AI-900 · ● Retiring (June 30, 2026) · Entry · Microsoft
Critical notice: This exam retires on June 30, 2026 at 11:59 PM Central Standard Time. The replacement exam is AI-901 (beta launch April 21, 2026). If you already hold AI-900, your certification remains permanently valid. The exam code changes, but the credential does not.
Exam facts
| Field | Value |
|---|---|
| Cost | $99 USD; regional pricing varies |
| Duration | 60 minutes |
| Questions | 40–45 mixed format (multiple choice, multiple response, drag-and-drop) |
| Passing | 700/1000 scaled score |
| Format | Multiple choice, multiple response, drag-and-drop, mixed interactive |
| Delivery | Pearson VUE (test center and OnVUE remote proctoring) |
| Languages | English, Japanese, Chinese (Simplified), French, German, Korean, Portuguese (Brazilian), Spanish |
| Valid | Lifetime (Microsoft fundamentals certs do not expire) |
| Renewal | N/A — fundamentals certifications are valid indefinitely |
| Prerequisites | None; no prior Azure experience required |
| Released | September 2020 |
| Retiring | June 30, 2026 11:59 PM CST |
Vendor source — Microsoft Learn Certification Page ↗
Official exam guide — Exam AI-900: Microsoft Azure AI Fundamentals ↗
Exam study guide — Study Guide for Exam AI-900 ↗
About
The Microsoft Azure AI Fundamentals exam validates foundational understanding of artificial intelligence concepts, Azure AI services, and responsible AI principles. Launched in September 2020, AI-900 has become the entry-level credential for professionals with technical and non-technical backgrounds entering the AI field. It requires no prior data science or software engineering experience and is intended for IT professionals, business analysts, students, and career-changers exploring AI workloads. As of May 2026, Microsoft is retiring AI-900 in favor of the next-generation AI-901, which enters beta April 21, 2026. Candidates have until June 30, 2026 to take the AI-900; after that date, AI-901 becomes the standard entry-level AI credential, though both exams lead to the same foundational certification.
Domain context — Data/AI
Foundational artificial intelligence and machine learning services spanning hyperscale public cloud platforms (Azure, AWS, GCP). This domain covers core ML principles, applied AI services (computer vision, NLP, generative AI), responsible AI frameworks, and cloud-hosted AI platforms.
Read full deep dive — Microsoft Azure + M365 Ecosystem →
Topics covered
The AI-900 exam blueprint covers five domains with equal weight distribution:
-
AI Workloads and Considerations (15–20%) — Understand AI as it applies to common business scenarios; distinguish between machine learning, computer vision, NLP, and generative AI workloads; identify considerations for responsible AI (fairness, transparency, accountability, privacy).
-
Machine Learning on Azure (20–25%) — Describe core machine learning principles (supervised, unsupervised, regression, classification); identify Azure Machine Learning capabilities; understand training, validation, testing concepts; use AutoML for quick model creation.
-
Computer Vision Workloads (15–20%) — Describe computer vision capabilities; identify Azure Computer Vision and Azure Form Recognizer services; understand image classification, object detection, optical character recognition (OCR), and facial recognition use cases.
-
Natural Language Processing Workloads (15–20%) — Describe NLP capabilities; identify Azure Language Service, Azure Translator, and Azure Bot Service; understand sentiment analysis, entity extraction, language translation, and conversational AI.
-
Generative AI Workloads (15–20%) — Describe generative AI and large language models (LLMs); identify Azure OpenAI Service capabilities; understand prompt engineering, retrieval-augmented generation (RAG), and responsible AI safeguards for generative models.
Source: Official Exam Objectives ↗
Common skills at Data/AI · Entry
Shared content for the Data/AI domain at Entry level — not specific to this cert.
- Understand supervised and unsupervised learning paradigms
- Distinguish between classification, regression, and clustering problems
- Identify bias and fairness considerations in machine learning models
- Recognize responsible AI principles (transparency, accountability, privacy)
- Apply basic exploratory data analysis (EDA) to tabular datasets
- Understand why and when to use cloud-hosted AI versus on-premises solutions
Recommended courses at Data/AI · Entry
| Provider | Title | Cost | URL |
|---|---|---|---|
| Microsoft Learn (Official) | AI-900T00: Introduction to AI in Azure | Free | ↗ |
| Microsoft Learn (Official) | Prepare to teach AI-900 Fundamentals (Academic Programs) | Free | ↗ |
| Pluralsight | AI-900: Microsoft Azure AI Fundamentals | $299/year (platform subscription) | ↗ |
| Coursera (Official Partner) | Microsoft Azure AI-900 AI Fundamentals | Free audit; $39+ for certificate | ↗ |
| YouTube (John Savill) | AI-900 Full Study Cram v2 | Free | ↗ |
| Udemy (Various Instructors) | AI-900: Microsoft Azure AI Fundamentals (2026 edition) | $10–$15 (during sales) | ↗ |
Course-selection rule: Microsoft Learn is the canonical free resource and aligns precisely with exam objectives. Pluralsight and Coursera are structured alternatives with scaffolded pacing. John Savill's YouTube series is dense and fast-paced; best for reinforcement after completing official material.
Practice exams
| Provider | Title | Cost | URL |
|---|---|---|---|
| MeasureUp (Microsoft Official Partner) | AI-900 Practice Test | $40–$60 | ↗ |
| MeasureUp (Official Assessment) | AI-900: Microsoft Azure AI Fundamentals Assessment | $40–$60 | ↗ |
| Whizlabs | AI-900: Fundamentals of Artificial Intelligence | $20–$40 | ↗ |
| Udemy (Third-Party) | AI-900 Practice Exam Bundle (2026) | $12–$20 | ↗ |
Books
| Title | Author | Publisher | Year | ISBN | URL |
|---|---|---|---|---|---|
| Azure AI Fundamentals (AI-900) Study Guide: In-Depth Exam Prep and Practice | Tom Taulli | Apress | 2024 | 978-1-4842-9884-5 | ↗ |
| Azure AI Fundamentals: Study Guide and Practice Exam for the Microsoft AI-900 Exam | David Voss | Independent | 2023 | 979-8671153989 | ↗ |
| Microsoft Azure AI Fundamentals Certification Companion | Krunal S. Trivedi | Apress | 2024 | 978-1-4842-9220-1 | ↗ |
| Microsoft Azure AI Fundamentals AI-900 Exam Guide | Aaron Guilmette, Steve Miles | Packt | 2025 | 978-1-8358-8567-3 | ↗ |
| Azure AI Fundamentals (AI-900) Study Guide | Tom Taulli | O'Reilly | 2024 | 978-1-0984-4904-8 | ↗ |
Book rule: All titles reference AI-900 specifically and were published or updated in 2023–2025 to reflect current Azure AI services and generative AI coverage. Tom Taulli's title is most current (2024).
Typical job titles at Data/AI · Entry
Data Analyst · Junior Data Scientist · Business Intelligence Analyst · AI Operations Specialist · Azure AI Specialist · Junior Machine Learning Engineer · Analytics Engineer
(Job titles drawn from current job-board postings that list AI-900 as required or preferred.)
Salary
| Region | Range | Source |
|---|---|---|
| USD | $85,000 – $105,000 (entry); $90,000 – $150,000 (with experience) | Glassdoor ↗ · ZipRecruiter ↗ |
| ZAR | R 511,389 – R 906,249 | ERI SalaryExpert (ZA) ↗ · Jobicy (ZA) ↗ |
| GBP | £55,500 – £80,000 | IT Jobs Watch ↗ · Hays ↗ |
Salary rule: AI-900 as an entry-level cert shows minimal direct salary impact. Professionals with AI-102 (intermediate) see 15–25% higher compensation. AI-900 primarily enables upskilling into higher-value credentials (AI-102, AI-200 series) rather than commanding premium alone. Entry-level roles using AI-900 cluster around $85–$105k USD; growth depends on advancing to AI-102 or domain-specific certs (DP-900 for data engineering, AZ-900 for cloud operations).
Skills validated
Cert-specific — what this exam actually tests, distinct from the shared "Common skills" above.
- Describe AI workloads (machine learning, computer vision, NLP, generative AI)
- Distinguish machine learning types (supervised regression/classification, unsupervised clustering)
- Identify Azure Machine Learning, Azure Cognitive Services, Azure OpenAI Service
- Explain responsible AI principles: fairness, transparency, accountability, privacy
- Use Azure Computer Vision for image analysis and OCR
- Apply Azure Language Service for sentiment analysis, entity recognition, translation
- Understand generative AI with Azure OpenAI (GPT, DALL-E)
- Recognize prompt engineering best practices and RAG architecture patterns
- Describe Azure Bot Service and conversational AI patterns
- Identify Azure Form Recognizer for document intelligence
Related certifications
- Stacks with: AZ-900 (Azure Fundamentals) ↗ · DP-900 (Data Fundamentals) ↗
- Next step: AI-102 (Azure AI Engineer) ↗ (retiring 2026, replaced by AI-200/201 series)
- Successor exam: AI-901 (Azure AI Fundamentals, beta April 2026, enters general availability after June 30, 2026)
- Replaces: None (launched September 2020 as greenfield entry-level cert)
- Equivalents at this level: Google Cloud AI Essentials (GACE) ↗ · AWS Certified Cloud Practitioner with AI focus (CLF-C02) ↗
- Vendor overview: Microsoft Vendor Overview ↗
Sources
- Microsoft Learn: Exam AI-900 Official Page ↗
- Study Guide for Exam AI-900 ↗
- Microsoft Certification: Azure AI Fundamentals ↗
- Course AI-900T00: Introduction to AI in Azure ↗
- MeasureUp AI-900 Practice Test ↗
- Whizlabs AI-900 Practice Exam ↗
- John Savill AI-900 Study Cram (YouTube) ↗
- Coursera: Microsoft Azure AI-900 AI Fundamentals ↗
- Glassdoor: AI Engineer Salary ↗
- ZipRecruiter: AI-900 Certification Jobs ↗
- ERI SalaryExpert: AI Engineer Salary in South Africa ↗
Last verified: 2026-05-01
Parent ecosystem: Microsoft Azure + M365 Ecosystem
Parent domain: Data/AI Domain
Vendor overview: Microsoft Vendor Overview