- The Short Answer: What ITS-AI Stands For
- Who Stands Behind the Name
- Reading the Name Word by Word
- What the Credential Actually Covers: Six Domains
- How the Exam Works
- A Warning About Outdated Outlines
- Who the Credential Is For
- Sequencing Your Preparation by Domain
- How Long the Credential Lasts
- Frequently Asked Questions
- ITS-AI here means Information Technology Specialist - Artificial Intelligence Certification, issued by Pearson and administered by Certiport.
- The current objectives group content 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.
- The exam allows a 50-minute maximum and an estimated 45-50 questions, a variable range rather than a fixed count.
The Short Answer: What ITS-AI Stands For
ITS-AI is shorthand for Information Technology Specialist - Artificial Intelligence Certification. On the official side, the credential appears under the public name "IT Specialist - Artificial Intelligence." The "ITS" portion points to the broader IT Specialist program, and the "AI" portion names the subject area this particular exam measures.
If you have arrived here from a search for the acronym, one clarification matters: this page discusses only the Pearson credential described above. The same letters get used informally elsewhere, so when you compare study resources, confirm that they target the IT Specialist exam on artificial intelligence and not some other program. For a shorter treatment of the naming question, see What Does ITS-AI Stand For? and the companion piece ITS-AI Meaning.
Who Stands Behind the Name
The credential is issued by Pearson and administered through Certiport, a Pearson VUE business. Pearson's catalogue identifier for the exam is INF-307, and you will see the objectives document labeled with the 307 number in several places. That number is useful when you are hunting for the correct official outline or matching a practice product to the right exam.
Knowing the issuer shapes your expectations. This is a vendor-neutral, knowledge-based assessment, not a hands-on lab or a product-specific badge tied to one cloud platform. It tests whether you understand the lifecycle of an AI project, including how problems are framed, how data and features are prepared, how models are built and evaluated, and how deployed systems are kept healthy.
Reading the Name Word by Word
Each word in the title tells you something about the exam's intent.
Information Technology Specialist
The IT Specialist program is aimed at people building foundational competence in a technology domain, often students and early-career professionals. The framing is "specialist" in a topic, not "architect" or "engineer," which signals that the exam rewards solid conceptual command across a defined objective list rather than deep production experience.
Artificial Intelligence
The subject is the practical AI project lifecycle. The six domains run from defining a problem through monitoring a system in production, so the exam treats AI as an end-to-end discipline, not only as a set of algorithms.
Certification
Passing earns a credential you can list on a resume or professional profile. It is a time-limited award for recent candidates, discussed in the validity section below. For the bigger picture of what the credential is, What Is ITS-AI Certification? goes deeper.
What the Credential Actually Covers: Six Domains
The current objectives list six domains. These are the official exam objectives, not a preparation curriculum, so treat them as the boundary of what can be tested. Pearson does not publish percentage weights for them, which means you should not assume any one domain is larger than another. For a deeper walk-through of each, read ITS-AI Exam Domains 2026: Complete Guide to All 6 Content Areas.
Domain 1: AI Problem Definition
Before any model exists, a candidate must show they can frame the work correctly.
- Deciding whether a problem is suited to AI at all, including feasibility considerations
- Defining goals and success measures in terms the business understands
- Understanding how humans will interact with the resulting system
Domain 2: Data Collection and Transformation
Models are only as useful as the data feeding them.
- Sourcing and gathering data responsibly
- Cleaning and transforming raw data into a usable shape
- Recognizing quality issues that undermine later results
Domain 3: Feature Engineering
The current objectives treat feature engineering as its own domain, separate from general data preparation.
- Creating and selecting inputs that help a model learn
- Understanding how representation choices affect outcomes
- Connecting feature decisions to the problem you defined in Domain 1
Domain 4: AI Algorithms and Models
This is where the technical vocabulary concentrates.
- Choosing appropriate algorithm families for a given task
- Natural language processing concepts
- Model-evaluation metrics and how to interpret them
- Explainability, meaning why a model produced a given output
Domain 5: Application Integrity and Deployment
This is the exact wording used in the revised objectives. Application integration remains objective 5.1.
- Integrating a model into a working application
- CI/CD concepts for shipping changes safely
- Security considerations for AI-enabled applications
Domain 6: Maintaining and Monitoring AI in Production
Launch is not the finish line.
- Watching deployed systems for drift as real-world data changes
- Keeping performance and integrity on track over time
- Decommissioning a system when it should be retired
Notice how the list mirrors a project timeline. Questions often reward candidates who can place a scenario at the correct stage and then choose the action that belongs there. A team complaining that accuracy has quietly degraded months after launch is a Domain 6 issue, while a team unsure whether the problem needs machine learning at all is a Domain 1 issue.
How the Exam Works
Format and Delivery
The exam is a computer-based, proctored knowledge assessment. You can take it at a Pearson VUE test center or through OnVUE, the online-proctored option, which requires a system check and a live webcam proctor. A separate route exists through a Certiport Authorized Testing Center (CATC). Each channel has its own voucher rules, covered below.
Length and Timing
Pearson's MindhubPro listing estimates 45-50 questions with a 50-minute maximum. Treat the question count as a range, not a promise of an exact number of items on every form. The 50 minutes refers to timed exam time and excludes administration and tutorials. An older generic tutorial for the IT Specialist family mentions a lower question estimate, but the exam-specific listing is the better reference for this credential. If you want a sense of how demanding that pace feels, How Hard Is the ITS-AI Exam? Complete Difficulty Guide 2026 covers it.
Scoring
The passing score is 700 on a 1-1000 scale. This is a scaled score, so it should not be read as "you need 70 percent of questions right." Certiport does not publish pass rates, which is why any site quoting a precise pass percentage deserves skepticism. Our own treatment is in ITS-AI Pass Rate 2026: What the Data Shows, and the scoring mechanics are explained in ITS-AI Passing Score 2026: Exactly What You Need to Pass.
Fees and Vouchers
| Option | Price shown | Key conditions |
|---|---|---|
| Exam-only voucher (Pearson MindhubPro) | USD 127 web/member pricing | Country-restricted, 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 |
Two details trip people up. First, voucher expiry is separate from credential validity: the 12-month clock on an unused voucher has nothing to do with how long your certification lasts after you pass. Second, the CATC voucher is tied to that channel only, so buying it and then trying to schedule through OnVUE will not work. A full breakdown lives in ITS-AI Certification Cost 2026: Complete Pricing Breakdown.
A Warning About Outdated Outlines
The exam content was updated, with the English release listed on June 30, 2026, following an April 29, 2026 announcement. Other-language rollout dates differ, so the release statement here concerns English only.
This creates a 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 revised objectives, with six domains, add or separate out topics such as feature engineering, natural language processing, explainability, human interaction, feasibility, model-evaluation metrics, CI/CD, security, drift and decommissioning.
Practical consequences:
- If a study resource lists only five domains, check whether it predates the revision.
- Some retail practice products retain legacy headings, and their item counts per heading are not official exam weights.
- When in doubt, download the current objectives from Certiport and compare line by line.
Key Takeaway
Anchor your preparation to the six-domain revised objectives. A study plan built on the legacy five-domain outline can leave real gaps, particularly in feature engineering, explainability, CI/CD and monitoring topics.
Who the Credential Is For
There is no degree requirement beyond knowledge of the objective domains. Certiport's program materials suggest roughly 150 hours of preparation or experience as a readiness profile. That figure describes the kind of background a candidate typically brings, not a logged-hours requirement you must document. Details on eligibility are in ITS-AI Requirements 2026: Eligibility, Prerequisites & How to Qualify.
The people who tend to benefit most include:
- Students in computing or data-related programs who want a recognized credential showing structured AI literacy.
- Career changers moving into AI-adjacent IT roles who need a defined syllabus.
- IT support and operations staff whose organizations are adopting AI tools and who need to speak accurately about deployment, security and monitoring.
- Junior analysts and developers who want to demonstrate they understand the whole lifecycle, not only one slice of it.
Employers reading the credential will generally interpret it as evidence of foundational, vendor-neutral competence. It is best viewed as a signal of readiness that complements projects and practical experience, not a replacement for them. For the career angle, see ITS-AI Jobs, and for the economics, Is the ITS-AI Certification Worth It? Complete ROI Analysis 2026 and ITS-AI Salary Guide 2026: Complete Earnings Analysis.
Sequencing Your Preparation by Domain
You do not need an elaborate methodology, but the domain order suggests a sensible schedule because later domains build on earlier ones. Here is one way to map a six-week plan onto the objectives. Adjust the pace to your own background, and see the ITS-AI Study Guide 2026: How to Pass on Your First Attempt for a fuller approach.
Problem framing and data
- Domain 1: practice deciding when AI is and is not appropriate
- Domain 2: learn data collection and transformation vocabulary
Feature engineering
- Domain 3 deserves its own week because it is a separate domain in the revised objectives
Algorithms and models
- Domain 4 carries the densest terminology: model types, NLP, evaluation metrics, explainability
Integration and deployment
- Domain 5: application integration, CI/CD and security
Production and review
- Domain 6: drift, monitoring and decommissioning
- Full review against the official objectives and timed practice
Because the exam has a 50-minute maximum for an estimated 45-50 questions, build in timed practice during the final week so the pace feels familiar. When you reach the review stage, a condensed reference such as the ITS-AI Cheat Sheet 2026: One-Page Review of Must-Know Facts can help you spot weak areas, and you can test yourself with the ITS-AI practice tests to see which domains need another pass. For structured courses and resources, see ITS-AI Training.
How Long the Credential Lasts
For awards earned on or after June 18, 2025, validity is five years. Awards earned before that date remain nonexpiring. Recertification means purchasing a new voucher and passing the current exam, not a continuing-education filing. Because the exam content has been revised, a recertification attempt years from now will test whatever the objectives look like then, so plan to re-check the official outline instead of relying on what you studied the first time.
If you are still working out when to sit the exam, ITS-AI Exam Dates 2026: Testing Windows, Deadlines & Scheduling explains scheduling. For a broader overview of the credential itself, start with What Is ITS-AI? or the focused explainer What Does ITS-AI Mean?, and when you are ready to measure your readiness, head to the ITS-AI Exam Prep practice test site.
Frequently Asked Questions
On this site, ITS-AI stands for Information Technology Specialist - Artificial Intelligence Certification, a Pearson credential administered by Certiport. Its public name is IT Specialist - Artificial Intelligence.
The revised objectives list six domains, running from AI Problem Definition to Maintaining and Monitoring AI in Production. No official percentage weights are published for them.
A scaled score of 700 on a 1-1000 scale. Because it is scaled, it does not translate to a fixed percentage of correct answers, and Certiport does not publish pass rates.
Pearson's MindhubPro listing estimates 45-50 questions with a 50-minute maximum. The question count is a variable range, and the time limit excludes administration and tutorials.
Awards earned on or after June 18, 2025 are valid for five years, while earlier awards remain nonexpiring. Recertifying requires a new voucher and passing the current exam.