Unlock the future of health care: AI, Data and Human Centered Experience

After visits, patients receive structured monitoring, medication reminders and secure communication for continuous support. The AI ​​permanently monitors health data, alerting clinical teams to potential risks and helping to prevent readmissions. The result is a more personalized, efficient and man centered health experience.

The transformation of the AI ​​begins with the data

Performing this vision requires the health care ecosystem to meet important data challenges. The first challenge is the volume of data: health care produces around 30% of global data, driven by sources such as electronic health files, advanced imaging technologies and portable devices. In addition to the volume, a substantial quantity of this data is isolated in inherited systems. Finally, monitoring compliance with rigorous regulatory requirements, such as Hipaa and GDPR, adds complexity to the path of data integration for artificial intelligence.

Learn pacesetters

There is an emerging group of health care companies that effectively approach data challenges to transform with AI. According to the Enterprise AI maturity index, developed by ServiceNow and Oxford Economics, the average IA maturity score in the health care sector increased from 45 to 34 in 2025. However, around 16% of organizations – designed as packages – make significant progress. These pacesetters consider AI as a transformative resource; More than a quarter has already implemented an agency AI and almost half plan to do so in the coming year.

Demonstrate leadership in the use of data for AI

These health care ptresseurs unlock the value of AI by demonstrating data leadership:

• Adopt a strategy based on the platform. The pacesetters connect modern and inherited platforms to create effective workflows and managed by AI for planning, coding, mapping, invoicing and reimbursement, while retaining the security and integrity of the data.
• It is essential to implement robust governance protocols. AI technologies used in health care are required to comply with certification standards, complete audit and compliance processes and follow confidentiality regulations. Pacesetters implement governance structures to assess risks, improve safety practices and maintain patient confidence.
• Promote transparency in the company. The adoption of the main practices in AI governance consists in creating centralized AI model registers which systematically catalog transparent details concerning intention, property, operational costs and life cycle management. The assessment of the commercial impact during the pilot phases allows leadership to justify improvements in the results of patients and organizational performance resulting from the implementation of the AI.

The future is brilliant

The transformation of successful AI requires sophisticated infrastructure, strong governance protocols and organizational transparency. By adopting a complete approach to IA integration, health systems can improve operational efficiency and provide care that is increasingly personalized, proactive and attentive to the individual needs of patients.

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