AI in Healthcare 2025: Moving From Experiments to Real Impact
AI is now embedded in how healthcare operates. According to a new Strategic Intelligence report, the combined AI market across providers, pharma, and medical devices was $11.9B in 2024 and is projected to reach $57.4B by 2029, a ~37% CAGR. The growth is fueled by consulting and support services for admin automation and clinical decision support, hardware like robotics and imaging systems, and platforms/apps reshaping pharma R&D. In short, pilots are giving way to scalable, production use.
Why this matters now
- Budgets are shifting from exploratory projects to measurable outcomes in care quality, throughput, and cost reduction.
- Regulators are clarifying expectations for AI-enabled imaging and software, accelerating adoption where evidence is strong.
- Vendor ecosystems are maturing: services to stand up workflows, hardware that fits clinical environments, and domain-specific AI models.
Where AI is delivering results
Providers
- Administrative automation: prior authorization, coding, denials management, and scheduling optimization.
- Clinical decision support: imaging triage, sepsis alerts, risk stratification, ambient clinical documentation.
- Operations: bed management, staffing forecasts, and supply chain prediction.
Pharmaceuticals
- R&D acceleration: target identification, molecule design, and trial site selection.
- Protocol design and feasibility using real-world data for faster enrollment and reduced dropouts.
- Safety and post-market surveillance with automated signal detection.
Medical Devices
- AI in imaging: detection, segmentation, workflow orchestration, and reporting.
- Robotics and smart systems that help standardize procedures and reduce variability.
- Connected devices generating datasets for continuous model improvement.
Market outlook and scope highlights
- AI adoption is accelerating across sectors with measurable gains in drug discovery and development timelines.
- Regulatory progress is supporting clinical use of AI imaging tools where efficacy and safety are demonstrated.
- Consulting and support services bridge gaps in data readiness, integration, and change management.
Practical next steps for healthcare leaders
- Pick 2-3 use cases with clear ROI and existing workflows (e.g., imaging triage, prior auth, ambient scribe). Define baseline metrics upfront.
- Tighten data governance: PHI handling, model monitoring, bias checks, and audit trails. Assign owners for each domain.
- Demand clinical validation and integration plans from vendors. No integration path, no deal.
- Build an AI procurement playbook: security, privacy, model update policy, indemnities, and exit options.
- Upskill teams to shorten time-to-value. Consider role-based AI training to align clinicians, ops, and IT on safe, effective use. Explore role-based AI training.
Who's moving: companies to watch
Biopharma: AstraZeneca, Bristol Myers Squibb, Johnson & Johnson, Lilly, Novartis, Pfizer, Roche, Sanofi.
Medtech and imaging: GE Healthcare, Illumina, Medtronic, Philips, Siemens Healthineers.
What's inside the Strategic Intelligence report
- Executive Summary and Players
- Value Chain and The Impact of AI on Healthcare
- Case Studies and Sector Scorecards
- Companies, Glossary, and Further Reading
- Thematic Research and Methodology
For full details and the latest market sizing and case studies, visit the report page: Strategic Intelligence: Artificial Intelligence in Healthcare (2025).
Useful regulatory resource
For teams deploying AI-enabled imaging or software as a medical device, review current guidance and cleared products: FDA on AI/ML-enabled medical devices.
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