1.3 Management Awareness and Strategic Alignment for AI Integration
Explore what managers and institutional leaders need to consider before integrating AI into teaching, learning, or institutional operations. This unit examines how readiness, governance, policy alignment, data quality, procurement, and staff capacity shape successful AI adoption—ensuring that implementation supports institutional strategy and academic values rather than becoming a purely technical decision.
👉 Start with the video for a quick overview.
👉 Now, read the document to explore the topic in more depth.
Download PDF👉 Finish with the task to reflect and apply what you’ve learned.
Imagine your institution is considering adopting an AI tool that supports teaching or student services (for example, an AI assistant for student queries, an analytics dashboard, or a tool that supports feedback on writing). Identify two readiness factors that should be assessed before moving forward. You might consider data quality and privacy, staff skills and workload, governance structures, accessibility, procurement requirements, or clarity about who is accountable for outcomes. For each factor, briefly explain what “good readiness” would look like in your context and what could go wrong if the factor is ignored. Then propose one practical step your institution could take in the next three months to improve readiness. This step should be realistic and within the influence of managers, such as setting up a review group, running a pilot with clear success criteria, providing training, defining a policy, or creating a feedback channel for students and staff. (Write up to 200–300 words.)
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