Evidence map›Paper›PMID 41166703›Full record

ArticleJMIR AI2025

Balancing Innovation and Control: The European Union AI Act in an Era of Global Uncertainty.

Elena Giovanna Bignami, Michele Russo, Federico Semeraro, Valentina Bellini

Abstract read
In one paragraph

Article in JMIR AI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
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  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Elena Giovanna BignamiAnesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Via Gramsci, 14, Parma, 43121, Italy, 39 0521702111.ORCID http://orcid.org/0000-0001-9985-4126
Michele RussoAnesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Via Gramsci, 14, Parma, 43121, Italy, 39 0521702111.ORCID http://orcid.org/0009-0002-1907-3296
Federico SemeraroDepartment of Anaesthesia, Intensive Care and Prehospital Emergency, Ospedale Maggiore Carlo Alberto Pizzardi, Bologna, Italy.ORCID http://orcid.org/0000-0002-3895-0242
Valentina BelliniAnesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Via Gramsci, 14, Parma, 43121, Italy, 39 0521702111.ORCID http://orcid.org/0000-0001-7993-9026

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unlabelled: The European Union's Artificial Intelligence Act (EU AI Act), adopted in 2024, establishes a landmark regulatory framework for artificial intelligence (AI) systems, with significant implications for health care. The Act classifies medical AI as "high-risk," imposing stringent requirements for transparency, data governance, and human oversight. While these measures aim to safeguard patient safety, they may also hinder innovation, particularly for smaller health care providers and startups. Concurrently, geopolitical instability-marked by rising military expenditures, trade tensions, and supply chain disruptions-threatens health care innovation and access. This paper examines the challenges and opportunities posed by the AI Act in health care within a volatile geopolitical landscape. It evaluates the intersection of Europe's regulatory approach with competing priorities, including technological sovereignty, ethical AI, and equitable health care, while addressing unintended consequences such as reduced innovation and supply chain vulnerabilities. The study employs a comprehensive review of the EU AI Act's provisions, geopolitical trends, and their implications for health care. It analyzes regulatory documents, stakeholder statements, and case studies to assess compliance burdens, innovation barriers, and geopolitical risks. The paper also synthesizes recommendations from multidisciplinary experts to propose actionable solutions. Key findings include: (1) the AI Act's high-risk classification for medical AI could improve patient safety but risks stifling innovation due to compliance costs (eg, €29,277 annually per AI unit) and certification burdens (€16,800-23,000 per unit); (2) geopolitical factors-such as United States-China semiconductor tariffs and EU rearmament-exacerbate supply chain vulnerabilities and divert funding from health care innovation; (3) the dominance of "superstar" firms in AI development may marginalize smaller players, further concentrating innovation in well-resourced organizations; and (4) regulatory sandboxes, AI literacy programs, and international collaboration emerge as viable strategies to balance innovation and compliance. The EU AI Act provides a critical framework for ethical AI in health care, but its success depends on mitigating regulatory burdens and geopolitical risks. Proactive measures-such as multidisciplinary task forces, resilient supply chains, and human-augmented AI systems-are essential to foster innovation while ensuring patient safety. Policymakers, clinicians, and technologists must collaborate to navigate these challenges in an era of global uncertainty.

Indexed as

AI ethicsArtificial Intelligence ethicsEU AI ActEuropean Union Artificial Intelligencegeopoliticshealth care innovationregulatory sandboxessupply chain resiliencetrade tariffs

Identifiers

PMID41166703
PMCPMC12574960

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.