- The One-Page Snapshot: Exam Facts at a Glance
- Which Credential This Is (and Which Outline Is Current)
- Format, Timing, and Scoring Mechanics
- Fees, Vouchers, and Delivery Channels
- The Six Domains: What to Memorize in Each
- Concepts That Trip Candidates Up
- Sequencing Your Review Around the Domains
- Validity, Recertification, and Where It Fits Professionally
- FAQ
- The exam has six objective domains; Pearson publishes no official percentage weights for them.
- Passing score is 700 on a 1-1000 scaled range, not a raw 70%.
- Expect roughly 45-50 questions in a 50-minute timed limit, per Pearson's listing.
- Use the revised 2026 outline; Pearson's older five-domain PDF is legacy and incomplete.
The One-Page Snapshot: Exam Facts at a Glance
This cheat sheet condenses everything you need to recall on exam week for the Information Technology Specialist - Artificial Intelligence Certification, issued by Pearson and administered through Certiport, a Pearson VUE business. Keep the table below as your quick-reference card, then use the later sections to drill into domain content.
| Item | Fact |
|---|---|
| Credential | IT Specialist - Artificial Intelligence (Pearson catalogue identifier INF-307) |
| Issuer / administrator | Pearson; administered by Certiport, a Pearson VUE business |
| Question count | Estimated 45-50 (a variable range, not a fixed form length) |
| Time limit | 50 minutes maximum of timed exam time |
| Passing score | 700 on a 1-1000 scaled score |
| Domains | Six objective domains; no official weights published |
| Exam-only voucher | USD 127 web/member pricing on Pearson MindhubPro |
| Delivery | Computer-based, proctored: Pearson VUE center, OnVUE, or a Certiport Authorized Testing Center |
| Validity | Five years for awards on or after 2025-06-18 |
| English content update | June 30, 2026 |
If you want the full narrative behind any row, the ITS-AI Study Guide 2026 walks through preparation end to end, and the ITS-AI Passing Score breakdown explains scaled scoring in more depth.
Which Credential This Is (and Which Outline Is Current)
The acronym can be ambiguous across the industry, so pin down exactly what you are preparing for: the Pearson/Certiport IT Specialist - Artificial Intelligence exam. If you are still orienting yourself, the explainers on what ITS-AI certification is and what ITS-AI stands for cover the naming in plain terms.
The practical consequence: if your study notes came from the five-domain outline, you are likely missing separate coverage that now appears explicitly, including feature engineering, natural language processing, explainability, human interaction, feasibility, model-evaluation metrics, CI/CD, security, drift, and decommissioning. Also note that the six domain headings are official exam objectives, not a preparation curriculum, so they tell you what can be tested rather than how to learn it. The complete guide to all six content areas expands each one.
Format, Timing, and Scoring Mechanics
Question count and time
Pearson MindhubPro lists an estimate of 45-50 questions with a 50-minute maximum. Treat the question count as a range: your form may land anywhere in it. You may see an older generic estimate of 36-40 questions in the IT Specialist Exam Tutorial (copyright 2021); that document is older than the exam-specific listing, so rely on the 45-50 figure. The 50 minutes is timed exam time only, excluding administrative steps and the on-screen tutorial.
Scaled scoring
You need 700 on a 1-1000 scale. This is a scaled score, so it should not be read as "answer 70% correctly." Certiport does not publish pass rates, which means any pass-rate figure you encounter should be treated skeptically. The ITS-AI pass rate analysis explains what can and cannot be said from available data.
Answer interaction
The IT Specialist tutorial describes answer-option navigation in the exam interface. Practice with an interface that mimics selecting and reviewing options so that mechanics do not cost you seconds on a 50-minute clock. For a realistic feel, run timed sets on the ITS-AI practice test site.
Key Takeaway
With roughly 45-50 questions in 50 minutes, budget a little over a minute per item. Flag and move on rather than letting one modeling scenario consume your buffer.
Fees, Vouchers, and Delivery Channels
Fee mechanics are a frequent source of confusion because several purchase routes exist. The facts to hold onto:
- Exam-only voucher: Pearson MindhubPro displays USD 127 web/member pricing. The voucher is country-restricted, unavailable in listed markets, and expires 12 months after purchase. Voucher expiry is separate from credential validity.
- Alternative voucher with retake: a US-only Certiport Authorized Testing Center (CATC) voucher at USD 133, which includes a retake. Proctoring may cost extra. This voucher cannot be used at Pearson VUE centers or through OnVUE.
- Retail practice products: practice-bank item counts are not official exam weights, and some products still use legacy headings.
| Route | Price shown | Where you can test | Notes |
|---|---|---|---|
| Exam-only voucher (MindhubPro) | USD 127 | Pearson VUE centers or OnVUE | Country-restricted; 12-month expiry from purchase |
| CATC voucher with retake | USD 133 | CATC only | US-only; proctoring may cost extra; not valid via OnVUE or Pearson VUE centers |
For a fuller view of budgeting, including what is and is not bundled, see the ITS-AI certification cost breakdown.
Test-day rules by channel
OnVUE requires a system check and a live webcam proctor. At a CATC, expect photo/signature ID, a non-disclosure agreement, parental consent for candidates under 18, and no personal paper or communication devices. Scheduling windows and deadlines are covered in the ITS-AI exam dates guide.
The Six Domains: What to Memorize in Each
Pearson publishes no percentage weights, so do not over-invest in one domain on the assumption that it dominates. The count of six domain lines is the only structural fact available. Below is a working checklist built around each official domain name.
Domain 1: AI Problem Definition
Decide whether and how AI should be applied before any data is touched.
- Framing a business need as a machine learning task (classification, regression, clustering, generation)
- Feasibility: is there enough data, a measurable target, and a realistic benefit?
- Success criteria and which model-evaluation metrics match the goal
- Human interaction considerations: who uses the output and how they will trust it
Domain 2: Data Collection and Transformation
Quality of inputs bounds quality of outputs.
- Sources, collection methods, and representativeness of samples
- Cleaning: missing values, duplicates, outliers, inconsistent formats
- Transformations such as normalization, scaling, and encoding
- Train/validation/test splitting and avoiding leakage between them
Domain 3: Feature Engineering
The current objectives treat this as its own domain rather than a sub-bullet.
- Creating, selecting, and transforming features from raw data
- Dimensionality reduction and why fewer, better features can help
- Handling categorical, numeric, text, and time-based inputs
- How feature choices influence bias, overfitting, and explainability
Domain 4: AI Algorithms and Models
Match method to problem and judge results.
- Supervised versus unsupervised learning and when each applies
- Neural networks, deep learning concepts, and natural language processing
- Evaluation metrics: choosing among accuracy-style measures, precision/recall tradeoffs, and error measures for regression
- Overfitting, underfitting, and tuning at a conceptual level
- Explainability: why a model produced an output and how to communicate it
Domain 5: Application Integrity and Deployment
Use this exact name; the revised outline preserves it. Application integration is objective 5.1.
- Integrating a model into an application and its surrounding systems
- CI/CD concepts as applied to AI workloads
- Security considerations for models, data, and endpoints
- Responsible-use and integrity concerns when releasing AI features
Domain 6: Maintaining and Monitoring AI in Production
A model is not finished at release.
- Monitoring performance and recognizing drift over time
- Retraining triggers and versioning
- Decommissioning a model or system responsibly
- Feedback loops and ongoing human oversight
These bullets are a review framework for the topic areas named in the objectives. For exercises tied to each area, the ITS-AI training overview and the practice question bank help you test recall rather than just re-read.
Concepts That Trip Candidates Up
Metric selection versus metric definition
Knowing what precision and recall mean is the easy part. Scenario questions ask which metric fits a situation. When missing a positive case is costly, favor recall-oriented reasoning; when false alarms are costly, favor precision-oriented reasoning. Read the consequence in the scenario, not just the vocabulary.
Data leakage and split discipline
Any transformation fitted on the full dataset before splitting can leak information into evaluation. Expect questions that ask where in the pipeline a step should occur.
Feature engineering is now a distinct domain
Candidates who studied from the legacy five-domain outline sometimes fold feature work into data preparation. The revised outline separates them, so be ready to distinguish cleaning and transformation from creating and selecting features.
Deployment is more than "put it on a server"
Domain 5 pairs integration with integrity and security, and Domain 6 continues the lifecycle through drift and decommissioning. Questions may describe a symptom, such as degrading predictions after a change in input patterns, and ask you to name the concept.
Sequencing Your Review Around the Domains
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 requirement for applying. There is no degree requirement beyond knowledge of the objective domains; the ITS-AI requirements guide covers eligibility in detail. One sensible way to distribute that time follows the lifecycle order of the domains:
Domains 1 and 2
- Problem framing, feasibility, and data quality foundations
- Practice splitting data and spotting leakage
Domain 3
- Feature creation, selection, and transformation
- Link features to bias and explainability
Domain 4
- Algorithm families, NLP, and evaluation metrics
- Metric-selection scenarios
Domains 5 and 6
- Integration, CI/CD, security, drift, and decommissioning
- Full timed mock exams against a 50-minute clock
Adjust the pacing to your own hours, and revisit your weakest domain in the final days rather than rereading strengths. The full study guide offers a longer plan.
Validity, Recertification, and Where It Fits Professionally
Awards earned on or after 2025-06-18 are valid for five years; earlier awards remain nonexpiring. Recertification requires purchasing a new voucher and passing the current exam, so refresh against whatever outline is current at that time rather than assuming today's objectives will persist.
As an entry-level, knowledge-based credential, it signals foundational fluency across the AI project lifecycle rather than deep specialization. It is most useful for students and early-career candidates building a portfolio for technology roles, and for working professionals who want a structured, vendor-issued record of AI literacy. For market context, see the ITS-AI jobs overview, the salary guide, and the ROI analysis; treat any specific earnings claim cautiously unless it cites a source.
FAQ
Pearson MindhubPro estimates 45-50 questions with a 50-minute maximum. This is a variable range rather than a fixed count, so your form may differ from another candidate's.
A scaled score of 700 on a 1-1000 scale. It is not a raw 70% requirement, and Certiport does not publish pass rates.
No official percentage weights are published. The six domains are Pearson's objective headings, so study all of them rather than guessing at emphasis based on retail practice-bank item counts.
Not necessarily. The USD 127 exam-only voucher is country-restricted and expires 12 months after purchase. The USD 133 US-only CATC voucher with retake works only through the CATC channel, not Pearson VUE centers or OnVUE.
Five years for awards earned on or after 2025-06-18. Earlier awards remain nonexpiring. Recertifying means buying a new voucher and passing the current exam.