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Wound Care AI Overload: Is it all Hype, or the Future?
The difference today versus a year ago walking the vendor booths at a trade show is striking. Already overwhelming with nicely dressed folks trying to engage you in conversation or to ply you with a delicious coffee drink to spend time in their booth, now clinicians are given whiplash with promises of AI saving their practice. Some vendors are there to “help” others stitch AI into their platform, others say they can handle your dictation, scheduling, AR, you name it. We had a lot of those conversations this week; part of our team just returned from a conference where AI was the topic in almost every conversation. New vendors promising that AI will revolutionize clinical and administrative workflows are popping up like weeds.
We have spent a large part of the last year working out how AI can actually benefit the wound clinicians we work with. We have our own thoughts about this (more on that soon). In the meantime, though, we should take a look at what the data says.
Health care is far from the only area where the promises and pitfalls of AI are not yet clear. A Harvard Business School experiment with 758 Boston Consulting Group consultants found AI users completed tasks 25% faster with 40% higher quality —but only on those tasks AI was actually good at. On tasks outside AI's competence, users performed 19% worse than those working unassisted, because they trusted the machine when they shouldn't have.¹
A nationally representative U.S. survey by researchers at Harvard and the St. Louis Fed estimated that AI saves the average user just 2.2 hours per week—real, but hardly transformative.² And when Upwork surveyed 2,500 workers across the U.S. and U.K., 77% said AI had actually increased their workload, largely from time spent learning new platforms and reviewing AI output.³
Data from Europe reinforces the US pattern. A study of over 12,000 EU firms found AI boosted labor productivity by 4% on average—but only where organizations invested in talent development and process redesign. Those that simply bolted AI onto existing workflows saw negligible gains.⁴ EY's 2025 European AI Barometer exposed a telling gap: 57% of managers believe AI enhanced their team's productivity, while only 35% of the employees actually doing the work agree.⁵
If workers across industries are still struggling to convert AI into consistent productivity gains, wound care clinicians should be skeptical of any vendor claiming a new platform will magically transform their practice. AI's gains are real but conditional—on targeting the right tasks, adequate training, and a willingness to redesign workflows rather than layer technology on top of broken ones.
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¹ Dell'Acqua, F. et al., "Navigating the Jagged Technological Frontier," HBS Working Paper No. 24-013 (Sept. 2023). https://www.hbs.edu/faculty/Pages/item.aspx?num=64700
² Bick, A., Blandin, A. & Deming, D., "The Rapid Adoption of Generative AI," Fed. Reserve Bank of St. Louis Working Paper 2024-027C (rev. Feb. 2025). https://www.stlouisfed.org/on-the-economy/2025/feb/impact-generative-ai-work-productivity
³ Upwork Research Institute, "From Burnout to Balance" (July 2024). https://www.upwork.com/research/ai-enhanced-work-models
⁴ Betz, F. et al., "How AI Is Affecting Productivity and Jobs in Europe," CEPR VoxEU (2025). https://cepr.org/voxeu/columns/how-ai-affecting-productivity-and-jobs-europe ⁵ EY European AI Barometer 2025. https://www.ey.com/en_ch/insights/ai/ey-study-european-ai-barometer-2025
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