A logistics company wants to use a generative Al (gen Al) agent to automatically check real-time inventory levels across its warehouses and adjust delivery schedules. The gen Al agent needs access to internal inventory dat
A. They want the most cost-effective solution. What should the organization do?
O B. Build a custom API instead of using the gen Al agent.
O C. Use pre-built gen Al chatbots for inventory questions.
D. Use Vertex Al Studio to fine-tune a model with sample inventory data.
E. Use Google Cloud databases and Vertex Al for the agent to get live data.
D
A nationwide retail chain plans to retire its aging on premises contact center stack and move to a cloud first model that uses Al throughout customer interactions. The company requires a single enterprise ready foundation that unifies telephony, IVR, conversational virtual agents, and real time
agent assist features while scaling globally as call volumes grow. Which Google Cloud solution best fits this fully managed end to end contact center platform need?
A. Dialogflow CX
B. Google Cloud Contact Center as a Service (CCaaS)
C. Google Voice
D. Vertex Al Agent Builder
B
During an annual strategy briefing at Meadowbrook Supply, the chief executive outlines several intelligent initiatives. She describes a model that forecasts customer churn from past behavior.
She mentions a conversational agent that writes personalized promotional emails. She explains autonomous systems that improve stocking layouts in regional warehouses. She also notes detectors that flag suspicious payment activity. What is the most accurate umbrella term that she should
use to collectively describe these capabilities?
A. Generative Al
O B. Machine Learning
C. Artificial Intelligence
D. Deep Learning
C
What is an example of unsupervised machine learning?
A. Analyzing customer purchase patterns to identify natural groupings.
B. Training a system to recognize product images using labeled categories.
C. Predicting subscription renewal based on past renewal status data.
D. Forecasting sales figures using historical sales and marketing spend.
A
A large company is creating their generative Al (gen Al) solution by using Google Cloud’s offerings. They want to ensure that their mid-level managers contribute to a successful gen Al rollout by following Google-recommended practices. What should the mid-level managers do?
A. Perform continuous testing, measurement, and refinement based on user feedback and real- world performance data.
B. Create a robust data strategy to ensure teams can access high-quality, relevant data that is appropriate for training and fine-tuning gen Al models.
C. Drive gen Al adoption by identifying high-impact, feasible solutions that address specific challenges within their workflows.
D. Secure funding and resources for Al initiatives by demonstrating the potential return on investment to the chief financial officer (CFO).
C
Sundale Electronics launched a generative Al support assistant, and after going live they observe that the assistant often produces fluent responses that fail to address customers’ questions about their newly introduced smart thermostats. The model was trained on a large set of generic support
logs collected over the past six years, and that set contains very little information about the latest devices. Which data quality attribute is most likely deficient and causing these off target replies?
A. Consistency
B. Timeliness
C. Relevance
D. Completeness
C
A company wants to use generative Al to create a chatbot that can answer customer questions about their products and services. They need to ensure that the chatbot only uses information from the company’s official documentation. What should the company do?
A. Use role prompting.
B. Adjust the temperature parameter.
C. Use prompt chaining.
D. Use grounding.
D
A company wants to adopt generative Al and is concerned about vendor lock-in. They want to maintain flexibility in their technology stack. What Google Cloud strength would ease their concerns?
A. Google Cloud’s Al solutions have an open approach that supports customer choice across offerings.
B. Google Cloud’s Al solutions are pre-packaged for easy deployment, eliminating the need for customization and integration efforts.
C. Google Cloud’s strict adherence to proprietary technologies ensures the highest level of security and performance.
D. Google Cloud’s focus on automation aims to replace human jobs with Al systems, potentially leading to significant workforce reductions.
A
A software development team wants to use generative Al (gen Al) to code faster so they can launch their software prototype quicker. What should the team do?
A. Use gen Al to refactor and optimize existing code.
O B. Use gen Al to suggest code snippets and complete functions.
C. Use gen Al to automatically generate comprehensive documentation for their code.
D. Use gen Al to identify potential bugs and security vulnerabilities in their code.
B
A customer success manager at BrightWave Systems uses the Gemini app. They want Gemini to always remember their role as “Customer Success Manager at BrightWave Systems” and to consistently apply the company’s standard account tiers and playbooks for everyday conversations so they
do not need to restate this in every chat. Separately they want a dedicated assistant for preparing quarterly business reviews that is preloaded with their slide templates, a persuasive yet consultative tone, and knowledge of the current marketing initiatives. Which Gemini capabilities should
they use for the persistent general context and for the specialized task assistant?
A. Use Saved Info for the enduring role and defaults, and create a Gem for the QBR focused assistant
O B. Use only Saved Info to handle both the persistent profile and the QBR workflow
O C. Rely on Gems alone for both the ongoing context and the QBR assistant
O D. Use Saved Info to build the QBR assistant, and use a Gem to store the broad role and product context
A
A product support team at Riverbend Electronics is piloting a ReAct style agent in Vertex Al that can plan tasks and call a web search tool hosted at example.com. After the model produces a
“Thought” about the issue and chooses an “Action” such as invoking the search tool with a specific query, what is the very next key step in the ReAct loop?
A. The model writes action details to Cloud Logging as the next control step
B. The model immediately crafts the final user reply without considering tool feedback
C. The model receives an observation that contains the outcome of the tool call and records what it found
D. The model performs on-the-fly fine-tuning of its weights based on its thought
C
A global travel booking platform named VistaVoyage is developing a generative Al system to identify payment fraud across about 45 million reservations each day. The team is concerned that adversaries may make small tweaks to inputs so the model incorrectly treats fraudulent behavior as
legitimate. At what point in the machine learning lifecycle should robust protections against these adversarial tactics be established to preserve security?
A. Limited to the business requirements and initial threat modeling stage
B. Handled mostly with input sanitation and validation in Dataflow pipelines before training or serving
C. It should be continuous with robustness techniques embedded during model training and reinforced by ongoing production monitoring
D. Exclusively when the model is released to production
C
A company is developing a generative Al application to analyze customer feedback collected through online surveys. Stakeholders are concerned about potential privacy risks associated with this data, as the feedback contains personally identifiable information (PII). They need to mitigate
these risks before using the data to train the Al model. What action should the company prioritize?
A. Focusing on collecting only quantitative feedback data in future surveys.
B. Ensuring that the Al model is trained on a large and diverse dataset.
C. Implementing strong access controls to limit which teams can view the raw survey data.
D. Applying data anonymization techniques to remove or obscure sensitive data.
D
A company collects customer feedback through open-ended survey questions where customers can write detailed responses in their own words, such as “The product was easy to use, and the customer support was excellent, but the delivery took longer than expected.” What type of data is this?
A. Unstructured data
B. Structured data
C. Labeled data
D. Quantitative data
A
Summit Dynamics has three groups that plan to use generative Al on Google Cloud. The Innovation Lab requires complete control of the guest operating system and exact NVIDIA driver builds on virtual machines so they can trial cutting edge Al frameworks. The Product Engineering group
wants to write only Python code for a custom model while Google manages the operating system, autoscaling, and infrastructure. The Communications department wants a ready to use assistant that helps them compose emails inside their current Workspace apps with no coding.
Which combination of Google Cloud services correctly aligns to the laaS, PaaS, and SaaS models for these groups?
O A. 1 maps to Vertex Al PaaS, 2 maps to Compute Engine laaS, 3 maps to Gemini for Workspace SaaS
B. 1 maps to Google Kubernetes Engine, 2 maps to Vertex Al PaaS, 3 maps to Gemini for Workspace SaaS
C. 1 maps to Gemini for Workspace SaaS, 2 maps to Vertex Al PaaS, 3 maps to Compute Engine laaS
D. 1 maps to Compute Engine laaS, 2 maps to Vertex Al PaaS, 3 maps to Gemini for Workspace SaaS
D
A finance team wants to use Gemma to help with daily tasks so that the financial analysts can focus on other work. Which business problem can Gemma most efficiently address?
A. The complexity of building and deploying sophisticated internal knowledge bases to answer employees’ finance-related questions with accurate and up-to-date information.
B. The difficulty in analyzing large datasets of financial transactions and market data to identify anomalies and predict future financial performance.
C. The struggle to accurately extract key financial figures and insights from a variety of document formats, such as balance sheets and income statements, for quick reporting.
D. The challenge of efficiently producing high-quality written summaries and initial drafts of financial communications.
D
A creative agency named Northshore Images plans to fine tune an image generation model using Vertex Al, and it needs a single repository to hold about 32 TB of source pictures. The data science group requires extremely durable and elastically scalable storage for unstructured objects that
will feed their Vertex Al training runs. Which Google Cloud service best fits storing large collections of object data such as image files?
A. Vertex Al Model Registry
B. BigQuery
C. Cloud Storage
D. Cloud SQL
C
A nonprofit news analytics lab is building a generative Al platform and wants the freedom to combine open-source models and tooling with managed Google Cloud services. They want to minimize vendor lock-in and benefit from innovations created by the wider Al community. Which
characteristic of Google Cloud’s generative Al strategy would most appeal to this lab?
A. Enterprise security and compliance capabilities
O B. An open ecosystem that supports open-source models, tools, and interoperability
C. Prebuilt industry solutions for common generative Al use cases
D. Custom TPUs tuned for select Google model families
B
An organization with a team of live customer service agents wants to improve agent efficiency and customer satisfaction during support interactions. They are looking for a tool that can provide real-time guidance to agents, suggest helpful information, and streamline the support process
without fully automating customer conversations. Which component of Google’s Customer Engagement Suite should they use?
A. Agent Assist
B. Conversational Agents
C. Conversational Insights
D. Google Cloud Contact Center as a Service
A
A company is developing a generative Al-powered customer support chatbot. They want to ensure the chatbot can answer a wide range of customer questions accurately, even those related to recently updated product information not present in the model’s original training dat
A. What is a key benefit of implementing retrieval-augmented generation (RAG) in this chatbot?
O B. RAG will significantly reduce the computational resources required to run the generative Al model.
O C. RAG will primarily help the chatbot generate more creative and engaging conversational responses.
O D. RAG will enable the chatbot to fine-tune its underlying language model on the fly based on customer interactions.
E. RAG will enable the chatbot to access and utilize external, up-to-date knowledge sources to provide more accurate and relevant answers.
D
A company wants to use an Al agent to automate some tasks. They want everyone to understand the different functions of an Al agent. What is the function of an Al agent in the context of gen Al?
A. To provide the computational resources needed to train and run gen Al models.
B. To store and manage large datasets used for training and running gen Al models.
C. To provide a user-friendly interface for interacting with gen Al models.
D. To analyze situations, use multiple tools, and make informed decisions without requiring constant human input.
D
A generative Al assistant at a mid-size logistics firm is asked to create a multi-city delivery itinerary. It collects initial constraints and preferences, drafts a tentative route, asks for clarifications or queries a tool for external data, updates the plan with the new information, and repeats these steps
until the objective is satisfied or a limit of eight iterations is reached. This recurring cycle of observing context, reasoning internally, deciding on the next step, and acting until a goal or constraint is met is a defining characteristic of which component in an Al agent?
A. The foundation model architecture
B. The agent’s reasoning loop
C. Vertex Al Safety Filters
D. The agent’s data ingestion pipeline
B
A travel app asks users to take a photo of a famous landmark and then returns a written overview with historical notes and nearby attractions. The system’s capability to interpret the picture and produce natural language output reflects what kind of model?
A. An image classification model
B. A multimodal learning model
C. A time series forecasting model
D. A text-only unimodal model
B
A highly regulated financial institution wants to use Gemini as the core decision engine for a loan approval system that will deterministically approve or reject loan applications based on a strict set of predefined criteria. Why is this an inappropriate use case for Gemini?
O A. Gemini cannot integrate with required financial databases.
O B. Gemini is not equipped to handle structured numerical data for financial assessments.
O C. Gemini is designed for flexible content generation and inference, not rigid rule-based decisions.
D. Gemini deployment for this scenario would be too expensive and complex.
C
