developing flexible techniques and mental agility.

Now, if this concept seems a bit vague, well, so is a lot of the GMAT.  And one form of GMAT AI involves taking abstract concepts and making them concrete with examples, so let’s do that.

Consider a few of the binary-program strategies that test-takers learn for Problem Solving questions:



Factors, Multiples, and Number Properties

Many a GMAT examinee loves to be able to say “this is an algebra problem” and then begin to do algebra.  Or to identify “this is a good problem on which to plug in the answer choices.”  But take a look at this 700-level problem, which appears courtesy of the GMATPrep software (spoiler alert: you might see this on a practice test someday):

A boat traveled upstream a distance of 90 miles at an average speed of (v – 3) miles per hour and then traveled the same distance downstream at an average speed of (v + 3) miles per hour.  If the trip upstream took a half-hour longer than the trip downstream, how many hours did it take for the boat to travel downstream?

(A)  2.5

(B)  2.4

(C)  2.3

(D) 2.2

(E)  2.1

Now, consider a few elements in play here – the algebra looks like it will set up ugly, so you may want to backsolve.  But the given variable is v and the question asks you to solve for a time, so a quick backsolve isn’t really in the cards.  You’ll have to do some algebra.