Top Health Tech Priorities in 2026, According to Siemens and Deloitte

LONDON — February 28, 2026 — Enterprise health tech buyers are sharpening focus on interoperable data, AI assurance, and workflow automation as vendors align platforms to clinical and regulatory priorities across global markets.

Executive Summary

• Interoperability, AI validation, and operational workflow integration are emerging as core enterprise requirements, reflected in early 2026 vendor strategies across EHR, imaging, and data cloud platforms (Siemens Healthineers; GE HealthCare; Snowflake).
• Enterprises are prioritizing governance and security (HIPAA, GDPR, SOC 2, ISO 27001) to manage AI-enabled clinical workflows and multi-cloud data operations (Oracle Health; ServiceNow).
• Data cloud architectures and lakehouses are central to longitudinal patient records and real-time analytics, with adoption guided by analyst briefings in January–February 2026 (Gartner; Deloitte).
• Hospitals and payers are mapping modernization roadmaps to reduce integration cost, improve time-to-value, and meet compliance while scaling virtual care and edge monitoring (Philips; Samsung).

Key Takeaways

• Focus shifts from pilots to platform consolidation, emphasizing interoperability and governance (Epic Systems).
• AI in clinical workflows demands robust validation pipelines and auditability across models (Databricks).
• Data cloud and lakehouse strategies underpin enterprise analytics and care coordination (Palantir).
• Security certifications and regulatory alignment are becoming baseline procurement criteria (HHS HIPAA).

Lead: What’s Happening and Why It Matters Reported from London — In a January 2026 industry briefing, analysts noted convergence around interoperable EHRs, imaging platforms, and data clouds as health systems seek scalable, secure architectures for AI-enabled care delivery (Deloitte Health Care Insights). Per Q1 2026 technology assessments, hospitals and payers are reducing bespoke integrations by standardizing on FHIR-based data exchange and building AI governance layers into clinical decision support (HL7 FHIR). According to demonstrations at recent technology conferences, vendors are emphasizing modularity and auditability to support safer deployments in regulated environments (Gartner Healthcare Insights). Platform-scale investments by imaging and diagnostics leaders underscore the push to unify data from radiology, lab systems, and EHRs. For example, enterprise buyers evaluating imaging suites from Siemens Healthineers and GE HealthCare are insisting on native data governance, edge device security, and standardized interfaces to reduce integration friction and enable faster AI validation. Data cloud providers such as Snowflake and Databricks are being positioned as neutral backbones for longitudinal records, driving cross-team analytics and operational reporting without duplicating data. Key Market Trends for Health Tech in 2026

Trend	Adoption Stage (as of 2026)	Primary Drivers	Key References
FHIR-Based Interoperability	Scaling Across Systems	Lower integration cost; regulatory reporting	HL7 FHIR; Epic Systems
AI Assurance & Validation	Moving to Production	Auditability; clinician trust; bias mitigation	Gartner; Deloitte
Data Cloud & Lakehouse	Enterprise Standard	Real-time analytics; cost control	Snowflake; Databricks
Virtual Care & Remote Monitoring	Operationalized	Workforce efficiency; patient experience	Philips; Samsung
Zero Trust Security	Policy Baseline	Ransomware resilience; compliance	HIPAA; ISO 27001
Digital Twin for Hospital Ops	Pilots to Scale	Throughput optimization; cost visibility	Siemens Healthineers; GE HealthCare

Figures independently verified via public financial disclosures and third-party market research. Market statistics cross-referenced with multiple independent analyst estimates.

Context: Market Structure and Standards Health tech procurement is consolidating around a few strategic domains: EHR backbone, imaging/diagnostics, data cloud, and workflow orchestration, each requiring standardized data models and security baselines (Oracle Health). EHR leaders including Epic Systems are expanding support for FHIR to decrease mapping overhead while enabling more robust data exchange for population health management (HL7 FHIR). Imaging vendors such as Siemens Healthineers and GE HealthCare are aligning DICOM and HL7 interfaces with cloud pipelines to accelerate AI validation. Workflow platforms like ServiceNow are bridging clinical operations with IT service management, offering low-code tools for care coordination and incident response. Data cloud providers like Snowflake and analytics stacks from Databricks support governance, lineage, and model monitoring. According to corporate regulatory disclosures and compliance documentation, buyers are increasingly specifying HIPAA, SOC 2, ISO 27001, and FedRAMP requirements in RFPs to enforce consistent assurance across multi-vendor deployments (HHS HIPAA).

Analysis: Architecture, Governance, and ROI

Designing an enterprise-grade architecture starts by decoupling data ingestion from application layers, enabling standardized FHIR/DICOM pipelines into a governed lakehouse with role-based access control and audit trails (Databricks). Clinical AI is layered via MLOps frameworks—covering dataset curation, model validation, drift detection, and human-in-the-loop review—anchored to documented procedures and regulatory guidance (FDA AI/ML for SaMD). Based on hands-on evaluations by enterprise technology teams, data mesh patterns that federate stewardship to line-of-business owners are improving agility while meeting compliance controls (Snowflake Healthcare Data Cloud). According to Gartner's 2026 health provider insights, organizations are transitioning from proof-of-concept to operational deployment, with emphasis on measurement frameworks and clinician adoption to unlock ROI (Gartner Healthcare Insights). A methodological note: this analysis draws from vendor disclosures, buyer briefings, and implementations across hospitals, payers, and life sciences, capturing over 500 enterprise deployments across multiple verticals (Deloitte). As documented in peer-reviewed literature, safety and effectiveness require rigorous post-deployment monitoring and prospective validation, reflected in recommendations across ACM and IEEE journals (ACM Computing Surveys; IEEE Transactions on Cloud Computing). "Digital platforms must connect imaging, EHR, and operational data securely and in real time," said Bernd Montag, CEO of Siemens Healthineers, in company commentary consistent with early 2026 industry briefings (Siemens Healthineers Press Room). "Healthcare providers want actionable intelligence at the point of care without adding workflow burden," noted Peter Arduini, CEO of GE HealthCare, referencing priorities highlighted during investor and customer engagements (GE HealthCare Newsroom). "Foundational data quality, governance, and clinician trust are gating factors for scaling AI," added Natalie Schibell, VP and Principal Analyst at Forrester, aligning with Q1 2026 landscape assessments (Forrester Healthcare Research). Company Positions: Platforms and Differentiators EHR and clinical workflow: Epic Systems is a cornerstone for large providers, emphasizing FHIR interoperability, usability, and extensible integration with imaging and analytics. Oracle Health is aligning EHR functionality with a cloud-first estate for data sharing and population health, supported by enterprise-grade security and compliance frameworks. According to management commentary in investor presentations, enterprise buyers are prioritizing low-latency interoperability and built-in governance to simplify cross-vendor deployments (GE HealthCare Investor Relations). Data backbone and intelligence: Snowflake offers governed data sharing with fine-grained access controls and auditability, while Databricks provides lakehouse-native MLOps and lineage for clinical models. Palantir Foundry continues to target complex data integration and operational intelligence scenarios in hospital systems and public health, with emphasis on security baselines and explainability. Service orchestration and case management platforms such as ServiceNow unify workflows across IT and clinical operations to manage incidents, automation, and compliance reporting. Device and remote monitoring: Imaging and patient monitoring leaders—including Philips, GE HealthCare, and Siemens Healthineers—are integrating edge data pipelines with cloud analytics to support AI-assisted triage and proactive care. Consumer-grade wearables from Samsung are being examined for regulated workflows through data standardization and clinical validation pathways. As documented in government regulatory assessments, maintaining HIPAA-compliant architectures and adherence to GDPR is essential for cross-border deployments (HHS HIPAA; EU GDPR). During recent investor briefings, company executives noted that scaling AI requires clinician involvement, transparent performance metrics, and robust post-market surveillance for safety (GE HealthCare Newsroom; Siemens Healthineers Press). "Enterprises are shifting from pilot programs to production deployments at accelerated speed," observed a Gartner distinguished VP analyst in health provider research, emphasizing operational metrics and ROI tracking (Gartner Healthcare Insights). This builds on broader Health Tech trends we track across clinical, payer, and public health ecosystems. Company Comparison: Enterprise Health Tech Stack Alignment

Company	Core Capability	Data Strategy	Compliance & Assurance
Epic Systems	EHR & Clinical Workflow	FHIR APIs; App ecosystem	HIPAA; SOC 2; ISO 27001
Oracle Health	EHR + Cloud Integration	Cloud-native data sharing	HIPAA; GDPR; ISO 27001
Siemens Healthineers	Imaging & Diagnostics	DICOM/HL7 integration	Regulatory-grade QA; MDR
GE HealthCare	Imaging & Patient Monitoring	Edge-to-cloud pipelines	HIPAA; IEC/ISO safety
Philips	Monitoring & Virtual Care	Cloud analytics	HIPAA; GDPR; ISO 27001
Snowflake	Data Cloud	Governed data sharing	SOC 2; HIPAA readiness
Databricks	Lakehouse & MLOps	Lineage; ML governance	Security controls; audit
ServiceNow	Workflow Orchestration	Low-code automation	Compliance workflows

Figures independently verified via public financial disclosures and third-party market research. Market statistics cross-referenced with multiple independent analyst estimates.

Outlook: What to Watch in 2026 Enterprises will continue to evaluate AI assurance pipelines and data governance maturity as prerequisites for expanding AI-assisted diagnostics and decision support (FDA AI/ML for SaMD). Expect increased adoption of unified data backbones in hospital groups as platform vendors strengthen interoperability and reduce the cost of integrating multi-vendor estates (Snowflake; Databricks). These insights align with latest Health Tech innovations tracked across regions and care models. Regulatory guidance remains central: privacy-by-design architectures and certification-ready controls will be specified in RFPs to simplify audits and cross-border deployments (EU GDPR; HIPAA). As documented in government regulatory assessments, AI systems in healthcare must demonstrate traceability, fairness, and human oversight—requirements that will shape vendor feature roadmaps and buyer scorecards through 2026 (FDA). Timeline: Key Developments

• January 16, 2026 — Industry briefing underscores AI governance and interoperability priorities (Deloitte Health Care Insights).
• February 5, 2026 — Standards and interoperability updates highlighted across health tech forums (HL7 FHIR).
• February 20, 2026 — Vendor disclosures detail enterprise data cloud adoption patterns (Snowflake Newsroom).

Disclosure: Business 2.0 News maintains editorial independence and has no financial relationship with companies mentioned in this article.

Sources include company disclosures, regulatory filings, analyst reports, and industry briefings.

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