Week 3: Demystifying AI – Past, Present, and Generative AI

AI in Practice – Adoption and Case Studies

Learning Objectives:
  • Understand the practical challenges and opportunities of adopting AI in organizational settings.
  • Learn from real-world case studies of successful and challenging AI implementations.
  • Identify key success factors for driving AI adoption and integrating it into existing operations.

Chapter 7: Riding the digital-technology wave

This chapter explores how digital technology and AI are no longer just an internal concern for engineers but are now a key business consideration. The availability of powerful, on-demand compute power and platforms has changed the landscape. This has led to the rise of massive open online courses (MOOCs), which offer free or low-cost access to high-quality educational content from top institutions.

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Chapter 8: Case studies in AI adoption

This chapter delves into real-world examples of how organizations are adopting and implementing AI. It highlights that the hype surrounding AI is often at odds with the reality of its implementation, which requires significant changes to internal practices, governance processes, and workforce capabilities. A key finding is that while some government bodies have begun to implement AI, widespread adoption is still in its early stages and remains limited.

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Chapter 9: A responsible approach to AI

This chapter addresses the critical ethical and social issues that arise with the widespread use of AI. It frames these as part of a "digital dilemma" where profound questions about human autonomy and the limits of AI's decision-making power must be confronted; privacy and security concerns from the extensive collection and analysis of personal data ; and the potential for a depersonalized customer experience when AI is used in service delivery.

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Quiz
What does "riding the digital-technology wave" imply for organizations in the context of AI adoption?

Quizzes are short tests or games designed to assess knowledge on a particular topic. They can be educational, entertaining, or both—helping people learn new facts, challenge themselves, and have fun along the way.

Based on the reading's insights, what are common reasons why organizations struggle with AI adoption?

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Name two types of benefits an organization might expect from successful AI adoption, as illustrated by case studies.

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What role does leadership play in driving successful AI implementation, according to the readings?

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Describe a key lesson learned from one of the AI adoption case studies presented in the readings.

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How can organizations overcome resistance to AI adoption from employees?

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What is the significance of "pilot projects" or "quick wins" in the initial stages of AI adoption?

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How do the readings suggest organizations can measure the success of AI adoption beyond just technical metrics?

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What are the challenges of integrating new AI solutions with existing legacy systems?

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What advice do the readings offer for fostering a culture that embraces AI and continuous digital change?

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Activities for Consideration
  • Case Study Analysis: Select one of the case studies from Chapter 8 (or an external one relevant to your industry) and analyze:
    What problem was AI trying to solve?
    What were the key challenges in implementation?
    What were the measurable outcomes or benefits?
    What lessons can you apply to your own organization?
  • AI Opportunity Identification: Based on your understanding of AI's capabilities, identify one specific, tangible problem or opportunity within your department or organization where AI could potentially create significant value. Outline the current state and the desired AI-powered future state.
  • Stakeholder Mapping: For a hypothetical AI project, identify key stakeholders and consider their potential concerns or excitement. How would you communicate the value and implications of the AI solution to each group?
Further Reading
  1. "The Path to AI Adoption" by Deloitte
  2. "Scaling AI in the Enterprise: Best Practices from Pioneers" by BCG
  3. "How to Pilot an AI Project Successfully" by Forbes
  4. "Change Management for AI: A New Imperative" by Gartner