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Preparing an AI-Enabled Workforce: Results of a Needs Assessment
Susan H Fenton1, Richard Halpin1, Litao Wang1
1The University of Texas Health Science Center at Houston, Houston, Texas, USA.
Studies in Health Technology and Informatics
|May 23, 2026
Summary
Artificial intelligence (AI) adoption is high in academia, but readiness varies. Findings reveal enthusiasm alongside gaps in understanding AI
Area of Science:
- Medical Education
- Artificial Intelligence
- Healthcare Technology
Background:
- Artificial intelligence (AI) and large language models (LLMs) are rapidly advancing.
- These technologies are increasingly impacting the education and healthcare sectors.
- Academic medical centers need to understand their community's preparedness for AI integration.
Purpose of the Study:
- To assess the adoption levels of AI within an academic medical center.
- To evaluate faculty, staff, and student perceptions of AI.
- To identify specific training needs related to AI implementation.
Main Methods:
- An institution-wide survey was distributed to faculty, staff, and students.
- A total of 1,376 responses were collected and analyzed.
- The survey covered AI adoption, perceptions, and training requirements.
Main Results:
- Over 90% of respondents believe AI integration is inevitable.
- One-third of participants reported feeling pressured to adopt new AI technologies.
- Significant variation exists in understanding the legal and ethical implications of AI.
Conclusions:
- The academic medical center shows both enthusiasm for and gaps in readiness regarding AI.
- Findings will inform the development of institutional policies for AI.
- Training priorities will be established to address identified needs and ensure responsible AI adoption.
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