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Expert commentary demonstrates that AI-driven time savings do not automatically yield productivity gains in health systems, highlighting the need for structured logic models.
The adoption of technologies rooted in AI is increasingly hailed as a path to greater efficiency in health care. One assumption often underpinning this view is that staff time saved by AI tools can and will be converted into increased productivity or cash savings. This commentary argues that health care organizations need to have explicit, feasible, and adequately resourced plans for converting any saved staff time into improved outcomes for managers, patients, and staff. It also highlights the important role that logic models can play in that planning. By shifting the focus from what AI tools can accomplish to what health care systems can achieve by using them, logic models have the potential to help health care organizations navigate the hype and secure the genuine benefits that AI can bring.
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Shand et al. (2026) studied this question.
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