If you are preparing for the AWS Certified AI Practitioner exam with material written before May 2026, part of the syllabus moved under you. AWS published version 1.1 of the AIF-C01 exam guide on April 30, 2026, five weeks after version 1.0, and the guide itself says updates show up on the exam about a month after publication. I went through the revision page line by line while writing a set of practice questions, and this is what changed.
The domain weights in version 1.1 are Fundamentals of AI and ML 20 percent, Fundamentals of GenAI 24, Applications of Foundation Models 28, Guidelines for Responsible AI 14, Security, Compliance, and Governance for AI Solutions 14. The exam has 65 questions, 50 of them scored, and you need 700 out of 1,000 to pass. The revision page lists its changes objective by objective.
Seven objectives that did not exist before
These are new lines in version 1.1, not rewordings.
- 1.2.6 When to use traditional ML models versus foundation models, for example because of regulatory concerns, explainability or operational constraints.
- 2.1.4 The token based pricing model and how it affects cost and performance for inference.
- 2.1.5 The role of context engineering in FM applications.
- 2.1.6 Foundational agentic AI concepts. Multi-agent patterns, Model Context Protocol and how it connects agents to external systems, multi-agent communication, memory management, tool usage and workflow orchestration.
- 3.2.5 Prompt versioning and management with Amazon Bedrock Prompt Management.
- 3.4.5 Business alignment metrics for AI applications, such as task completion rate, user satisfaction and cost per interaction.
- 5.1.5 Hallucination detection and grounding, such as RAG grounding, output validation and confidence scoring.
Agentic AI is the big one. It now appears in the basic terms you must define (1.1.1), in the comparison between AI, ML, GenAI and deep learning (1.1.2), in real world applications (1.2.4), in a whole new objective (2.1.6), and in the security objective through AgentCore Identity and Policy in AgentCore (5.1.1).
Services that came in
The revision page lists seven services added to the in-scope list. Amazon Aurora, Amazon Bedrock AgentCore, Kiro, Strands Agents, Amazon Q, Amazon SageMaker JumpStart and AWS Transform. Amazon MemoryDB left the list.
One detail if you read the guide closely. Amazon Q is in that "added" list and in the revision table for objective 1.3.4, but the in-scope services page and the objective 1.3.4 as published today do not mention it. Objective 1.3.4 now gives Amazon Bedrock, Amazon Quick, Kiro and SageMaker AI as examples. I would not spend much time on Amazon Q until the guide settles.
Examples that changed inside existing objectives
Some objectives kept their number but swapped their examples, which is where older question banks quietly go stale.
- Inference types (1.1.3) used to say batch and real-time. It now adds asynchronous and serverless.
- Model metrics (1.3.6) dropped Area Under the Curve and now lists accuracy, precision, recall and F1 score.
- Pipeline services (1.3.4) used to point at SageMaker Data Wrangler, Feature Store and Model Monitor. The examples are now Amazon Bedrock, Amazon Quick, Kiro and SageMaker AI.
- Services to build GenAI apps (2.3.1) no longer cite Bedrock PartyRock or Bedrock Data Automation. The new examples are Bedrock, SageMaker AI, JumpStart, Amazon Quick, Kiro, Strands Agents and Bedrock AgentCore.
- Agents (3.1.6) used to name Amazon Bedrock Agents. It now asks you to define the role of AI agents and their business applications, without naming a product.
- Customization cost (3.1.5) adds model distillation next to pre-training, fine-tuning, in-context learning and RAG.
- FM evaluation metrics (3.4.2) add LLM-as-a-judge next to ROUGE, BLEU and BERTScore.
- Explainability tools (4.2.2) add SageMaker Clarify and Amazon Bedrock Model Evaluations.
- Security considerations (5.1.4) add data leakage prevention, output filtering and validation, audit trails for AI interactions, and toxicity.
How I would study with this
If your course predates May 2026, keep it. Most of the exam is still the same material. Then spend extra time on three things the old courses barely touch. What an agent is and how it uses tools, memory and MCP. How tokens drive cost, and when RAG, fine-tuning or distillation is the cheaper route. And the Bedrock pieces that make answers safer, Guardrails, contextual grounding and Prompt Management.
Sources
- AIF-C01 exam guide,
docs.aws.amazon.com/aws-certification/latest/ai-practitioner-01/ai-practitioner-01.html - Revisions page of the same guide,
aif-01-revisions.html - In-scope services page,
aif-01-in-scope-services.html
All three read on October 5, 2026.
Practice
I put 30 AIF-C01 questions online for free, written against version 1.1, split by the official domain weights, no signup. After each answer you see the sentence from the AWS documentation that backs it, with the link.
30 free AIF-C01 practice questions with sources
They come from a set of 300, four full exams and a drill. It is a PDF on Ko-fi for 12 euros, or the same questions as a timed Udemy practice test course at 12.99 dollars with that link until November 4. If a quote has changed by the time you read this, tell me in the comments and I will fix the question.
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