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6.1 The Performance Paradox: Reading the Adoption and Impact Figures

Lecture Video 6.0

Lecture Video 6.1

I. Two Numbers That Are Not Comparable

II. What Each Study Counted

III. The Pilot Trap

IV. Redesign, and the Confound It Carries

V. Efficiency and Growth

VI. Reading Survey Evidence About Impact

6.2 Marketing and the New Funnel: Answer Engines and Agentic Commerce

Lecture Video 6.2

I. What the Search Figures Measure

II. Answer Engine Optimisation, and Its Missing Feedback Loop

III. Generative and Agentic

IV. Is Unified Customer Data a Moat?

V. Agentic Commerce, From Both Sides

VI. Reading Vendor Research

6.3 Finance and Governance: Fraud Detection Under Supervisory Expectation

Lecture Video 6.3

I. Authorised Harm

II. The Regulatory Foundation Has Moved

III. Frameworks and Proposals

IV. Discrimination, Stability, and Adversarial Drift

V. Explanation as a Regulatory Artefact

VI. What a Risk Committee Should Require

6.4 Supply Chain and Operations: Why the Returns Are Demonstrable Here

Lecture Video 6.4

I. Why Operations Pays

II. Demand Sensing

III. What a Reduced Buffer Actually Trades

IV. Simulation and Its Limits

V. The Data Precondition

VI. Reading Vendor Case Studies

6.5 The Jagged Frontier in Knowledge Work

Lecture Video 6.5

I. The Two Tasks

II. Why the Boundary Is Jagged

III. The Persuasion Bomb

IV. Why Neither Collaboration Mode Protects

V. What Actually Protects

VI. Is the Frontier Smoothing?

6.6 The Hybrid Operational Model: What a Public Reversal Teaches

Lecture Video 6.6

I. What the Averages Showed, and What They Hid

II. Deflection as a Target

III. Tiering, and Why the Percentages Are Not Yours

IV. Reversal Costs and Asymmetry

V. Regulatory and Regional Constraints

VI. What to Measure

6.7 Hiring Tools Under Regulation: Scope, Audit, and What Compliance Establishes

Lecture Video 6.7

I. What Is Actually in Scope

II. What the Audit Requires, and What It Does Not

III. The Data Problem

IV. Notice, and the Enforcement Paradox

V. What Actually Prohibits Discrimination

VI. The Wider Picture

6.8 The Shadow AI Reality: Processing Risk, Prevalence, and Governed Access

Lecture Video 6.8

I. Processing, Not Storage

II. The Prompt Is the Asset

III. What the Prevalence Figures Measure

IV. The Breach Premium and What It Establishes

V. Persistent Access and Offboarding

VI. Enablement, and What the Evidence Supports

6.9 Decision Point: Calibrating the Business Case

Lecture Video 6.9

I. Three Drivers of the Gap

II. Two Axes, Not One

III. Where the Returns Concentrate, and Why

IV. Data Readiness as a Gate

V. The Decision Quadrant

VI. Calibrating the Case

Knowledge Check

Knowledge Check: 6.1 The Performance Paradox: Reading the Adoption and Impact Figures

Knowledge Check: III. The Pilot Trap

Knowledge Check: VI. Reading Survey Evidence About Impact

Knowledge Check: III. Generative and Agentic

Knowledge Check: IV. Is Unified Customer Data a Moat?

Knowledge Check: VI. Reading Vendor Research

Knowledge Check: I. Authorised Harm

Knowledge Check: VI. What a Risk Committee Should Require

Knowledge Check: I. Why Operations Pays

Knowledge Check: III. What a Reduced Buffer Actually Trades

Knowledge Check: II. Why the Boundary Is Jagged

Knowledge Check: V. What Actually Protects

Knowledge Check: II. Deflection as a Target

Knowledge Check: VI. What to Measure

Knowledge Check: II. What the Audit Requires, and What It Does Not

Knowledge Check: V. What Actually Prohibits Discrimination

Knowledge Check: II. The Prompt Is the Asset

Knowledge Check: IV. Data Readiness as a Gate

Welcome to "Artificial Intelligence Across Business Functions," a comprehensive course designed to bridge the gap between AI hype and real-world business application. In today's rapidly evolving digital landscape, understanding how artificial intelligence impacts various departments is no longer optional—it is a critical leadership mandate.

Welcome to "Artificial Intelligence Across Business Functions," a comprehensive course designed to bridge the gap between AI hype and real-world business application. In today's rapidly evolving digital landscape, understanding how artificial intelligence impacts various departments is no longer optional—it is a critical leadership mandate. This course dives deep into the practical realities of AI adoption, moving beyond theoretical concepts to explore how AI is reshaping marketing, finance, supply chain, operations, and human resources.

You will explore the "Performance Paradox" to accurately read AI adoption and impact figures, avoiding common pitfalls like the pilot trap. Discover how agentic commerce and answer engines are revolutionizing the marketing funnel, and learn the rigorous governance required for AI-enabled fraud detection in finance. We will unpack why supply chain operations often yield the most demonstrable AI returns through demand sensing and optimized buffers. Furthermore, the course addresses the "jagged frontier" of knowledge work, the complexities of hybrid operational models, and the stringent regulatory landscape surrounding AI hiring tools. Finally, you will learn to navigate the hidden risks of Shadow AI and master the art of calibrating a robust AI business case based on data readiness and strategic value. Whether you are a business leader, strategist, or functional manager, this course equips you with the analytical tools to make informed, high-impact AI decisions across your organization.

Chapter 6: Artificial Intelligence Across Business Functions

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            <p>Artificial intelligence is no longer just a theoretical technology; it is fundamentally reshaping how organizations operate across every major business function. However, the transition from pilot programs to measurable business impact is fraught with complexities, often resulting in a performance paradox where adoption figures outpace actual returns. This course provides a comprehensive examination of how AI integrates into distinct operational areas, moving beyond the hype to analyze real-world applications, regulatory constraints, and strategic trade-offs. By exploring the unique challenges and opportunities within specific domains, leaders can better understand where AI creates genuine value and where it introduces unforeseen risks.</p>

<p>Throughout this exploration, we will dissect the nuanced role of AI in marketing through the lens of answer engines and agentic commerce, and evaluate the shifting regulatory foundations of fraud detection in finance and governance. The curriculum delves into the demonstrable returns of demand sensing in supply chain operations, while also mapping the "jagged frontier" of AI capabilities in knowledge work. Furthermore, we will address critical governance issues, including the compliance realities of AI-driven hiring tools, the growing risks of shadow AI, and the hidden costs of hybrid operational models. Ultimately, this comprehensive analysis culminates in a strategic framework for calibrating your AI business case, ensuring that data readiness and governed access align with your organization's long-term objectives.</p>
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