2026 AI and Digital Trends in Healthcare
The Path to AI-Powered Customer Experiences for Healthcare
Explore the top industry insights from Adobe’s 2026 AI and Digital Trends research to understand the actions healthcare organisations must take now to turn AI ambition into connected, personalised customer experiences at scale.
How Healthcare Can Close the Gap Between AI Ambition and Execution
Healthcare organisations are entering the next phase of AI adoption, building on early success with generative AI while preparing to expand agentic AI into more customer-facing work. But those ambitions are outpacing the operating model needed to support them. Turning the industry’s AI momentum into enterprise-wide results will require strengthening capabilities across data, governance and workforce readiness.
This overview explores the Adobe 2026 AI and Digital Trends findings across three critical areas for healthcare organisations: extending early AI gains into agentic workflows, breaking down the barriers to scale AI and building the foundation for agentic AI.
Section 1
Extending Early AI Gains into Agentic Workflows
Healthcare is already seeing real returns from generative AI and organisations are quickly expanding their ambitions for agentic AI. The next step is extending those gains into more connected, conversational customer experiences.
Generative AI is delivering measurable value across the business.
Organisations report “significant” or “moderate” benefits from generative AI in the following areas:
Finding information within the organisation
Volume and speed of content ideation and production
Customer experience (e.g., personalisation across channels)
The vision for customer experience (CX) is connected and conversational.
say future customer experiences will need to be designed as conversational-first (e.g., AI-powered chat, voice).
use agentic or generative AI for journey design and omnichannel activation to achieve personalisation at scale.
are preparing to optimise content for AI-powered discovery tools.
Section 2
Breaking Down the Barriers to Scale AI
The healthcare industry’s plans for AI are outpacing the conditions needed to scale and sustain it. The priority now is to strengthen the operational groundwork — workforce readiness, content production, governance and measurement — that scaling successfully depends on.
AI deployment is advancing faster than workforce readiness.
say AI is integrated into their day-to-day workflows and tools.
say AI is changing roles and workflows faster than employees can adapt.
The content engine is not equipped for AI-scale delivery.
AI governance exists on paper more than in practice.
say they have strong AI governance policies in place.
say those policies are routinely followed.
Healthcare organisations are less likely than those in other industries to prioritise financial outcomes when measuring AI success.
What organisations say their leadership prioritises compared to the survey average:
Section 3
Building the Foundation for Agentic AI
Agentic AI can only scale as far as the enterprise is prepared to support it. Healthcare organisations must strengthen the data, systems and infrastructure needed to turn isolated AI initiatives into enterprise-wide impact.
AI initiatives stall when key fundamentals are not in place.
say their ability to advance AI initiatives is limited by their current level of data unification and structure.
say they have security and privacy controls in place for their AI tools.
say their data quality and accessibility are adequate for AI in general.
Healthcare still faces major barriers to implementing agentic AI.
Organisations cite the following challenges:
AI-driven insight is only as good as the data underlying it.
To successfully scale agentic AI, organisations must prioritise:
Clear rules and processes for managing data
Tools for connecting different systems or software
Extra protections for customer data privacy
Section 4
The Bottom Line for Healthcare
Invest in a data and content foundation built to support agentic AI.
Unified data and AI-ready content operations are what turn early wins from generative AI into fully connected agentic experiences. Without them, AI initiatives will remain fragmented rather than enterprise-wide capabilities.
Create governance protocols for compliant AI at scale.
Most healthcare organisations have AI governance policies in place, but far fewer follow those policies consistently. Routine oversight will enable organisations to keep agentic AI accountable in a heavily regulated industry.
Establish a clear framework for evaluating AI’s ROI.
Organisations must hold AI to measurable business and customer outcomes. Those that fail to do so will struggle to translate investment into demonstrable returns.
View more insights from the 2026 AI and Digital Trends research.
Learn more | Learn more insights from the 2026 AI and Digital Trends research
Appendix
Research Methodology
For Adobe’s 16th annual AI and Digital Trends research, Oxford Economics, in partnership with Adobe, conducted global surveys of 3,000 executives and practitioners and 4,000 customers to better understand how organisations are leveraging AI to capture customer interest, build brand loyalty and augment customer experience (CX) workflows — and how customers are responding to these changes. The surveys were fielded online and via computer-assisted telephonic interviewing (CATI) from October through November 2025. “Healthcare” refers to a global set of executives and practitioners from organisations in the healthcare industry. This group makes up 8% of respondents and represents a wide range of organisation sizes. View the 2026 AI and Digital Trends report for more on the full research methodology.
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