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    AI Strategy and Decision Making
    Wharton Executive Education

    AI Strategy and Decision Making

    Wharton Executive Education, Philadelphia
    HomeData & AIWharton Executive EducationAI Strategy and Decision Making
    AnytimeDuration
    onlineFormat
    EnglishLanguage
    Data & AITopic

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    Anytime - Self-Paced
    online · Self-Paced
    Open
    $1,350

    All-inclusive program fee

    About This Program

    AI is transforming how organizations make decisions, serve customers, and compete — but knowing what AI can do is not the same as knowing when and how to use it well. This course helps leaders develop the strategic judgment needed to evaluate where data, analytics, and AI create real value, where they fall short, and why the difference matters. Rather than teaching you to build models or select tools, this course focuses on the strategic decisions AI is meant to support. You will examine how AI reshapes workflows and organizational capabilities and explore topics such as prediction versus judgment, human-machine collaboration, data as a competitive asset, and the limits and risks of analytics-driven initiatives. Through cases and applied frameworks, you will assess when decisions should be automated, augmented, or left to human expertise — and how data availability, bias, explainability, and scale affect the strategic choices you face.

    Why Wharton Executive Education?

    When Fortune 500 boards, sovereign wealth funds, and serial founders want their senior teams sharpened on finance, strategy, or leadership, they repeatedly arrive at the same address in West Philadelphia. Wharton's executive programs are built on the same faculty who define the academic disciplines themselves — not practitioners brought in to translate research, but the researchers writing it.

    Your Profile

    • Strategy and transformation leaders evaluating where AI fits into their organization’s digital strategy
    • Product and platform leaders influencing AI-supported decisions about features, personalization, and automation
    • Operations and general management leaders accountable for performance, risk, and responsible adoption
    • Analytics, data, and technology leaders shaping AI governance, prioritization, and organizational readiness
    • Leaders involved in AI review or governance who need frameworks for evaluating proposals without owning technical implementation

    Benefits

    • Delivered fully online and self-paced, this course features four in-depth modules (approximately two to three hours each). You will move through a blend of short-form video lectures, guided workbook reflections, applied activities, and optional stretch exercises that connect concepts to your own organizational context.
    • You will go beyond concepts and put ideas into practice. Specifically, this course will equip you to:
    • Complete decision-framing exercises, simulations, and reflections that connect AI concepts to real organizational choices Build a running decision journal and toolkit that captures insights, trade-offs, and reusable frameworks across modules Produce a work-ready capstone artifact: either an AI Decision Framing Brief for a specific organizational decision or an AI Decision Support Toolkit you can use across contexts
    • By the end, you will have the judgment and tools to engage credibly in AI-related conversations: asking better questions, surfacing hidden risks, and making more informed decisions about where AI belongs in your organization.

    What You'll Learn

    • Diagnose where data, analytics, and AI can (and cannot) create competitive advantage within an organizational context
    • Design a high-level, practical job aid for AI-supported decision making
    • Evaluate the strategic, organizational, and ethical trade-offs involved in scaling analytics and AI initiatives
    • Reflect on and articulate your role in shaping how analytics, AI, and machine learning are used within your organization
    • Demonstrate a commitment to building AI and digital capabilities responsibly, valuing the short-term and long-term consequences of substituting computation for human expertise
    • Develop a personal approach for continuously evaluating, learning about, and adapting to evolving AI and digital capabilities.

    Frequently Asked Questions

    How to Apply

    1. 1

      Check your eligibility

      Review the entry requirements listed on this page. Most executive programs require 8–15 years of professional experience.

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    3. 3

      Contact the school

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    4. 4

      Prepare your application

      Gather your CV, reference letters, and any required test scores. Many EMBA programs waive standardised tests for senior candidates.

    5. 5

      Submit your application

      Apply directly through Wharton Executive Education's official application portal.

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