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Merge pull request #53459 from pablorodMS/Module04-evaluate-costs-benefits-ai-powered-business-solution
Module 4 evaluate-costs-benefits-ai-powered-business-solution
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‎learn-pr/wwl/evaluate-costs-benefits-ai-powered-business-solution/1-introduction.yml‎

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### YamlMime:ModuleUnit
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uid: learn.wwl.evaluate-costs-benefits-ai-powered-business-solution.introduction
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title: "Introduction"
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metadata:
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title: "Introduction"
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description: "Learn the essentials of evaluating AI-powered business solutions, balancing costs and benefits for sustainable, value-driven adoption."
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ms.date: 02/13/2026
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author: pabloMS
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ms.author: taeldin
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ms.topic: unit
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durationInMinutes: 3
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content: |
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[!include[](includes/1-introduction.md)]

‎learn-pr/wwl/evaluate-costs-benefits-ai-powered-business-solution/2-roi-criteria-ai-powered-business-solution-including-total-cost-ownership.yml‎

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### YamlMime:ModuleUnit
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uid: learn.wwl.evaluate-costs-benefits-ai-powered-business-solution.roi-criteria-ai-powered-business-solution-including-total-cost-ownership
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title: "Evaluate ROI criteria for AI-powered solutions"
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metadata:
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title: "Evaluate ROI Criteria for AI-Powered Solutions"
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description: "Learn to evaluate ROI criteria, including TCO, for AI-powered solutions. Use structured frameworks and analytics to quantify business value."
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ms.date: 02/13/2026
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author: pabloMS
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ms.author: taeldin
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ms.topic: unit
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durationInMinutes: 6
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content: |
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[!include[](includes/2-roi-criteria-ai-powered-business-solution-including-total-cost-ownership.md)]

‎learn-pr/wwl/evaluate-costs-benefits-ai-powered-business-solution/3-create-roi-analysis-proposed-ai-solution-business-process.yml‎

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### YamlMime:ModuleUnit
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uid: learn.wwl.evaluate-costs-benefits-ai-powered-business-solution.create-roi-analysis-proposed-ai-solution-business-process
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title: "Create ROI analysis for a proposed AI solution"
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metadata:
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title: "Create ROI Analysis for a Proposed AI Solution"
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description: "Learn how to create a structured ROI analysis for an AI solution, balancing benefits against costs to evaluate its impact on a business process."
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ms.date: 02/13/2026
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author: pabloMS
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ms.author: taeldin
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ms.topic: unit
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durationInMinutes: 8
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content: |
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[!include[](includes/3-create-roi-analysis-proposed-ai-solution-business-process.md)]

‎learn-pr/wwl/evaluate-costs-benefits-ai-powered-business-solution/4-analyze-whether-build-buy-extend-ai-components-business-solutions.yml‎

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### YamlMime:ModuleUnit
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uid: learn.wwl.evaluate-costs-benefits-ai-powered-business-solution.analyze-whether-build-buy-extend-ai-components-business-solutions
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title: "Analyze whether to build, buy, or extend AI components"
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metadata:
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title: "Analyze Whether to Build, Buy, or Extend AI Components"
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description: "Learn how to evaluate whether to build, buy, or extend AI components for business solutions using strategic frameworks and cost analysis."
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ms.date: 02/13/2026
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author: pabloMS
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ms.author: taeldin
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ms.topic: unit
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durationInMinutes: 6
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content: |
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[!include[](includes/4-analyze-whether-build-buy-extend-ai-components-business-solutions.md)]

‎learn-pr/wwl/evaluate-costs-benefits-ai-powered-business-solution/5-implement-model-router-intelligently-route-requests-most-suitable-model.yml‎

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### YamlMime:ModuleUnit
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uid: learn.wwl.evaluate-costs-benefits-ai-powered-business-solution.implement-model-router-intelligently-route-requests-most-suitable-model
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title: "Implement a model router to intelligently route requests to the most suitable model"
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metadata:
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title: "Implement a Model Router to Intelligently Route Requests"
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description: "Learn how to design and configure a model router in Azure AI Foundry to optimize cost, latency, accuracy, and reliability across AI workloads."
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ms.date: 02/13/2026
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author: pabloMS
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ms.author: taeldin
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ms.topic: unit
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durationInMinutes: 5
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content: |
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[!include[](includes/5-implement-model-router-intelligently-route-requests-most-suitable-model.md)]

‎learn-pr/wwl/evaluate-costs-benefits-ai-powered-business-solution/6-knowledge-check.yml‎

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### YamlMime:ModuleUnit
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uid: learn.wwl.evaluate-costs-benefits-ai-powered-business-solution.knowledge-check
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title: "Module assessment"
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metadata:
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title: "Knowledge check"
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description: "Knowledge check"
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ms.date: 02/13/2026
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author: pabloMS
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ms.author: taeldin
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ms.topic: unit
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module_assessment: false
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durationInMinutes: 3
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content: "Choose the best response for each of the following questions."
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quiz:
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questions:
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- content: "Which of the following is a financial ROI indicator in AI-powered business solutions?"
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choices:
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- content: "Customer satisfaction score"
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isCorrect: false
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explanation: "Incorrect. Customer satisfaction is considered a strategic or intangible (soft value) indicator, not a direct financial metric."
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- content: "Minutes saved per workflow"
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isCorrect: false
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explanation: "Incorrect. Minutes saved per workflow is a time-based metric, not a direct financial indicator."
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- content: "Money saved per successful agent run"
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isCorrect: true
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explanation: "Correct. Financial ROI measures quantifiable, monetary outcomes such as 'money saved per successful agent run,' which is a direct financial metric."
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- content: "Employee sentiment rating"
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isCorrect: false
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explanation: "Incorrect. Employee sentiment is considered a strategic or intangible (soft value) indicator, not a direct financial metric."
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- content: "Which element must be included to produce a complete ROI analysis for an AI solution?"
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choices:
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- content: "Only financial savings"
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isCorrect: false
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explanation: "Incorrect. A complete ROI analysis requires more than just financial savings; it must also include Total Cost of Ownership (TCO)."
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- content: "Only labor-hours saved"
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isCorrect: false
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explanation: "Incorrect. Labor-hours saved is a measurable benefit but doesn't account for the full ROI analysis, which includes TCO."
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- content: "Both measurable benefits and TCO"
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isCorrect: true
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explanation: "Correct. A complete ROI analysis requires both quantifiable benefits (such as time and cost savings) and a full accounting of Total Cost of Ownership (TCO), ensuring the analysis is balanced and enterprise-ready."
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- content: "Only the number of automated tasks"
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isCorrect: false
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explanation: "Incorrect. The number of automated tasks alone doesn't provide a complete ROI analysis; TCO and measurable benefits are also required."
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- content: "Which scenario most strongly indicates a Build approach for AI components?"
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choices:
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- content: "Standard HR onboarding workflow"
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isCorrect: false
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explanation: "Incorrect. Standard workflows are typically well-supported by commercial tools and do not require a Build approach."
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- content: "Document summarization for internal policies"
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isCorrect: false
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explanation: "Incorrect. Document summarization is a common task that can often be handled by off-the-shelf solutions."
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- content: "Highly specialized decision engine that differentiates the organization competitively"
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isCorrect: true
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explanation: "Correct. The Build approach is best when the AI solution defines competitive advantage, requires deep customization, or supports unique business processes not covered by commercial tools."
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- content: "Simple customer email triage"
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isCorrect: false
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explanation: "Incorrect. Simple tasks like customer email triage are typically well-supported by commercial tools and do not require a Build approach."
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- content: "Which Total Cost of Ownership (TCO) category includes costs for data cleansing, labeling, and monitoring data drift in AI-powered business solutions?"
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choices:
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- content: "Infrastructure Costs"
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isCorrect: false
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explanation: "Incorrect. Infrastructure Costs typically include hardware, cloud services, and other foundational resources, not data preparation."
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- content: "Development and Integration Costs"
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isCorrect: false
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explanation: "Incorrect. Development and Integration Costs focus on creating and integrating AI solutions, not data preparation."
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- content: "Data Quality and Preparation Costs"
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isCorrect: true
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explanation: "Correct. Data Quality and Preparation Costs encompass data collection, cleaning, labeling, structuring, chunking, grounding, indexing, and monitoring."
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- content: "Ongoing Operational Costs"
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isCorrect: false
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explanation: "Incorrect. Ongoing Operational Costs include maintenance and monitoring but do not specifically cover data preparation tasks."

‎learn-pr/wwl/evaluate-costs-benefits-ai-powered-business-solution/7-summary.yml‎

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### YamlMime:ModuleUnit
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uid: learn.wwl.evaluate-costs-benefits-ai-powered-business-solution.summary
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title: "Summary"
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metadata:
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title: "Summary"
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description: "Explore a framework for evaluating AI-powered business solutions, focusing on ROI, TCO, and strategic decisions to ensure measurable value."
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ms.date: 02/13/2026
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author: pabloMS
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ms.author: taeldin
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ms.topic: unit
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durationInMinutes: 3
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content: |
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[!include[](includes/7-summary.md)]

‎learn-pr/wwl/evaluate-costs-benefits-ai-powered-business-solution/includes/1-introduction.md‎

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## Overview
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This module is designed to equip solution architects and business decision-makers with a comprehensive framework for assessing, justifying, and selecting AI-powered business solutions. As AI technologies become increasingly integral to modern enterprises, it is essential to rigorously evaluate both their potential benefits and associated costs to ensure sustainable, value-driven adoption.
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The module comprises three key units, each addressing a critical aspect of the evaluation process:
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### 1. Select ROI Criteria for AI-Powered Business Solutions, Including Total Cost of Ownership (TCO)
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This unit introduces the foundational concepts of Return on Investment (ROI) and Total Cost of Ownership (TCO) in the context of AI solutions. Learners explore how to define ROI criteria that reflect measurable business value, technical feasibility, and long-term sustainability. The unit synthesizes guidance from agent analytics, ROI forecasting frameworks, and cost-driver models, enabling architects to select appropriate criteria that balance financial, strategic, and time-based value against lifetime costs.
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### 2. Create an ROI Analysis for the Proposed AI Solution for a Business Process
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Building on the previous unit, this section provides a structured approach for constructing a complete ROI analysis. Solution architects learn to quantify measurable value such as time savings, cost reductions, and automation gains using tools like Microsoft's agent savings analytics. The unit emphasizes the integration of structured ROI frameworks and the alignment of projected benefits with practical TCO components, ensuring that analyses are robust, data-backed, and suitable for executive decision-making.
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### 3. Analyze Whether to Build, Buy, or Extend AI Components for Business Solutions
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The final unit addresses the strategic decision of whether to build custom AI components, buy prebuilt solutions, or extend existing platforms. Learners engage with a structured decision framework that considers organizational strategy, cost structure, and extensibility models. Through comparative analysis, solution architects will be able to select the optimal approach balancing cost, time-to-value, risk, scalability, and long-term sustainability for each business process.
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Throughout the module, participants apply industry best practices, leverage analytics tools, and engage with real-world scenarios to develop actionable insights. Knowledge checks and reflection questions are provided to reinforce learning and encourage critical evaluation of the concepts presented.
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By the end of this module, learners possess the skills and methodologies necessary to evaluate AI investments holistically ensuring that both the benefits and costs are rigorously considered and aligned with strategic business objectives.

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