1z0-1145-1 Oracle Fusion AI Agent Studio Foundations Associate - Rel 1 Free Practice Exam Questions (2025 Updated)

Comprehensive and Detailed Explanation:

TheBenefits Agentis the out-of-the-box (OOTB) template designed to address all employee benefits inquiries, including medical, dental, and vision. This agent is preconfigured to surface benefits information, eligibility, coverage details, and more, supporting self-service HR for employees.

Oracle documentation:

“Benefits Agent templates deliver rapid, accurate answers to benefits-related questions, reducing HR workloads and empowering employees with direct access to their own coverage data.”

(Reference: Oracle Fusion AI Agent Studio OOTB Agents Catalog, 2024, p. 22)

Other agents are focused on IT help desk, service requests, or reporting—not benefits.

Practical takeaway:Deploy the Benefits Agent for any employee-facing HR benefits self-service use case.

Comprehensive and Detailed Explanation (Exact Extract from Oracle documentation):

To ensure agents generate customer communications that reflect the company’s specific tone, Oracle Fusion AI Agent Studio enables users to tailor both the topics and the system prompts in agent templates. Creating additional topics (Option A) allows the agent to handle a broader range of customer interaction scenarios, ensuring communication is both contextually relevant and aligned with company standards. Modifying the system prompt (Option D) is critical—this is where users can specify not just instructions, but explicit preferences for language, tone, and manner of response. According to the Oracle Fusion AI Agent Studio documentation:

“System prompts define the agent’s personality, communication style, and response format. By specifying company-preferred tone and language in the system prompt, organizations ensure consistent messaging across all customer touchpoints. Topics, meanwhile, extend the agent’s conversational coverage, enabling it to address organization-specific scenarios and maintain the desired tone in diverse situations.”

(Reference: Oracle Fusion AI Agent Studio Implementation Guide, “Customizing Agent Templates for Branding and Communication,” 2024 release, p. 32-33)

Options B and C would restrict the agent’s abilities or disable essential functions, which is not aligned with the goal.

Comprehensive and Detailed Explanation:

TheCompensation Agentis designed for advanced compensation analysis, allowing managers and HR leaders to review salary histories, assess additional compensation, and benchmark team compensation against market trends—all within a unified conversational interface.

Oracle documentation:

“Compensation Agent templates support dynamic exploration of pay data, comparative analytics, and enable proactive compensation management across the organization.”

(Reference: Oracle Fusion AI Agent Studio OOTB Agents Catalog, 2024, p. 25)

Other agents are focused on employment details, payslip queries, or benefits—none provide comparative compensation analytics.

Practical takeaway:Use Compensation Agent for all salary, pay progression, and market benchmarking needs.

Comprehensive and Detailed Explanation:

Secure and up-to-date data retrieval in Oracle Fusion is best achieved by configuring the agent to access business objects within Fusion itself, where data governance, security policies, and real-time updates are enforced.

From the official documentation:

“Business objects in Fusion Applications are subject to strict security and data freshness guarantees. Agents configured to interact directly with these objects inherit these protections, ensuring all data retrieved is current and appropriately secured.”

(Reference: Oracle Fusion AI Agent Studio Data Security Guide, 2024, p. 28)

Other methods either obscure data, risk data loss, or weaken security.

Practical takeaway:Always utilize native business object access for secure, real-time data.

Comprehensive and Detailed Explanation:

Fusion’s role-based access controls (RBAC) are the definitive method for managing agent access to sensitive information. By configuring RBAC, developers ensure that each agent’s permissions mirror those of the intended users, preventing unauthorized data access or manipulation.

Oracle’s documentation states:

“Role-based access control is enforced at both the user and agent levels, ensuring that data exposure aligns strictly with security policies and user responsibilities within the enterprise.”

(Reference: Oracle Fusion Security Administration Guide, 2024, p. 12-14)

System prompts and folder permissions provide context or content restrictions, not security enforcement at the data level.

Practical takeaway:Always audit and configure RBAC settings when deploying agents for sensitive tasks.

Comprehensive and Detailed Explanation:

Oracle AI Agent Studio is built around a modular framework of agent teams, tools, templates, and topics.

Agent teams: Enable collaborative design, testing, and management of agents.

Tools: Extend functionality—such as data access, communication, or external integration.

Templates: Provide starting points for common business use cases.

Topics: Define the conversational and functional boundaries of each agent.From Oracle’s documentation:

“The architecture is centered on reusable templates, customizable topics, and pluggable tools, all organized and governed by agent teams for enterprise scalability.”

(Reference: Oracle Fusion AI Agent Studio Overview, 2024, p. 7-8)

Options A and B mention unrelated or partial features.

Practical takeaway:Leverage the full modular system for rapid agent deployment and customization.

Comprehensive and Detailed Explanation:

Customization in AI Agent Studio is achieved efficiently through:

(B) Editing thesystem promptto inject specific language, tone, or policy details unique to the organization

(C) Updating or adding newtopicsto ensure the agent can handle questions or cases particular to that company’s benefits structureOracle documentation:

“System prompts and topics are the primary vectors for tailoring OOTB agents to reflect company culture, policy, and procedures—enabling rapid adaptation of prebuilt HR workflows.”

(Reference: Oracle Fusion AI Agent Studio Customization Guide, 2024, p. 38)

Source code editing is not supported; document uploads supplement, but do not tailor, the conversational flow.

Practical takeaway:Focus on prompt and topic customization for rapid, compliant benefits agent deployment.

Comprehensive and Detailed Explanation:

Structured agent testing requires both the ability to manage test cases (Option D) and compare outcomes over time (Option B). Oracle Fusion AI Agent Studio provides robust tools for managing evaluation datasets and for comparing the results of different test runs to assess improvements or regressions in agent behavior.

The documentation states:

“Evaluation test data management is fundamental for consistent agent assessment. Additionally, built-in comparison tools enable users to review performance across multiple versions or configurations, ensuring that any changes made to agents result in measurable improvements.”

(Reference: Oracle AI Agent Studio Evaluation Framework, 2024, p. 24)

Options A and C are not part of the standard testing toolkit.

Practical takeaway:Maintain organized test data and always compare results for continuous quality.

Comprehensive and Detailed Explanation:

The External REST tool allows agents to query third-party logistics platforms in real time using defined REST APIs. This tool is specifically designed for cross-application integration, supporting any external service with a standards-compliant API, and returning data directly into the agent workflow.

Oracle documentation details:

“External REST tools facilitate seamless interaction with external systems, enabling use cases like real-time order tracking, status updates, and supply chain event monitoring without leaving the Oracle Fusion ecosystem.”

(Reference: Oracle Fusion AI Agent Studio Integration Guide, 2024, p. 31)

User Session and Document tools do not enable live external integration; Business Object tool is only for internal Fusion data.

Practical takeaway:Use the External REST tool whenever agents must interact with outside systems.

Comprehensive and Detailed Explanation:

To automate the order-to-cash process in Oracle Fusion AI Agent Studio, the agent must access structured invoice data (via Business Object tools) and send out those invoices to customers (via the Email tool). The Business Object tool allows the agent to interact securely and efficiently with transactional data in Fusion Applications, ensuring all invoice information is accurate and up to date. The Email tool then automates outbound communication, generating and delivering invoice documents to customer email addresses.

Oracle documentation clarifies:

“Combining Business Object tools and the Email tool enables end-to-end automation of transactional processes—from data extraction and transformation to automated customer communications.”

(Reference: Oracle Fusion AI Agent Studio Tools Integration Guide, 2024, p. 59)

Other options either involve irrelevant tools or miss the integration required for this use case.

Practical takeaway:Always pair data access (Business Object) with communication (Email) for end-to-end workflow automation.

Comprehensive and Detailed Explanation:

Evaluation test data in Oracle Fusion AI Agent Studio is primarily used to assess the quality and reliability of agent responses. Users upload test inputs and reference outputs to compare actual agent performance against expected results during offline testing phases.

From the Oracle documentation:

“Evaluation sets allow developers to simulate real-world usage by supplying a battery of inputs and expected outputs. This enables objective measurement of agent performance before deployment and helps identify gaps or errors in agent logic.”

(Reference: Oracle AI Agent Studio Testing Guide, “Offline Evaluation with Test Sets,” 2024, p. 18)

Option A is incorrect—evaluation sets do not fine-tune the LLM, and Option C misrepresents their function.

Practical takeaway:Always use uploaded evaluation sets for objective, reference-based agent testing.