Is AI Adoption Outpacing Infrastructure? Part 2
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By
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Helen Bristow
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September 25, 2026
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10 min
Clinical Report: Is AI Adoption Outpacing Infrastructure? Part 2
Overview
The discussion highlights the need for robust digital infrastructure in pathology labs to support AI-only biomarker tests. Experts emphasize that data quality is a critical bottleneck for AI deployment.
Background
The integration of AI in pathology is becoming increasingly vital as AI-only biomarkers enter the market. However, concerns about data quality and the need for scalable systems have been raised.
Data Highlights
No numerical data or trial data were provided in the source material.
Key Findings
- AI-only biomarkers could become a clinical necessity, accelerating the adoption of digital pathology.
- Data quality, rather than algorithm quality, is identified as a significant bottleneck for AI deployment.
- Artifacts and errors during digitization can adversely affect algorithm performance and pathologist interpretation.
- Variability in laboratory processes can lead to incorrect treatment decisions, highlighting the need for standardized practices.
- Larger, diverse datasets are essential for improving algorithm performance across different environments.
- Transparency in AI algorithm training data is crucial for laboratories before clinical implementation.
Clinical Implications
Pathology labs must focus on data quality and standardization to ensure reliable AI deployment.
Conclusion
The integration of AI in pathology requires efforts to enhance data quality and infrastructure.
Related Resources & Content
- the pathologist, The Pathologist, 2026 -- Is AI Adoption Outpacing Lab Infrastructure? Part 1
- contact lens spectrum, Contact Lens Spectrum, 2025 -- AI IN PRACTICE
- Kaiser Family Foundation (KFF), KFF, 2026 -- The Growing Use of Artificial Intelligence in Health Care and Implications for Disparities
- Journal of Medical Internet Research (JMIR), JMIR, 2026 -- Backcasting the Trust Gap: A Strategic Road Map for Clinician Adoption of AI Diagnostics by 2040
- ESMO basic requirements for AI-based biomarkers in oncology (EBAI) - ScienceDirect, ScienceDirect, 2026 -- ESMO basic requirements for AI-based biomarkers in oncology (EBAI)
- Artificial intelligence in histopathology and cytopathology: an umbrella review of systematic reviews and meta-analyses | Surgical and Experimental Pathology | Springer Nature, Springer Nature, 2026 -- Artificial intelligence in histopathology and cytopathology: an umbrella review of systematic reviews and meta-analyses
- Guidance for laboratory implementation, governance and continuous assurance of artificial intelligence in histopathology | Virchows Archiv | Springer Nature, Springer Nature, 2026 -- Guidance for laboratory implementation, governance and continuous assurance of artificial intelligence in histopathology
- ESMO basic requirements for AI-based biomarkers in oncology (EBAI) - ScienceDirect
- Artificial intelligence in histopathology and cytopathology: an umbrella review of systematic reviews and meta-analyses | Surgical and Experimental Pathology | Springer Nature Link
- Guidance for laboratory implementation, governance and continuous assurance of artificial intelligence in histopathology | Virchows Archiv | Springer Nature Link
Based on findings from:
Is AI Adoption Outpacing Infrastructure? Part 2
Helen Bristow. The Pathologist, 2026.
https://www.thepathologist.com/issues/2026/articles/september/is-ai-adoption-outpacing-infrastructure-part-2/
This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.
