2026 Global Health Care Outlook — Deloitte
Health systems are prioritizing revenue, workforce challenges, and care model transformation as AI’s transformative potential remains on the horizon.
— the report’s subtitle
TL;DR
Deloitte’s annual outlook for hospital systems, based on a survey of 180 C-suite executives of large health systems in Australia, Canada, Germany, the Netherlands, the United Kingdom and the United States, fielded August–September 2025. AI is one of five themes; finance, workforce and cybersecurity are the others.
- Gen AI at scale in parts, rarely everywhere. “About 30% of surveyed health systems report operating gen AI at scale in select areas of their organizations … while just 2% have deployed AI across their entire enterprise” (introduction).
- Returns are mostly unmeasured. 51% “either haven’t measured returns or determined that it is too soon to see results”; 31% report “moderate” financial returns; 3% say the ROI has been “significant” (section “AI will likely be important in 2026”).
- Expectations are high anyway. In Figure 3 (n = 178), 56% expect “significant value” from gen AI and agentic AI for operational efficiencies in 2026, and 52% for administrative tasks such as ambient scribes.
- AI is not the top 2026 priority. Only 22% of non-US and 37% of US executives say AI is likely to be a major focus at their facilities in 2026. Workforce is the top concern; more than 90% call productivity a priority.
- Deloitte’s own advice names the pilot trap. “Many organizations pursue pilots or proofs of concept but stumble when trying to scale.”
Key data
| Measure | Figure | Base | Where |
|---|---|---|---|
| Operate gen AI at scale in select areas | ~30% | all respondents, US and non-US alike | introduction |
| Deployed AI across the entire enterprise | 2% | all respondents | introduction |
| ROI not measured or “too soon” | 51% | all respondents | ”AI will likely be important in 2026" |
| "Moderate” financial returns from AI | 31% | all respondents | same |
| ”Significant” ROI from AI | 3% | all respondents | same |
| Gen AI and agentic AI share of 2026 tech budget (expected) | 19% | “surveyed executives” | same |
| AI/Gen AI share of 2026 tech budget | 14% | non-US, n = 120 | Figure 2 |
| AI likely a major focus in 2026 | 22% non-US / 37% US | by region | same section |
| Expect “significant value” from AI: operational efficiencies / admin tasks / clinical decision support / patient experience | 56% / 52% / 42% / 35% | n = 178 | Figure 3 |
| AI and automation of workflows as a savings strategy | 64% | the 56% who see technology as most impactful | Figure 1 |
Method and definitions
- Sample. 180 C-suite executives “from large health systems”, run by Deloitte Global with the Deloitte US Center for Health Solutions through an external survey vendor. Figure 2 gives n = 120 for non-US respondents, so about 60 were US executives (inferred). No per-country counts, no Dutch subsample, no response rate.
- Fieldwork. August and September 2025.
- Definitions. “At scale in select areas” and “across their entire enterprise” are not defined further. Both are the executive’s own judgement. ROI is a self-rated category (significant / moderate / not measured or too soon); no financial threshold is given.
- Sponsor. Deloitte, a consultancy that sells health-care AI and transformation services.
Scope and reliability
- Self-report by executives, small N per country (on average 30), developed markets only. The report says so: “the insights primarily reflect the perspectives of developed health care markets.”
- Two budget figures disagree. The text says executives expect gen AI and agentic AI to take 19% of technology budgets; Figure 2 gives AI/Gen AI 14% for non-US respondents. They may describe different bases; the page does not reconcile them.
- The Netherlands is in the sample but not reported separately. No figure on the page is specific to Dutch health systems.
- A web report, not a PDF. The “Download PDF” button prints the page; there is no longer report behind it.
Dynamic-capabilities reading
digital-sensing/digital-scouting: an annual scan of how hospital executives in six countries read their market, including AI.digital-transforming/improving-digital-maturity: the 30% “at scale in select areas” against 2% “across the entire enterprise” is a maturity gap, measured by self-report.digital-seizing/balancing-digital-portfolios: Deloitte’s advice to “avoid the pilot trap” and start with a “phase 1 approach” instead of a pilot is about scaling up from experiments.
How it connects
- enterprise-ai-adoption — a sector-specific instance of high breadth and low depth: gen AI used at scale in parts of 30% of health systems, enterprise-wide in 2%.
- ai-maturity-measurement-comparison — another self-reported “scale” measure with its own definition, from a vendor-consultancy executive survey.
- micro-productivity-trap — 51% have not measured AI returns; 3% report significant ROI.
- Health-care sources already in the wiki: Keneally (BCG) on health systems and patient-facing AI; Peron (Philips) on imaging AI and clinician trust.
- In this batch: 2026-03-16-mxi-ai-monitor-ziekenhuizen-2026 measures the same breadth-and-depth gap for 52 Dutch hospitals, with its own scale categories. 2026-04-09-qventus-cio-report-2026 reports 4% of US health-system CIOs with “scaled AI with measurable outcomes”. Bain measures how many health-care AI proofs of concept reach production.
- ai-in-health-care: the concept page that sets the health-care sources in this wiki side by side.
What was actually ingested
The full web page as served on 7 November 2026 (published 11 December 2025, last modified 30 August 2026): the body text, the three figures (transcribed from the images), endnotes and acknowledgments. Author bios and contact cards were left out. There is no separate PDF report.
Linked entities and concepts
- Deloitte — publisher (Deloitte Insights).
- enterprise-ai-adoption, micro-productivity-trap — concepts.
- ai-maturity-measurement-comparison — thread.
Dangling (single-source mention, deferred): Deloitte US Center for Health Solutions, Sara Siegel (Deloitte Global Health & Human Services Sector Leader; probably lead author), Minni Särkkä-Hietala, Kavita Rekhraj, Filipe Piteira Ganhão (co-authors in the byline).