- The Short Answer: What the Letters Spell Out
- Who Stands Behind the Name
- Reading the Title Word by Word
- What the Credential Covers: Six Domains
- How the Exam Is Delivered and Priced
- Scoring and Validity in Plain Terms
- Where the Name Shows Up in Hiring
- Naming Pitfalls: Outdated Outlines and Look-Alike Acronyms
- Turning the Name Into a Study Plan
- Frequently Asked Questions
- ITS-AI stands for Information Technology Specialist - Artificial Intelligence Certification, issued by Pearson and administered through Certiport.
- The current English outline organizes the exam into six domains, from AI Problem Definition to Maintaining and Monitoring AI in Production.
- Passing requires a scaled score of 700 on a 1-1000 scale, not a raw 70 percent.
- Awards earned on or after 2025-06-18 stay valid for five years; earlier awards do not expire.
The Short Answer: What the Letters Spell Out
ITS-AI stands for Information Technology Specialist - Artificial Intelligence Certification. Pearson publishes it, and Certiport, a Pearson VUE business, administers it. On Pearson's public listings the credential appears as "IT Specialist - Artificial Intelligence," and the Pearson catalogue identifier is INF-307. Here, ITS-AI refers to that credential and nothing else.
If you landed here from a search for the acronym, you may have seen it attached to other products or programs. This article stays focused on the IT Specialist credential. For a broader overview, see our pages on what ITS-AI is and the meaning of ITS-AI. The acronym is simply a compact way of writing the name of the IT Specialist series entry that tests artificial intelligence knowledge.
Who Stands Behind the Name
The credential sits inside Pearson's IT Specialist family of knowledge assessments. Pearson is the issuer, and Certiport handles administration. That matters for candidates in practical ways: the exam objectives live on Certiport's site, vouchers are sold through Pearson-linked storefronts, and testing happens either through Pearson VUE channels or through the separate Certiport Authorized Testing Center (CATC) channel.
If you want the full picture of what the credential is and how it fits into a career, our ITS-AI certification overview and what is ITS-AI certification pages go deeper.
Reading the Title Word by Word
Each word in the name tells you something about what to expect.
Information Technology
The credential belongs to an IT-focused series. It is framed as a knowledge assessment for people working in or entering technology roles, not as a research-level machine learning qualification. No degree is required beyond command of the objective-domain knowledge.
Specialist
"Specialist" signals a defined, bounded subject area. The exam does not try to certify general computing skill; it certifies that you understand the specific objectives published for artificial intelligence. Those objectives are the contract between the issuer and the candidate.
Artificial Intelligence
This is the subject. In the current English objectives, it spans the full lifecycle of an AI solution: defining the problem, preparing data, engineering features, choosing and evaluating models, integrating and deploying applications, and monitoring them after launch. It is a lifecycle credential, not a single-algorithm test.
Certification
Passing the exam earns the credential. The issuer describes about 150 hours of preparation as a readiness profile. That figure is a suggestion about the knowledge level the program expects, not a logged-hours requirement you must document when you register.
What the Credential Covers: Six Domains
The revised public objectives, a 2026-copyright document from Pearson and Certiport, list six domains. Official percentage weights are not published, so the list below simply counts domains rather than ranking them. The six headings are official exam objectives, not a preparation curriculum, which means they tell you what could be tested, not how to learn it. Our complete guide to all six ITS-AI content areas expands on each one.
Domain 1: AI Problem Definition
Candidates must be able to frame a business or technical need as an AI problem and judge whether AI is the right tool.
- Assessing feasibility before committing resources
- Translating goals into measurable success criteria
- Recognizing where human interaction fits the solution
Domain 2: Data Collection and Transformation
Models depend on data, so this domain covers sourcing, cleaning, and reshaping it for use.
- Gathering and validating datasets
- Handling missing, inconsistent, or noisy values
- Transforming data into usable formats
Domain 3: Feature Engineering
The revised outline treats feature engineering as its own domain rather than folding it into data preparation.
- Selecting and constructing informative features
- Preparing inputs for different model types
- Understanding how feature choices affect results
Domain 4: AI Algorithms and Models
This domain addresses choosing, training, and judging models, including language-focused work.
- Matching algorithm families to problem types
- Natural language processing (NLP) concepts
- Model-evaluation metrics and how to interpret them
- Explainability of model behavior
Domain 5: Application Integrity and Deployment
This domain keeps the revised PDF's exact wording. Application integration is objective 5.1, so deployment topics start with connecting AI to real applications.
- Application integration
- CI/CD practices for AI solutions
- Security considerations for deployed AI
Domain 6: Maintaining and Monitoring AI in Production
Launch is not the end. This domain covers keeping a deployed system healthy.
- Watching for drift as real-world data changes
- Monitoring performance over time
- Planning for decommissioning when a system is retired
Notice how the name's phrase "Artificial Intelligence" is stretched across both ends of the lifecycle. The first domain asks whether a problem deserves an AI solution at all, and the last asks how to retire one responsibly. Candidates who only study algorithms will find that a large share of the objectives lies outside model math.
How the Exam Is Delivered and Priced
The name tells you what the credential is, but candidates also want to know how to sit for it. The exam is a computer-based, proctored knowledge assessment. You can take it through Pearson VUE centers, through OnVUE online proctoring, or through the separate CATC channel.
Pearson's MindhubPro listing estimates 45-50 questions with a 50-minute maximum. That is a variable range, not a fixed form count, so do not plan around a specific number of items. The 50 minutes is timed exam time and excludes administration and tutorials. An older generic IT Specialist tutorial mentions a 36-40-question estimate, but that figure predates the exam-specific listing and should not override it.
| Channel | What to know |
|---|---|
| Pearson VUE test center | In-person proctored delivery; uses the standard voucher. |
| OnVUE online proctoring | Requires a system check and a live webcam proctor. |
| Certiport Authorized Testing Center (CATC) | Separate channel with its own conditions: photo/signature ID, an NDA, parental consent for candidates under 18, and no personal paper or communication devices. |
Fee mechanics
Pearson MindhubPro displays USD 127 web/member pricing for the exam-only voucher. That voucher is country-restricted, is unavailable in some listed markets, and expires 12 months after purchase. Voucher expiry is a separate matter from how long the credential remains valid once you earn it.
An alternative is a USD 133 voucher with retake, sold through Certiport's store. It is US-only and designed for the CATC channel. Proctoring may cost extra, and this voucher cannot be used at Pearson VUE centers or through OnVUE. Choosing the wrong voucher for your testing channel is an avoidable and expensive mistake. For a fuller breakdown, see our ITS-AI certification cost guide.
Scoring and Validity in Plain Terms
The passing score is 700 on a 1-1000 scale. This is a scaled score, not a raw 70 percent requirement, so you cannot convert it to a simple count of correct answers. Certiport does not publish pass rates, which means any specific pass-rate figure you see circulating should be treated skeptically. Our pages on the ITS-AI passing score and the ITS-AI pass rate explain what is and is not known.
Validity depends on when you earn the credential. Awards earned on or after 2025-06-18 are valid for five years. Earlier awards remain nonexpiring. To recertify, you buy a new voucher and pass the current exam, which is worth remembering because "current" means the exam as it exists then, not the one you originally passed.
Where the Name Shows Up in Hiring
The credential name appears most naturally on resumes of people entering technology roles that touch AI: junior data and machine learning support positions, AI-adjacent analyst roles, application developers integrating AI features, and IT staff who maintain deployed AI systems. Because the objectives run from problem definition through production monitoring, the credential maps to teams that build, ship, and operate AI rather than only research it.
It is best treated as a structured signal that you know the vocabulary and lifecycle of AI work, not as a guarantee of any particular job or pay level. We avoid quoting salary figures here because none are published for this credential. For discussion of roles and earnings context, see our ITS-AI jobs and ITS-AI salary guide pages, and our worth-it analysis if you are weighing the investment.
Naming Pitfalls: Outdated Outlines and Look-Alike Acronyms
Two kinds of confusion trip up candidates.
The legacy outline problem
Pearson's general IT Specialist resources page still links an older outline carrying a 2025 copyright date, organized into five domains. The revised English document has six. If you study from the five-domain outline, you may miss separately listed topics that the current version treats on their own, such as feature engineering, NLP, explainability, human interaction, feasibility, model-evaluation metrics, CI/CD, security, drift, and decommissioning.
The English content update took effect June 30, 2026, per Certiport's exam content updates archive, following an announcement dated April 29, 2026. Other-language rollout dates differ, so a candidate testing in another language should check the schedule for that language rather than assume the English date applies.
Practice-bank headings
Some retail practice products retain legacy domain headings, and their item counts per heading are not official exam weights. Use practice material to rehearse question styles and find weak spots, but anchor your scope to the issuer's revised objectives.
Key Takeaway
Before you open any study material, check that it reflects six domains and includes Application Integrity and Deployment as written. If it describes five domains, it is likely built from the legacy outline.
Turning the Name Into a Study Plan
The lifecycle structure suggests a natural order. Start where the work starts, with problem definition, and finish where the work ends, with production monitoring. The sequence below uses the roughly 150-hour readiness profile as a sizing guide only; it is not a requirement. For a fuller approach, our ITS-AI study guide and one-page cheat sheet are good companions, and you can drill question styles on the main practice test site.
Problem framing and data
- Work through Domain 1 first so every later topic has context.
- Cover Domain 2, since data quality shapes everything downstream.
Features and models
- Study Domain 3 as a standalone topic, not an afterthought.
- Give Domain 4 the most time: algorithm choice, NLP, evaluation metrics, explainability.
Deployment and operations
- Cover Domain 5, starting with application integration as objective 5.1.
- Finish with Domain 6: drift, monitoring, and decommissioning.
- Use timed practice questions to rehearse a 50-minute pace.
Candidates who wonder how demanding this is can read our difficulty guide, and those still checking eligibility can start with the requirements page and the exam dates page. For hands-on prep options, see ITS-AI training.
Frequently Asked Questions
It stands for Information Technology Specialist - Artificial Intelligence Certification. Pearson issues the credential and Certiport, a Pearson VUE business, administers it. Pearson's public listings call it IT Specialist - Artificial Intelligence.
No. Several unrelated products share the letters. This site covers only the Pearson and Certiport IT Specialist credential, so fees, domains, and scoring rules described here apply to that credential alone.
The revised English objectives list six: AI Problem Definition; Data Collection and Transformation; Feature Engineering; AI Algorithms and Models; Application Integrity and Deployment; and Maintaining and Monitoring AI in Production. No official percentage weights are published.
You need 700 on a 1-1000 scaled score. That is not the same as answering 70 percent of questions correctly, and Certiport does not publish pass rates.
Awards earned on or after 2025-06-18 are valid for five years, while earlier awards do not expire. Recertifying means purchasing a new voucher and passing the current exam. Voucher expiry, 12 months after purchase, is a separate matter from credential validity.