Solutions
Assess every graduate against the same criteria, and improve those criteria every year
Applications spike, but you cannot add interviewers overnight. The AI Interviewer runs first interviews 24 hours a day, 365 days a year, many at once. You define the criteria yourself, so you can compare the scores with retention once people have started and improve the criteria for next year.
The problem
Assessing people with no work history, at volume, in a short window
In Japan, most graduates are hired as a single annual intake, so applications arrive in a narrow window and you cannot add interviewers overnight. Graduates have no employment record, so even when you write the criteria down and hand them out, interviewers still look at different things.
- Applications peak right after company information sessions, and the wait for a first interview grows longer
- Several interviewers are involved, so the same criteria still produce different scores
- Many application essays are now written with generative AI, so the writing no longer shows how the person thinks
- It is hard to review, with evidence, whether that year’s criteria were right
Building the criteria
Write criteria you can score from what candidates say
What do you look at instead of a work history? One option is to adopt the Japanese Ministry of Economy, Trade and Industry’s Fundamental Competencies for Working Persons directly. Proposed by the ministry in 2006, the framework sets out three competencies and twelve elements, which it describes as the basic abilities needed to work with many different people in the workplace and the local community.
Write each element as five levels in BARS (behaviourally anchored rating scales) format and you can score interview answers directly. Here is one element from each of the three competencies.
Taking initiative
Initiative
Found a problem nobody had raised, brought others along, and got it started
Volunteered for work outside their remit and carried it to the end
Went beyond what was asked within their own remit
Did what was assigned, as it was assigned
Can name an activity, but not what they themselves did
Thinking it through
Problem identification
Questioned the premise of the question and redefined the problem worth solving
Separated several causes and judged which one mattered
Restated the problem concretely and named candidate causes
Can restate the problem, but the causes stay undifferentiated
Describes what happened without framing it as a problem
Working in a team
Listening
Checked what the other person had left unsaid and resolved the mismatch before moving on
Restated the other person’s intent in their own words and confirmed it before answering
Heard the other person out and answered on that basis
Listens, but the answer drifts back to what they had prepared
States what they wanted to say, with little connection to what was said
Sources
Element names — Ministry of Economy, Trade and Industry, “Fundamental Competencies for Working Persons” (proposed 2006; three competencies, twelve elements)
Scale format — Behaviourally Anchored Rating Scales (BARS). Smith, P. C., & Kendall, L. M. (1963) “Retranslation of expectations: An approach to the construction of unambiguous anchors for rating scales,” Journal of Applied Psychology. A rating scale whose levels are fixed by descriptions of behaviour.
The L1–L5 wording — written by us, following that format. It is not officially defined.
Whether or not you use a framework, AI interview services differ in whether you can rewrite these five levels in your own words. You can keep the public framework unchanged, or replace it with your own competency definitions and behavioural models. Where criteria are free text, the definitions you already use in performance reviews go straight in.
What to settle
What to decide before your next new-graduate intake
01
Who decides the criteria
Use the vendor’s standard framework, or write definitions like the ones above yourself. This decides which type of service fits.
02
The same yardstick as your interviewers
If you can write L1–L5 yourself, the AI and your interviewers judge on the same basis, and the second interview picks up the scores along with the quotes behind them.
03
Whether it extends beyond the offer
With new graduates, what matters is retention. Compare the scores on each criterion with who is still there a year later and you learn whether that year’s criteria were right.
Running it
The annual cycle
A new-graduate intake is not a one-off job. One cycle runs from the end of selection, through a review of that year, to the changes you make for the next.
01
Information session and application
Put a QR code in the session materials and the session itself becomes the entry point. You can also have the AI explain the business and training before the interview. No scheduling needed, so students reach the interview while their interest is still high.
02
First interview
Everyone is assessed against the same criteria. Each score is kept with the remark it is based on and the recording, so you can trace why it was given.
03
Handover to the second interview
Points worth probing are passed on. The interviewer changes; the yardstick does not, and the conversation picks up where it left off.
04
Department assignment
Apply the same criteria to current employees and you see, from real data, which criteria your strong performers score highly on. Compare that with an offer holder’s scores and you have input for deciding which department they join.
05
Next year’s criteria
Compare the selection scores with who stayed, judge which criteria made the difference, and revise them. The change is yours to make; there is no vendor model update to wait for.
Into next year’s selection
An example: one year of new-graduate hiring in five stages. Where the boundaries fall depends on your own selection process.
Stages 4 and 5 assume the criteria are yours. A vendor’s standard framework can run the first interview on its own, but if you want to plan placements against the same standard as your post-hire reviews and rewrite the criteria for next year, criteria you define yourself are the better fit.
Related pages
More detail, by topic
Related topics are covered on these pages. Start with whichever is closest to your question.
Run first interviews in parallel when applications concentrate, without adding interviewers.
When scores differ by interviewer: one set of criteria for everyone, with the reasons on record.
How far you can narrow the field before the interview, when the paperwork is not enough.
How to choose an AI interview tool →
What to put in your comparison table, and why who owns the criteria decides which service fits.
AI interview services compared →
The leading services, sorted by what they optimise for and compared on questions, criteria and verification, using public information.
Rewrite your criteria, then test them on past interviews →
Re-score past interviews against rewritten criteria. What the full transcript can test, and what it cannot.
Frequently asked questions
Can an AI assess a student with no work history?
How well it works depends on whether you have decided what to look at. Answers are scored against each criterion and the remark behind each score is kept, so a person can check why the score was given. The criteria themselves are yours to define, and what to look at in place of a work history is for you to decide, on your own or with us.
Will it show when the application essay was written with generative AI?
Not from the written application alone. The AI interview asks follow-up questions as the conversation goes, so what it assesses is not the written text but whether the person can answer on the spot. Gaps between a prepared answer and what the candidate actually thinks tend to show up as the AI follows up.
Do we have to use the Fundamental Competencies framework?
No. This page shows an example built on a public framework. If you have your own competency definitions or behavioural models, you can set those as the criteria instead. If the criteria use the same wording as your performance reviews, people are measured on the same yardstick at selection and after they join.
Can it run case interviews?
Yes. The case can be presented before the interview, on slides with a spoken explanation. The student goes through it, thinks it over, and starts the interview when ready. In the interview, the AI asks for their conclusion and the reasoning behind it, then follows up on the assumptions they made and how they estimated the numbers. You can set criteria such as how the problem is broken down, how numbers are handled, and how the conclusion is put across. We agree the cases and criteria with you when you start.
What size of intake does this suit?
Flex is the easiest way to start: you begin with a minimum of 100 interviews and can top up in blocks of 10. Around 100 interviews is also when results usually start to show. For steady use there is Starter (240 interviews a year), and for higher volumes Growth (500 a year). See pricing
Tell us about next year’s new-graduate intake
Based on your expected application volume and the criteria you use today, we will show you where to start. Free, about 30 minutes.