Previous Drive Resources (AI)
On this page you'll find resources that have previously been included in the Drive Pathway.
April 2026 - AI Opportunities
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The topic of AI and it's use across our health and social care sector can initially seem overwhelming, particularly as there are so many different factors to consider. This paper looks at the potential and future uses of AI within public health and healthcare systems in Scotland, and helpfully addresses some of the key questions that organisations may have: |
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The paper discusses the importance of health and care professionals upskilling in AI so that they can collaborate with technologists, ask the right questions, test assumptions, spot AI biases and advocate for the general public. With this in mind, what could be done across your organisation to support staff to develop essential AI knowledge? |
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| Reflecting on the recommendations set out within the paper, what do you think needs to happen across the sector to enable organisations to fully harness the benefits of AI technologies? |
January 2026 - Purposeful AI
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This article provides practical advice on how to identify the most meaningful AI opportunities by starting with human needs. Link: AI with purpose: Finding meaningful opportunities through a user-centric lens | Digital Leaders |
| Question |
| How do you think decisions should be made within your organisation about which AI opportunities to pursue? |
October 2025 - AI Risks
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It’s important to understand the risks and challenges that come with AI in order to use it in a safe and ethical way. In this podcast, you’ll hear the perspectives of two healthcare professionals on the risks of AI and how to manage these. Link: Digital Health Unplugged: Exploring the risks of GenAI for clinicians |
| Question |
| How can you reassure staff about the risks of AI so that AI technologies are embraced and adopted? |
June 2025 - Leading AI
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This guide offers practical advice on how to lead the implementation of an AI solution. |
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As a leader, think about your role and responsibility when it comes to the implementation of AI.
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