- Why No Official ITS-AI Pass Rate Exists
- What the Exam Actually Measures
- Scoring Mechanics: 700 on a 1-1000 Scale
- Format and Time Pressure
- The 2026 Content Revision and Outdated Outlines
- Where Candidates Are Most Likely to Slip
- A Domain-Ordered Readiness Plan
- Fees, Vouchers and Retake Mechanics
- How to Judge Pass-Rate Claims You Find Online
- Frequently Asked Questions
- Certiport does not publish pass rates for the IT Specialist - Artificial Intelligence exam, so any quoted percentage is unverified.
- The passing score is 700 on a 1-1000 scaled range, not a raw 70% requirement.
- The exam runs 45-50 questions with a 50-minute maximum, so pacing matters as much as knowledge.
- The English exam content update took effect June 30, 2026 and covers six domains.
Why No Official ITS-AI Pass Rate Exists
If you searched for the ITS-AI pass rate hoping for a tidy percentage, here is the honest answer: there isn't a verified one. The Information Technology Specialist - Artificial Intelligence Certification is issued by Pearson and administered through Certiport, a Pearson VUE business, and Certiport's scoring policy page states that it does not publish pass rates. That is a fact about the program, not a gap in this article.
This matters because pass-rate numbers circulate widely around certification exams, usually with no source. For ITS-AI, any figure you see quoted as an "official" or "industry average" pass rate should be treated as unsupported. What you can do is understand the mechanics that decide whether a candidate passes, and prepare against those. That is what the rest of this article covers, alongside our broader difficulty guide for the ITS-AI exam.
What the Exam Actually Measures
Because there is no pass-rate data to analyze, the most useful substitute is the exam's own blueprint. The IT Specialist - Artificial Intelligence exam objectives (catalogue identifier INF-307, copyright 2026) list six domains. Certiport does not publish percentage weights for them, so you should not assume any domain counts more than another. Treat all six as testable. If you want the full breakdown, see our complete guide to all six ITS-AI content areas.
Domain 1: AI Problem Definition
Deciding whether a problem suits an AI approach at all, and framing it so success can be measured.
- Feasibility assessment: is AI the right tool, and is the data and effort realistic?
- Translating a business need into a well-formed AI task
- Recognizing risks and constraints before any modeling begins
Domain 2: Data Collection and Transformation
Getting data into a usable, trustworthy shape.
- Sourcing and assembling datasets
- Cleaning, transforming and preparing data for modeling
- Understanding how data quality limits everything downstream
Domain 3: Feature Engineering
The 2026 outline treats this as its own domain rather than folding it into data preparation.
- Creating and selecting features that help a model learn
- Why representation choices change model behavior
- Connecting feature decisions to the data work in Domain 2
Domain 4: AI Algorithms and Models
The broadest conceptual domain, covering how models are chosen, built and judged.
- Natural language processing concepts
- Model-evaluation metrics and what each one tells you
- Explainability and human interaction with AI systems
Domain 5: Application Integrity and Deployment
Moving a model into a working application responsibly. The domain name is preserved exactly as the revised PDF words it.
- Application integration (objective 5.1)
- CI/CD practices for AI applications
- Security considerations for deployed AI
Domain 6: Maintaining and Monitoring AI in Production
What happens after launch.
- Detecting and responding to drift
- Ongoing monitoring of model behavior
- Decommissioning models at end of life
Notice what this implies about difficulty. The exam rewards candidates who understand the full AI lifecycle, from framing a problem to retiring a model, rather than those who only know how to train one. Candidates with a strong modeling background but little exposure to deployment, security or drift are the ones most likely to be surprised.
Scoring Mechanics: 700 on a 1-1000 Scale
The passing score is 700 on a 1-1000 scaled range. This is a scaled score, which is not the same as getting 70% of questions right. Scaling exists so that results are comparable across different forms of the exam, and it means you cannot reliably convert a number of correct answers into a score. For a deeper look, read our explainer on the ITS-AI passing score.
| Common assumption | What the published facts say |
|---|---|
| "You need 70% correct" | The threshold is 700 on a scaled 1-1000 range, not a raw percentage |
| "There is an official pass rate" | Certiport does not publish pass rates |
| "The exam has a fixed number of questions" | The listed estimate is 45-50 questions, a variable range |
| "Domain weights tell me where to focus" | No official percentage weights are published for the six domains |
The practical takeaway is that you should aim for comfortable mastery across all six domains rather than trying to calculate a minimum number of correct answers. Gaming a raw-percentage target is not a sound strategy when the scoring is scaled and the question count varies.
Format and Time Pressure
The exam is a computer-based, proctored knowledge assessment. Pearson's listing estimates 45-50 questions with a 50-minute maximum. That 50 minutes is timed exam time and excludes administration and tutorials, so you are not losing clock to the on-screen walkthrough. Even so, the arithmetic is tight: at the upper end you have roughly a minute per question.
- Delivery: through Pearson VUE test centers, through OnVUE online proctoring, or through the separate Certiport Authorized Testing Center (CATC) channel.
- OnVUE: requires a system check and a live webcam proctor.
- CATC: requires photo and signature ID and an NDA, with parental consent for candidates under 18 and no personal paper or communication devices.
- Interface: the IT Specialist exam tutorial describes how answer-option navigation works. Its generic 36-40-question estimate predates the exam-specific listing used here, so rely on the 45-50 range for ITS-AI.
The 2026 Content Revision and Outdated Outlines
One of the most important, and least discussed, influences on whether candidates pass is which outline they studied. Pearson announced an update to the IT Specialist AI certification on April 29, 2026, and Certiport's exam content update archive lists the English update as taking effect June 30, 2026. Other-language rollout dates differ, so this statement concerns English only.
Here is the trap. Pearson's general IT Specialist resources page still links a legacy copyright-2025 outline built around five domains. That older document should not be treated as complete current English coverage. The current outline has six domains and separates out topics that the legacy version did not treat independently, including feature engineering, NLP, explainability, human interaction, feasibility, model-evaluation metrics, CI/CD, security, drift and decommissioning.
Key Takeaway
Before you buy materials or take a practice test, check that it maps to six domains and mentions feature engineering as its own area. Retail practice banks sometimes retain legacy headings, and their item counts per heading are not official exam weights.
Where Candidates Are Most Likely to Slip
Without published statistics, we cannot say which domain has the lowest success rate, and we will not pretend otherwise. What we can do is reason from the structure of the blueprint about where preparation tends to be thinnest.
Lifecycle topics that sit outside the training loop
Many learners spend most of their time on model building and evaluation. The newer outline gives real room to Domain 5 (integration, CI/CD, security) and Domain 6 (drift, monitoring, decommissioning). Candidates who treat these as afterthoughts may meet unfamiliar scenario questions.
Early-stage judgment in Domain 1
Problem definition and feasibility are judgment topics rather than memorization topics. Questions here tend to reward recognizing when AI is a poor fit or when a framing is flawed. Reading definitions is not enough; you need to practice reasoning through short scenarios.
Metric selection in Domain 4
Knowing the names of evaluation metrics is the easy part. The harder skill is matching a metric to a situation and understanding what it hides. Pair this with explainability and human-interaction concepts, since the exam treats them as part of responsible model use.
Treating feature engineering as "just data prep"
Because Domain 3 is now separate from Domain 2, expect questions that probe the distinction. Study how feature choices connect to data quality, but be ready to answer feature-specific questions on their own terms.
A Domain-Ordered Readiness Plan
The program suggests approximately 150 hours of preparation, and objective profiles describe at least 150 hours. These are readiness profiles, not a verified logged-hours application requirement, and there is no degree requirement beyond objective-domain knowledge. See our ITS-AI requirements guide for eligibility detail. Below is one way to sequence that effort so each domain builds on the last. It is a suggestion, not an official curriculum, and the six domain headings are exam objectives rather than a prescribed course. Our full ITS-AI study guide expands on this approach.
Frame and feed: Domains 1 and 2
- Practice judging AI feasibility and framing measurable problems
- Work through data collection, cleaning and transformation concepts
- Start with these because every later domain assumes you can define the problem and trust the data
Represent and model: Domains 3 and 4
- Study feature engineering separately from data prep
- Cover NLP basics, evaluation metrics, explainability and human interaction
- This is the heaviest conceptual block, so give it the most hours
Ship and sustain: Domains 5 and 6
- Review application integration, CI/CD and AI security
- Cover drift, monitoring and decommissioning
- Finish with these so they are fresh, then run timed full-length practice
Reserve the final days for timed question sets rather than new reading, and keep a one-page list of facts to skim; our ITS-AI cheat sheet is a good template for that.
Fees, Vouchers and Retake Mechanics
Pass-rate anxiety often comes down to what a failed attempt costs. Two voucher routes appear in the published facts, and they are not interchangeable.
| Option | Listed price | Key conditions |
|---|---|---|
| Exam-only voucher (Pearson MindhubPro) | USD 127 web/member pricing | Country-restricted and unavailable in listed markets; expires 12 months after purchase |
| CATC voucher with retake | USD 133 | US-only; proctoring may cost extra; not usable at Pearson VUE centers or through OnVUE |
Voucher expiry is separate from credential validity. A voucher you buy must be used within 12 months, while a passed credential awarded on or after 2025-06-18 stays valid for five years; earlier awards remain nonexpiring. Recertification means purchasing a new voucher and passing the current exam. For the complete financial picture, see our ITS-AI certification cost breakdown.
If you are weighing whether the investment pays off, the ROI analysis and the salary guide cover that question separately from the pass-rate discussion here.
How to Judge Pass-Rate Claims You Find Online
Since the issuer does not release the data, treat every number you encounter with a checklist mindset:
- Ask for the source. A genuine statistic would trace back to Certiport or Pearson. None exists for ITS-AI, so a sourced claim should be easy to verify and an unsourced one should be ignored.
- Check the credential name. The acronym is shared by other, unrelated certifications. Confirm the page is about the IT Specialist - Artificial Intelligence exam from Pearson and Certiport.
- Check the date and outline. Material built on the legacy five-domain outline predates the June 30, 2026 English update and may not reflect current coverage.
- Distrust confident precision. A claim like "exactly 68% pass" implies data that the issuer says it does not publish.
If you are still orienting yourself, our primer on what the ITS-AI certification is clarifies exactly which credential this site covers, and the ITS-AI jobs overview discusses who tends to value it. The most productive use of your time is a realistic self-assessment: take a full ITS-AI practice exam, review misses by domain, and repeat until your results are consistent across all six areas.
Frequently Asked Questions
There is no official figure. Certiport does not publish pass rates for the IT Specialist - Artificial Intelligence exam, so any specific percentage you see is unverified. Focus on the published passing score of 700 on a 1-1000 scale instead.
No. The passing score is a scaled value on a 1-1000 range, not a raw 70% requirement. Scaling accounts for differences between exam forms, so you cannot directly convert correct answers into a final score.
Pearson's listing estimates 45-50 questions with a 50-minute maximum. The count is a variable range rather than a fixed form size, and the 50 minutes covers timed exam time only, excluding administration and tutorials.
Yes. Certiport lists an English update effective June 30, 2026, following an April 29, 2026 announcement. The current outline has six domains. Other languages roll out on different dates, and the older five-domain outline still linked on some pages is not complete current English coverage.
The published facts do not say difficulty changes with retake timing. What does change is the content outline if an update occurs in between, so always confirm you are studying the current six-domain objectives before scheduling another attempt.