In healthcare, patient data is crucial for diagnosis and establishing trust. The rise of digital health systems and AI tools has significantly increased sensitive data collection, exacerbating vulnerabilities. Global data privacy frameworks like GDPR, HIPAA, and CCPA aim to safeguard this data but vary in enforcement and technical maturity, creating fragmented compliance practices. Q3 2025 statistics show that third-party vendors were involved in notable data breaches, underscoring the risks they present.
Dr. Ankur Sharma from Bayer highlights the urgent need for standardized governance and reimbursement models to facilitate AI adoption in healthcare. Currently, AI tools face challenges in transparency and integration due to unclear regulatory frameworks. While predictive AI tools are being assessed by bodies like the FDA, generative AI remains less regulated and faces obstacles in trust and safety.
To foster effective AI use in healthcare, standardized governance and clearly defined reimbursement pathways are essential for wider adoption, ultimately improving care quality and efficiency.
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