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Course Orientation and Outcomes

Welcome, Expectations, and How to Use This Course

Defining the Decision Problem Leaders Face with AI

The Simple 4-Step Decision Framework

Question 1: What job is this task trying to get done? (JTBD) 

Question 2: What’s the risk if AI gets it wrong?

Question 3: How predictable is the environment? (Cynefin lens)

Question 4: How much human judgment is required?

Short Example: AI in Formative Assessment (EdTech) — 2 min

Knowledge Checks

Quiz 1: Identify High-Value, Low-Risk Opportunities

Quiz 2: Apply the 4-Step Framework to a Scenario

Implementation and Close

Execution Toolkit and Next Steps

Course Feedback and Commitment to Action Survey

AI Decision Framework for Leaders: Assess, Prioritize, and Apply is a concise, practical course for non-technical managers who need to evaluate AI opportunities with confidence. Instead of hype or heavy theory, you’ll learn a clear four-step framework that helps you decide where AI adds value, what risks to watch, and how to design the right level of human oversight. Across short videos, worksheets, and two quick quizzes, you’ll apply the method to one real process from your team—moving from vague ideas to a concrete pilot plan. You’ll learn when AI thrives (structured, repeatable tasks like drafting, summarizing, and analysis) and when it struggles (emotionally charged, political, or ambiguous work). You will classify risks, gauge predictability using a Cynefin-inspired lens, and decide how much human judgment is truly required. By the end, you will have a value-risk matrix, a readiness score, and a 30-60-90 day plan to test or shelve your idea with clear metrics and stakeholder alignment. This course is built for mid-to-senior leaders in AI-forward organizations seeking fast, responsible, and measurable decisions about AI adoption.

AI Decision Framework for Leaders: Assess, Prioritize, and Apply

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            <p>AI Decision Framework for Leaders: Assess, Prioritize, and Apply equips mid- to senior-level leaders with a clear, practical way to decide where AI creates value, where it introduces risk, and how to deploy it responsibly. The course centers on a simple four-step decision framework you will apply to one real process from your team, moving beyond hype and technical jargon to sound managerial judgment. By the end, you will have clarity on the job the task is meant to accomplish, the risk profile if AI fails, the predictability of the environment, and the level of human judgment required—so you can choose a fit-for-purpose operating model: automate, augment, or avoid.</p>

<p>The orientation sets expectations and shows how to navigate short videos, worksheets, two knowledge checks, and a final survey. You will define a concrete decision problem early on, avoiding common traps such as shiny-object adoption, over-automation, and analysis paralysis. Foundational principles guide every step: start with a business outcome, begin small, design for oversight, and measure continuously. Key terms—task, workflow, risk class, guardrail, ROI, pilot—are simplified for non-technical leaders to ensure shared language across functions.</p>

<p>The core of the course is the 4-step framework. First, clarify the job to be done: AI performs well on drafting, summarizing, or analysis tasks, and poorly where politics, emotion, or motivation dominate. Second, assess risk: high-stakes areas like hiring, performance reviews, and legal or regulatory communications demand human ownership with AI in a supporting role; medium-risk work such as strategy drafting or insights analysis calls for tight oversight; low-risk tasks like note-taking, formatting, or basic content drafts are candidates for acceleration. Third, evaluate predictability using the Cynefin lens: structured environments favor AI; ambiguous, contested contexts require human leadership. Fourth, determine the degree of human judgment needed, especially where values, ethics, nuance, and relationships matter.</p>

<p>To make this actionable, you will see the framework applied to a real scenario from education technology: AI can draft formative feedback while educators review and personalize—a hybrid pattern you can adapt across functions. Two brief quizzes help you identify high-value, low-risk opportunities and practice applying the framework. In the close, you will receive an execution toolkit: templates for a problem statement, value–risk matrix, readiness scorecard, and pilot plan; a stakeholder map spanning legal, security, data, and operations; and a 30-60-90 day plan to scale or sunset. You will also learn how to communicate impact through a simple narrative and a few meaningful metrics, ensuring your organization moves forward with discipline, transparency, and measurable outcomes.</p>
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