Which Generative AI Leader domain carries the most weight?

Google Cloud’s gen AI offerings, at about 35% of the exam per the official exam guide.

How many questions are on the Generative AI Leader exam?

50-60 multiple choice questions in 90 minutes, per the official certification page.

Do I need technical experience?

No. Google describes it as business-level knowledge with no hands-on technical experience required, and lists no prerequisites.

What is the passing score?

Google does not publish one on the certification page.

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Google Cloud Generative AI Leader study guide (by exam domain)

This guide restructures the official Generative AI Leader exam guide into a checklist. The exam is 50-60 multiple choice questions in 90 minutes and costs $99 (plus tax where applicable). Google does not publish a passing score on the certification page.

Last checked 2026-10-16 against the official sources listed below.

Domain 1: Fundamentals of gen AI (~30%)

Core concepts: AI, NLP, machine learning, generative AI, foundation models, multimodal foundation models, diffusion models, prompt tuning, prompt engineering, LLMs.
ML approaches (supervised, unsupervised, reinforcement) and the ML lifecycle: data ingestion, preparation, training, deployment, management, plus the Google Cloud tools for each stage.
Choosing a foundation model for a business use case: modality, context window, security, availability and reliability, cost, performance, fine-tuning and customization.
Data: quality and accessibility (completeness, consistency, relevance, availability, cost, format), structured vs unstructured, labeled vs unlabeled.
Layers of the gen AI landscape: infrastructure, models, platforms, agents, applications.
Google foundation models and their strengths: Gemini, Gemma, Imagen, Veo.

Domain 2: Google Cloud’s gen AI offerings (~35%, the largest)

Google Cloud strengths: AI-first approach, enterprise-ready platform, ecosystem, open approach, AI-optimized infrastructure (hypercomputer, TPUs, GPUs, data centers).
Data control (security, privacy, governance) and democratized AI (low-code/no-code, pre-trained models, APIs).
Prebuilt offerings for work: the Gemini app and Gemini Advanced (e.g., Gems), Gemini Enterprise, Gemini for Google Workspace.
Customer experience: Agent Search on Gemini Enterprise Agent Platform, Google Search, Customer Engagement Suite (Conversational Agents, Agent Assist, Conversational Insights, Contact Center as a Service).
Building with AI: Agent Platform (Model Garden, Agent Search, AutoML), RAG offerings, custom agents.
Agent tooling: extensions, functions, data stores, plugins; services such as Cloud Storage, Cloud Run, Cloud Functions and the pre-built AI APIs (Speech-to-Text, Translation, Document AI, Vision, Natural Language and more); when to use Agent Studio vs Google AI Studio.

Domain 3: Techniques to improve gen AI model output (~20%)

Foundation model limitations: data dependency, knowledge cutoff, bias, fairness, hallucinations, edge cases.
Mitigations: grounding, RAG, prompt engineering, fine-tuning, human in the loop; continuous monitoring (versioning, drift monitoring, performance tracking, Feature Store).
Prompting: zero-, one- and few-shot, role prompting, prompt chaining, chain-of-thought, ReAct.
Grounding with first-party, third-party and world data; pre-built RAG with Agent Search, RAG APIs, Grounding with Google Search.
Sampling parameters: token count, temperature, top-p, safety settings, output length.

Domain 4: Business strategies for a successful gen AI solution (~15%)

Types of gen AI solutions, factors that shape needs (business requirements, technical constraints), choosing a solution, integration steps, measuring impact.
Secure AI: security across the ML lifecycle, Google’s Secure AI Framework (SAIF), IAM, Security Command Center, workload monitoring.
Responsible AI: transparency, privacy (anonymization, pseudonymization), data quality, bias and fairness, accountability and explainability.

A free study plan weighted by the exam

Read the official exam guide once end to end and tick off each bullet above.
Spend the most time on Domain 2 (~35%) and Domain 1 (~30%); together they are about two thirds of the exam.
Use the official learning path linked from the certification page.
Product names changed recently: the official page says the exam was updated for branding changes, so learn the names used in the current guide (for example, Agent Platform and Agent Search).
Check whether you qualify for a discounted or free voucher before you pay.

Full exam facts: Google Cloud Generative AI Leader

FAQ

Which Generative AI Leader domain carries the most weight?: Google Cloud’s gen AI offerings, at about 35% of the exam per the official exam guide.
How many questions are on the Generative AI Leader exam?: 50-60 multiple choice questions in 90 minutes, per the official certification page.
Do I need technical experience?: No. Google describes it as business-level knowledge with no hands-on technical experience required, and lists no prerequisites.
What is the passing score?: Google does not publish one on the certification page.

Recommended resources

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Sources

Official exam guide (PDF) (last checked 2026-10-16)
Official certification page (last checked 2026-10-16)

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