Nearly 67% of healthcare practice staff spend at least an hour each day entering data manually, according to a survey of 285 employees across dental, specialty medical, optometry, and veterinary practices. The findings highlight a growing gap between AI adoption in clinical settings and the persistent administrative burden that still slows daily operations.
Sixty percent of practice owners, office managers, and front-desk staff cited HIPAA and data privacy as leading AI risks, per the poll conducted by Weave, which builds AI-enabled communication tools for medical practices. The survey also found that 80% of respondents said duplicate data entry affects their workflow, with 47% describing the impact as moderate or significant.
Manual entry persists across disconnected systems
Nearly one-third of staff spend at least two hours a day entering data manually. Seven in 10 practices said they do not operate an integrated software stack, forcing employees to re-enter the same patient information across multiple platforms.
Staffing shortages amplify the pressure. Nearly two-thirds of practices experienced shortages in the previous 12 months, and 48% currently face them. Almost a quarter said shortages forced them to reduce patient or appointment volume.
Nearly half of respondents want to automate appointment scheduling and confirmations. Insurance verification followed at 46%, patient intake and forms at 42%, and billing and payment reminders at 41%.
"Practitioners can name exactly what's slowing them down, and it isn't a mystery - it's manual work moving between systems that don't talk to each other," said Marcus Bertilson, COO and head of product at Weave, in a statement.
Privacy concerns slow AI adoption
Only 41% of practices have adopted some AI workflows, while another 33% said they have considered AI tools but have not committed to implementation. Among non-adopters, 51% worry AI will produce low-quality work, and 35% cite regulatory uncertainty.
Many practices also lack formal AI governance. Fifty-eight percent have no governance structure in place, and 48% leave AI strategy to the practice owner. A solid governance policy would help address the privacy concerns respondents ranked highest.
For practices that did automate workflows in 2025, the results were measurable. Sixty-one percent cited better patient communications and responsiveness, and 39% said automation reduced no-shows and last-minute cancellations. Companies interested in building these capabilities may benefit from AI automation training. Staff who understand automation principles can more effectively evaluate vendor tools and spot integration gaps before they cause rework.
Technology vendors push deeper into clinical workflows
Major health technology companies are embedding AI more deeply into their products. Oracle Health's Clinical AI Agent, for example, uses semantic reasoning to surface relevant context from medical histories, lab results, and medications while supporting real-time clinician dictation and recommending professional fee charge codes for review.
Meanwhile, CFOs face pressure to show tangible returns on AI investments. A recent Deloitte report said finance leaders' responsibilities are expanding faster than the tools and data available to support them.
Oxford Physical Therapy reported recovering revenue by combining AI documentation with revenue cycle management, giving clinicians more time with patients.
Why this matters for healthcare professionals
For practice owners and front-desk staff, the survey points to a clear opportunity: automating disconnected systems in the day-to-day routine with effective AI. The workflows with the strongest demand for automation - scheduling, insurance verification
Areas that directly affect daily workload and patient volume. Formal governance policies are expensive to create, but they are necessary for managing privacy risks and regulatory uncertainty that hold back adoption.
Staff who develop broader AI skills will be positioned to orient the emerging toolsets in their practices. Online AI courses for healthcare settings cover the clinical and administrative use cases that are moving from pilot projects to standard practice.
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