Check-Ride.ai: Can Artificial Intelligence Become Your Virtual DPE for Checkride Preparation?

 For a student pilot, few moments are as important—and as intimidating—as the checkride.

After months of flying, studying regulations, learning aircraft systems, practising maneuvers and spending considerable money on flight training, the student eventually has to sit across from a Designated Pilot Examiner (DPE) and demonstrate that he or she is ready to exercise the privileges of a pilot certificate or rating.

The checkride is not simply a test of whether a pilot can remember facts. The examiner wants to know whether the candidate understands what they are doing, why they are doing it and how they would apply that knowledge in a real-world situation.

That is where Check-Ride.ai is attempting to bring artificial intelligence into flight training.

The platform describes itself as a voice-native AI DPE designed to simulate the oral portion of a checkride. It allows pilots to practise answering questions verbally, rather than simply reading questions and typing responses. It can evaluate answers against the FAA's Airman Certification Standards (ACS), identify weak areas and provide a post-session debrief.

For pilots preparing for a checkride, this represents an interesting development in the rapidly expanding world of AI-assisted aviation training.

What exactly is Check-Ride.ai?

At its core, Check-Ride.ai is an AI-powered mock oral examination platform.

The concept is relatively simple.

Instead of a pilot sitting alone with a textbook or question bank, the pilot interacts with an AI examiner. The examiner asks questions, the pilot responds by speaking, and the system evaluates the response.

But there is an important difference between this and simply asking ChatGPT or another AI system an aviation question.

If you ask a conventional AI assistant:

"What are the VFR weather minimums in Class D airspace?"

you will receive an answer.

But a real DPE might ask the question, listen to your answer, ask why the rule exists, introduce a scenario and then ask how your answer changes under different circumstances.

That conversational and probing element is what Check-Ride.ai is trying to reproduce.

The company describes its product as a way to rehearse the checkride rather than merely study for it.

The importance of practising the oral exam

One of the interesting aspects of pilot training is that knowing something and explaining it are two different skills.

A student might be able to recognise the correct answer while reading a multiple-choice question. But when an examiner asks the question verbally and expects the candidate to explain the reasoning, weaknesses can suddenly become obvious.

For example, a pilot may know that an aircraft requires certain equipment to operate legally. But can the pilot explain:

• Where the requirement comes from?
• What happens if the equipment is inoperative?
• What documents need to be checked?
• How would the situation change under different operating conditions?
• What would the pilot do if the aircraft became unairworthy before departure?

The oral examination tests this ability to think, explain and apply knowledge.

Check-Ride.ai therefore focuses on spoken interaction rather than just conventional question-and-answer study.

The pilot talks. The AI listens. The response is transcribed and evaluated, and the system can identify areas where the candidate's knowledge or explanation needs improvement.

It is designed around the FAA Airman Certification Standards

One of the most important features of the platform is its connection to the FAA Airman Certification Standards.

The ACS provides the framework u  sed to evaluate practical pilot certification and rating applicants. Rather than simply asking random aviation questions, Check-Ride.ai says its evaluation system tracks performance against specific ACS areas and tasks.

This is important because checkride preparation should ultimately be connected to what the candidate is actually expected to demonstrate.

The platform's demonstration shows individual ACS elements being evaluated as satisfactory, marginal or unsatisfactory, accompanied by an explanation of the assessment.

That creates a potentially useful feedback loop:

Question → spoken answer → evaluation → identify weakness → study → practise again.

This is considerably different from simply completing a 50-question practice test and looking at the percentage at the end.

A virtual examiner that can challenge your answers

Perhaps the most interesting part of the concept is the ability to simulate an examiner rather than simply function as a digital textbook.

A real oral examination is dynamic.

A DPE may begin with one subject and then move into another based on the candidate's response. If an answer is incomplete, the examiner may probe further.

For example:

DPE: "What are the requirements for operating this aircraft?"

Candidate: gives a basic answer.

DPE: "Okay. But what if the aircraft's required equipment is inoperative?"

Now the candidate has to think beyond memorisation.

This is the kind of interaction AI can potentially reproduce more effectively than a static question bank.

Check-Ride.ai says users can configure their mission profile, including the rating, aircraft, airport environment, weather and even examiner persona. The system then conducts the session and provides feedback based on the performance.

That degree of contextualisation could make the practice session considerably more realistic.

Why voice interaction matters

The voice component may actually be one of the most valuable features.

Pilots preparing for an oral examination often study silently. They read textbooks, highlight information, watch videos and answer written questions.

But the checkride is not silent.

You have to speak.

That creates a different challenge.

A pilot may understand the answer internally but struggle to explain it clearly. Another pilot may know the basic rule but start rambling when asked to elaborate. Someone else may become nervous when confronted with a follow-up question.

Speaking out loud exposes these weaknesses.

According to Check-Ride.ai's own comparison of AI tools, the purpose of its voice-based format is to reproduce the interaction between examiner and candidate rather than simply provide answers to questions.

That distinction is important.

The objective is not just:

"Do I know the answer?"

It is:

"Can I explain the answer clearly when someone is sitting across from me and asking questions?"

What happens after the mock checkride?

The session doesn't simply end after the last question.

Check-Ride.ai provides a debrief that identifies performance across ACS areas and highlights knowledge gaps. Its website demonstrates a dashboard containing satisfactory, marginal and unsatisfactory evaluations, along with specific study pointers.

This could be particularly useful because pilots often have an inaccurate idea of their own strengths and weaknesses.

We tend to study what we enjoy or what we already know.

A system that repeatedly identifies weaknesses can redirect preparation towards the subjects that actually need attention.

For example, a pilot might discover that:

• aircraft systems knowledge is strong;
• weather knowledge is reasonable;
• emergency procedures need improvement;
• regulations are inconsistent;
• airspace knowledge is weak;
• cross-country planning needs more work.

Instead of spending another ten hours reviewing everything equally, the pilot can concentrate on the deficient areas.

From studying everything to studying intelligently

This is potentially where AI can change the economics of pilot preparation.

Flight training is expensive.

Every hour spent with a CFI costs money, and instructor availability is not unlimited.

That doesn't mean AI should replace instructors. It means some repetitive preparation can potentially be done independently before the student meets the instructor.

Check-Ride.ai itself explicitly positions the product as a training supplement rather than a replacement for certified flight instruction. Its terms state that the service is not a replacement for certified flight instruction.

This distinction is extremely important.

A student could potentially use an AI system for repeated oral rehearsal and then use valuable CFI time for areas requiring human instruction, judgement and practical flying.

In other words:

AI can provide repetition.
The instructor provides instruction, judgement and real-world experience.

Which pilots can use it?

The current Check-Ride.ai website lists preparation for several FAA certificates and ratings, including:

• Private Pilot (PPL)
• Instrument Rating (IR)
• Commercial Pilot
• Certified Flight Instructor (CFI)
• Certified Flight Instructor–Instrument (CFII)
• Airline Transport Pilot (ATP)

The exact availability and configuration of individual ratings can change as the platform develops, so pilots should check the current service before relying on it for a particular checkride.

The broader idea, however, is significant.

AI-based oral preparation is no longer limited to the student pilot preparing for a Private Pilot checkride. It can potentially become useful throughout a pilot's progression.

It can also be useful for experienced pilots

There is an interesting lesson here for pilots who already have considerable flying experience.

Experience does not automatically mean that regulatory and theoretical knowledge remains sharp.

A pilot may have spent years flying but not regularly revisited particular regulations, equipment requirements or other knowledge areas.

Check-Ride.ai has published an analysis of more than 10,000 individually graded ACS answers from hundreds of mock oral sessions. The company's analysis found that regulatory and legality-related subjects were among the areas where weaknesses appeared, while it also reported stronger performance in areas involving aeronautical decision-making and weather.

These findings should be treated as platform-specific data rather than a representative study of all pilots. The company itself acknowledges selection bias and other methodological limitations.

Nevertheless, the underlying observation is worth considering:

Knowledge that isn't regularly tested can become rusty.

That applies not only to student pilots but potentially to experienced aviators as well.

One particularly interesting finding: thinking out loud

The company's analysis also looked at how pilots answered questions.

According to its published dataset, pilots who gave more structured and complete spoken explanations had higher satisfactory rates than pilots who tended to answer in fragments. The company explicitly cautions that this is a correlation and does not establish causation.

This makes intuitive sense.

An oral checkride isn't simply about producing a keyword.

A good pilot needs to demonstrate understanding.

For example, saying:

"Because of the regulations."

is very different from explaining:

"This operation requires X because the regulation addresses Y, and in this particular scenario I would also consider Z."

The second answer gives the examiner evidence of actual understanding.

Practising complete spoken explanations could therefore be useful even outside an AI platform.

How is this different from ChatGPT?

This is perhaps the most obvious question for anyone familiar with AI.

Why use a dedicated platform when general AI systems can already answer aviation questions?

The answer is purpose and workflow.

A general AI assistant can be extremely useful for:

• explaining difficult aviation concepts;
• simplifying regulations;
• creating study notes;
• generating practice questions;
• comparing aircraft systems;
• explaining weather;
• helping interpret technical material.

But the pilot generally controls the conversation.

You ask a question, the AI responds.

Check-Ride.ai is designed around the opposite relationship.

The examiner asks.
The pilot answers.
The examiner evaluates.
The examiner follows up.

That makes it closer to an oral-exam simulator.

The company's own comparison makes essentially this distinction: general AI tools are useful for learning and explanation, while Check-Ride.ai is specifically designed around rehearsal of the oral examination.

It doesn't necessarily mean one tool has to replace the other.

A pilot could use general AI to understand a difficult topic and then use a dedicated oral simulator to practise explaining it.

What about the CFI?

This is probably the most important question.

Can an AI DPE replace a flight instructor?

No—and it shouldn't be viewed that way.

An AI system can ask questions and evaluate responses against programmed standards, but a CFI brings something fundamentally different: human experience.

A CFI can observe a student's behaviour, understand their individual learning difficulties, relate theoretical knowledge to actual flying and recognise nuances that an automated system may miss.

The best use of AI is therefore likely to be alongside the instructor.

Imagine a student preparing for a checkride.

Instead of arriving at the instructor's office and spending an hour answering basic questions, the student could conduct several AI mock orals beforehand.

The instructor can then concentrate on the areas where the student repeatedly struggles.

That potentially makes instructor time more productive.

What about accuracy?

This is where pilots need to exercise caution.

Aviation is not a field in which an AI-generated answer should automatically be accepted simply because it sounds convincing.

AI systems can make mistakes.

Regulations change. FAA guidance changes. Aircraft-specific information differs. Operating limitations vary. Local procedures can differ.

And an AI system can sometimes produce an answer that sounds authoritative while being incomplete or incorrect.

Check-Ride.ai says that its responses are grounded through its technology and sources, and its platform is aligned with the ACS.

But that does not eliminate the need for pilots to verify important information against authoritative FAA material, aircraft documentation and their instructor.

For a pilot, the correct hierarchy should remain something like:

FAA regulations and official guidance → aircraft documentation → qualified instructor/DPE → AI as a training aid.

AI should help the pilot become better prepared—not become the final authority on aviation regulations.

The privacy question

There is another consideration that becomes relevant because the system involves voice interaction and performance tracking.

According to its privacy policy, Check-Ride.ai collects information such as account details, training parameters—including aircraft type and operating location—and payment information processed through third-party payment providers.

Pilots should therefore read the current privacy policy before using any AI training platform, particularly if sessions contain personally identifiable information or other information they would prefer not to share.

The platform also says that flight-school analytics are aggregate and privacy-protected, with student participation and minimum thresholds built into its school analytics model.

How does its pricing work?

One interesting feature of the current model is that Check-Ride.ai says it uses practice-session credits rather than a conventional subscription.

The website states that one credit is used per practice session, sessions have no duration limits or time caps, sessions can be paused and resumed without consuming another credit, credits do not expire and unused credits are refundable.

The company also currently advertises a free first session/demo without requiring a credit card.

For someone who only wants occasional oral practice, a pay-for-practice model may be attractive compared with paying for a recurring subscription. Pilots should, however, check the current pricing before purchasing because pricing and product terms can change.

The biggest advantage may be unlimited repetition

Perhaps the strongest argument for a tool like Check-Ride.ai is not that AI is somehow a better examiner than a human.

It is that AI can make repetition easier.

Imagine being able to conduct another mock oral at 10 p.m.

And another one the following morning.

And another one after reviewing your weak areas.

A human DPE cannot realistically provide that level of repeated practice at no scheduling cost.

A CFI cannot be available every time a student suddenly wants to practise.

An AI system can.

That makes it particularly interesting as a rehearsal tool.

But pilots should not confuse confidence with competence

There is also a danger.

Repeatedly using an AI system can make someone feel comfortable with a particular question set. But checkrides are not predictable scripts.

A real DPE may ask something the pilot never encountered during practice.

Therefore, the goal shouldn't be:

"Can I memorise the questions that the AI asks?"

The goal should be:

"Can I understand the underlying concepts well enough to handle a question I have never seen before?"

That distinction is fundamental to good pilot training.

Where Check-Ride.ai could fit into a pilot's preparation

A sensible preparation workflow could look something like this:

Step 1: Learn

Use ground school, textbooks, FAA publications and your CFI to learn the material.

Step 2: Clarify

Use appropriate resources—including AI tools—to clarify concepts that you don't understand.

Step 3: Practise

Use question banks and other study tools to test your knowledge.

Step 4: Speak

Conduct mock oral sessions using a tool such as Check-Ride.ai.

Step 5: Identify weaknesses

Look at the ACS areas where your performance is marginal or unsatisfactory.

Step 6: Return to authoritative sources

Study those subjects again using FAA material, aircraft documentation and instructor guidance.

Step 7: Practise again

Repeat the oral examination.

Step 8: Final human assessment

Have your CFI determine whether you are genuinely ready for the checkride.

This is where AI can fit naturally into the existing training ecosystem.

Could this become the future of pilot training?

It is too early to say exactly how far AI will go in aviation training.

But the direction is clear.

AI is moving from being a tool that simply answers questions to a system that can interact, evaluate and personalise training.

Check-Ride.ai is an example of this transition.

Its significance isn't necessarily that it has created an artificial DPE capable of replacing a human examiner.

The more interesting development is that it is attempting to turn AI into a practice environment.

That is a different concept.

A pilot doesn't necessarily need another textbook.

What a pilot often needs is someone—or something—to say:

"Okay, explain this to me."

Then:

"Why?"

Then:

"What if the situation changes?"

And finally:

"Let's move on to the next area."

If AI can do that reliably, it can become a useful addition to pilot training.

My view: an interesting tool, but not a shortcut

For student pilots, the attraction of Check-Ride.ai is easy to understand.

It provides a way to practise the oral examination whenever you want, forces you to answer verbally, evaluates your performance against the ACS and identifies areas requiring further preparation.

But I would not look at it as a shortcut to passing a checkride.

The real benefit is rehearsal.

Just as pilots practise emergency procedures repeatedly so that the correct response becomes more natural under pressure, practising oral responses can make the examination environment less unfamiliar.

And that may be the real value of AI in this particular part of aviation training.

The future of pilot training may not be about choosing between human instructors and artificial intelligence.

It may be about using each for what it does best.

The instructor provides experience, judgement, mentorship and practical flying expertise.

The FAA provides the regulatory and certification framework.

The aircraft provides the real-world environment.

And AI can provide something humans struggle to provide economically and continuously:

an examiner who is available whenever the pilot wants to practise.

For a pilot approaching a checkride, that could make the difference between simply knowing the material and being able to talk through it confidently when the examiner starts asking questions.