KARACHI: As artificial intelligence becomes increasingly relevant to healthcare education, research and professional practice, Liaquat College of Medicine and Dentistry (LCMD) is focusing on a skill that determines how effectively people can use these tools: asking the right questions and providing clear, structured instructions.
The institution's AI Facilitation Cell recently conducted an interactive, hands-on workshop titled “The Art of Prompting: Communicating Effectively with AI”, bringing together nursing students, undergraduate and postgraduate learners, and healthcare professionals to develop practical skills in communicating with artificial intelligence (AI).
Rather than treating AI as a technology that simply generates answers, the workshop explored how users can guide it towards more relevant, structured and useful responses through purposeful instructions, clearly defined expectations and repeated refinement.
The session combined live demonstrations, practical challenges, prompt-rescue activities and real-time AI exercises, allowing participants to experience how differences in the way a question or instruction is framed can influence the quality and relevance of an AI-generated response.
PROMPT ENGINE introduces a structured approach to AI communication
A central feature of the workshop was the introduction of PROMPT ENGINE, an integrated practical framework covering seven essential elements of effective prompting.
The framework was designed to help participants move beyond vague or unstructured instructions and develop a more systematic approach to interacting with AI tools.
Its seven components were presented as follows:
P – Purpose: Establishing what the user wants to achieve through the interaction.
R – Role: Defining the role or perspective the AI should adopt when responding.
O – Orientation: Providing the necessary background, context and direction to guide the response.
M – Method: Specifying the approach, steps or reasoning process expected for the task.
P – Presentation: Defining how the information should be organised and delivered, including its format and level of detail.
T – Testing: Evaluating the response, identifying shortcomings and refining instructions to improve the output.
E – Ethical Boundaries: Recognising the limitations of AI and ensuring that its use respects accuracy, privacy, professional responsibilities and ethical standards.
Together, these elements offered participants a practical structure for communicating their requirements to AI, assessing the responses and improving results through an iterative process.
From academic learning to clinical practice, research
The workshop connected prompting techniques with situations relevant to participants' academic and professional responsibilities.
Through practical exercises, attendees explored applications across academic learning, clinical practice, healthcare research, postgraduate preparation and healthcare administration.
The emphasis was on understanding how structured instructions could make AI-assisted tasks more purposeful, whether users were seeking help with learning material, organising information, preparing academic content or exploring professional workflows.
The prompt-rescue activities and live demonstrations also gave participants an opportunity to identify weaknesses in poorly framed instructions and understand how adding context, defining objectives and specifying the desired output could improve the usefulness of AI-generated responses.
This practical approach was particularly relevant to the diverse audience, bringing together learners at different stages of their education and professionals working across healthcare disciplines.
Responsible AI use remains central to healthcare
Beyond improving the quality of AI-generated responses, the workshop placed particular emphasis on the responsibility that comes with using these technologies in healthcare and education.
Participants were encouraged to critically evaluate AI-generated information, verify factual accuracy and avoid treating automated responses as inherently reliable or authoritative.
This distinction is especially important in healthcare, where inaccurate information or unverified AI-generated content can have consequences beyond an ordinary academic or administrative task.
The workshop reinforced that AI can assist with information processing, learning, research and professional activities, but human judgment and accountability must remain central to its use.
Its guiding message, “AI as a co-pilot, not the decision-maker”, reflected the need for healthcare professionals and learners to retain responsibility for evaluating information and making decisions.
The closing principle — “THINK → TYPE → TEST → REFINE → VERIFY” — summarised the approach promoted throughout the session, encouraging users to think through their requirements, communicate them clearly, test the responses, improve their prompts and verify the information received.
LCMD's expanding focus on AI in healthcare education
The latest workshop builds on LCMD's continuing engagement with artificial intelligence in medical and dental education.
The AI Facilitation Cell has also outlined a broader workshop series for healthcare professionals, following an October 2026 open house that explored AI applications in clinical practice, research and medical and dental education, alongside concerns surrounding patient confidentiality, research integrity and ethical use.
Against this background, the focus on prompting represents another practical dimension of LCMD's efforts to familiarise healthcare learners and professionals with AI tools and their appropriate applications.
As AI becomes increasingly accessible, the ability to formulate effective instructions, recognise limitations and independently verify outputs is becoming an important part of digital literacy in healthcare.
Acknowledgements and facilitation
The AI Facilitation Cell acknowledged the continued encouragement and support of Prof. Dr. Navid Rashid Qureshi in conducting the initiative.
The workshop was directed and facilitated by Dr. Rizwan Hassan, Lead, AI Facilitation Cell, and Dr. Amna Afridi, Co-Lead, AI Facilitation Cell.
Dr. Daniyal Najeeb and Dr. Abdul Karim served as moderators, contributing to the interactive proceedings and participant engagement.
The organisers also appreciated the active participation of nursing students, undergraduate and postgraduate learners, and healthcare professionals, whose enthusiasm and engagement contributed to the workshop.
Through initiatives such as these, LCMD's AI Facilitation Cell is encouraging healthcare learners and professionals to develop the skills needed to engage with emerging technologies more effectively, while keeping critical thinking, ethical awareness and professional accountability at the forefront.
For healthcare professionals and students, the central takeaway is straightforward: getting better results from AI is not simply about using more advanced tools. It also requires knowing how to communicate with them, question their responses and verify what they produce.
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