1.5 Business Considerations - AAIA Domain 1 - Part A - AI Models, Considerations and Requirements скачать в хорошем качестве

1.5 Business Considerations - AAIA Domain 1 - Part A - AI Models, Considerations and Requirements

00:00 1.5 Business Considerations - AAIA Domain 1 - Part A - AI Models, Considerations and Requirements 00:03 Bridging Technology and Business Strategy Focus: AI Business Considerations. Objective: Bridge the gap between code and business value. Key Elements: Costs. Risks. Strategy. 00:20 The Big Picture: Leverage established change management processes. Do not treat AI as an alien solution. Crucial Distinction: Address unique operational and risk perspectives. 00:42 The Blueprint: Business Use Cases and Scope Prerequisite: No spending without a documented business case. The Risk: Without documentation, implementation fails. Discovery Methods: IT Steering Committees and employee efficiency feedback. 01:06 Mandatory Inclusion (5 Items): Problem: What needs solving? Solution: How AI fixes it. Financials: Cost-benefit analysis and ROI. Risk: Identified dangers and mitigation plans. Execution: Detailed implementation plan. 01:51 Assessing Maturity: The Gartner Hype Cycle Concept: Graphical representation of maturity vs. expectations. The 5 Phases: Innovation Trigger: The launch. Peak of Inflated Expectations: Unrealistic hype. Trough of Disillusionment: Reality hits. Slope of Enlightenment: Understanding utility. Plateau of Productivity: Stability. Auditor Insight: Peak Phase: High variability and risk. Plateau/Cloud Services: Known use cases; lower risk. Warning: New concepts bring high expectations but unclear paths. 03:17 Conducting Cost-Benefit Analysis The Cost Buckets: Implementation: Development, licensing, training. Operational: Maintenance, energy consumption, salaries. Risk & Compliance: Privacy protection, reputation management. The Benefits: Efficiency: Automating repetitive tasks. Decision Making: Data-driven insights. Cost Reduction: Lowering labor and error-related expenses. 04:17 Analyzing Return on Investment (ROI) Market Data (Google Survey): 74%: Organizations seeing ROI. 84%: Production reached within 6 months. 86%: Revenue growth estimated at ≥6%. The Catch: Early financial benefits may be invisible. Initial ROI suppressed by upfront costs/ramp-up. Strategy: Manage expectations; look beyond financials (Employee satisfaction, Customer Experience). 05:09 Hosting Strategy: Internal vs. Cloud Decision: "Build vs. Buy." 05:25 Internal Hosting (On-Premises): Pros: Control, customization, data security mastery. Cons: High infrastructure/power costs, specialized hiring, poor scalability. 05:44 Cloud Hosting: Pros: Scalability, low overhead, low upfront costs. Cons: Infrastructure opacity, vendor lock-in, data sovereignty risks. 06:15 Vendor Management and Oversight Requirement: Mandatory vetting during onboarding. Assessment Factors: Alignment of AI strategies/values. Ethical adherence (Transparency/Explainability). Data security and privacy standards. Lifecycle Management: Periodic reviews of Service Level Agreements (SLAs). Reviewers must comprehend the organization's AI vision. 07:01 Shared Responsibility Models Context: Off-the-shelf solutions (Fast implementation, high risk). Key Risks: Accountability: Undefined maintenance roles. Ethics: Bias liability. Security: New attack vectors via data sharing. The Golden Rule: You cannot outsource accountability. 07:45 Microsoft Shared Responsibility Model (The "Layer Cake"): Layers: AI Platform (Bottom) → AI Application → AI Usage (Top). Customer Retention: Data Governance, Device Management, and Training are always the client's job. 08:32 Summary and Next Steps Session Recap: Business Case & Hype Cycle. Cost-Benefit & ROI. Hosting & Vendor Management. Shared Responsibility. 08:45 Immediate Action: Post questions/feedback in comments. Task: Complete Chapter MCQs at Roocloud.com.