2026 AI and Digital Trends in Healthcare | Adobe

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 organizations must take now to turn AI ambition into connected, personalized customer experiences at scale.

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How Healthcare Can Close the Gap Between AI Ambition and Execution

Healthcare organizations 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 organizations: 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 organizations are rapidly 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.

Organizations report “significant” or “moderate” benefits from generative AI in the following areas:

79 percent

Finding information within the organization

74 percent

Volume and speed of content ideation and production

70 percent

Customer experience (e.g., personalization across channels)

Within the next 18 months, organizations anticipate that agentic AI will handle half to all of these customer-facing interactions:
Customer support 84 percent, content recommendations and strategy 68 percent, conversational customer engagement 66 percent

The vision for customer experience (CX) is connected and conversational.

72 percent

say future customer experiences will need to be designed as conversational-first (e.g., AI-powered chat, voice).

61 percent

use agentic or generative AI for journey design and omnichannel activation to achieve personalization at scale.

60 percent

are preparing to optimize content for AI-powered discovery tools.

AI deployment is advancing faster than workforce readiness.

52 percent

say AI is integrated into their day-to-day workflows and tools.

63 percent

say AI is changing roles and workflows faster than employees can adapt.

The content engine is not equipped for AI-scale delivery.

More than half (57%) say their content supply chain is largely linear and resource intensive.

AI governance exists on paper more than in practice.

61 percent

say they have strong AI governance policies in place.

44 percent

say those policies are routinely followed.

Healthcare organizations are less likely than those in other industries to prioritize financial outcomes when measuring AI success.

What organizations say their leadership prioritizes compared to the survey average:

42 percent say leadership prioritizes revenue growth when assessing AI success, vs. 57 percent survey average, while 44 percent say leadership prioritizes operational efficiency and cost savings, vs. 56 percent survey average.
53 percent
More than half struggle to demonstrate measurable returns on their AI investments using CX-related metrics.

Section 3

Building the Foundation for Agentic AI

Agentic AI can only scale as far as the enterprise is prepared to support it. Healthcare organizations 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.

53 percent

say their ability to advance AI initiatives is limited by their current level of data unification and structure.

52 percent

say they have security and privacy controls in place for their AI tools.

40 percent

say their data quality and accessibility are adequate for AI in general.

Healthcare still faces major barriers to implementing agentic AI.

Organizations cite the following challenges:

Data integration and quality issues 66 percent, talent and skills gaps 65 percent, unclear ROI or business case 60 percent

AI-driven insight is only as good as the data underlying it.

52 percent
have a unified customer data foundation that lets them extract insights created by AI agents and conversational interfaces.

To successfully scale agentic AI, organizations must prioritize:

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

The path forward requires a unified foundation built to support AI at scale.

Organizations that unify their data, strengthen their governance frameworks, and invest in skills will turn AI ambition into lasting advantage. Here are the top three action items for healthcare organizations:

View 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 organizations 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 organizations in the healthcare industry. This group makes up 8% of respondents and represents a wide range of organization sizes. View the 2026 AI and Digital Trends report for more on the full research methodology.