Innovation in Healthcare

1) Physician Assistants Embrace AI—but Seek More Training

Signal: workforce AI adoptionImpact: productivity & upskilling

A new Wolters Kluwer survey underscores how deeply artificial intelligence has become embedded in the physician assistant workforce. The findings show that 56 % of PAs use AI daily and nearly one in five relies on it extensively, with clinical documentation (61 %) and ambient scribe technologies (48 %) topping the list of use cases【820764529616947†L804-L814】. Yet the profession’s rapid adoption outpaces education: almost nine in ten PAs say they need to learn more about AI and only 32 % report having clear workplace guidelines for safe usage【820764529616947†L810-L823】. These insights highlight the urgent need for structured training and governance to ensure AI enhances care without compromising safety.

2) Included Health’s AI Assistant Puts Clinicians in the Loop

Signal: personalised AI navigationImpact: integrated care & engagement

On December 11 Included Health expanded its platform with an intelligent assistant called Dot. The always‑on tool draws on members’ medical history, claims and benefits data to deliver personalised guidance, processing more than ten billion AI tokens to date【264826159447782†L123-L135】. Unlike generic chatbots, Dot operates on a deep understanding of each member and hands off to human clinicians when a situation requires expert input, providing a clinician‑in‑the‑loop experience【264826159447782†L130-L145】. By harnessing integrated data and expert oversight, Included Health aims to reimagine how people navigate coverage, care and costs【264826159447782†L147-L166】.

3) AI Agent Optimizes Room Assignments and Reduces Wait Times

Signal: operational AIImpact: clinic efficiency & patient experience

Realtime‑location provider Kontakt.io introduced an AI agent on December 9 that dynamically assigns exam rooms for outpatient clinics. Built on the company’s real‑time location system, the Access Agent analyses historical appointment durations and live EMR data to forecast room availability and visit length【407245894474450†L137-L147】. By reducing idle rooms and aligning room assignments with provider readiness, the system can boost clinic efficiency by up to 20 % while shortening patient wait times【407245894474450†L106-L147】. Early pilots suggest the agent helps clinics expand capacity without costly new construction【407245894474450†L145-L161】.

4) AI Agents Aim to Tame the Clinical Trial Data Deluge

Signal: trial data automationImpact: faster drug development

eClinical Solutions unveiled elluminate AI agents, a suite of artificial intelligence tools designed to handle the exploding data volumes in late‑stage drug trials. Phase III trial data has grown sixfold to over 5.9 million data points in 2025【208115662409836†L57-L59】, overwhelming traditional workflows. The new agents combine governed data and explainable intelligence across four pillars—data mapping, data review, risk‑based quality management and study operations—to surface anomalies, draft risk statements and interpret protocols【208115662409836†L43-L83】. By accelerating insights from hours to seconds, eClinical aims to help researchers navigate complex trials and bring therapies to patients sooner.

5) Preparing for 2026: Responsible AI, Cybersecurity and Talent

Signal: strategic foresightImpact: governance & resilience

Ernst & Young’s latest outlook for 2026 warns that while 88 % of health executives trust artificial intelligence, moving beyond pilot projects will require strong guardrails and proactive education for patients and clinicians【808608743248524†L934-L939】. The advisory firm urges health leaders to establish “agentic AI” guidelines, validate outputs and deploy AI to streamline claims adjudication and fraud detection【808608743248524†L936-L944】. The report also highlights other trends shaping the next year: cybersecurity incidents are causing moderate to severe financial impacts at 72 % of health organizations, making cyber resilience a strategic priority【808608743248524†L946-L951】; targeted mergers and acquisitions and offshoring will accelerate; and investments in talent upskilling and regulatory preparedness will be essential【808608743248524†L934-L989】.

6) Beyond the Headlines: Adoption vs. Governance in Healthcare AI

Signal: synthesis & equityImpact: readiness & trust

This week’s announcements illustrate a central tension in digital health: adoption of AI is accelerating, but frameworks for training, governance and equity are lagging. Physician assistants are embracing AI for documentation and scribing, yet nine in ten say they need more education and only a third have clear guidelines【820764529616947†L804-L823】. Startups like Included Health and Kontakt.io are using AI to personalize care and optimize clinic operations【264826159447782†L123-L145】【407245894474450†L137-L147】, while eClinical Solutions is building agentic tools to manage millions of data points in clinical trials【208115662409836†L57-L83】. These innovations promise efficiency and better outcomes, but they also highlight the risk of “shadow AI” and safety lapses if guardrails are absent.

EY’s 2026 health‑sector outlook underscores this governance gap, urging leaders to develop responsible AI strategies, invest in cybersecurity and prepare for new regulatory and workforce realities【808608743248524†L934-L989】. Meanwhile, only 20 % of health‑system executives believe value‑based care models are progressing, even though 77 % plan to increase participation【602142829452304†L207-L210】. These figures suggest that without robust oversight and reimbursement reforms, AI and digital health tools may widen inequities rather than close them. As we look ahead, the challenge for innovators and policymakers is to pair technological breakthroughs with training, transparency and equitable access so that the benefits of AI are shared across all patient populations.