ASCs, spine and pain practices are under pressure to grow patient volume without growing operational headcount, even as payer requirements make administrative work increasingly complex. A new generation of AI agent workforce is emerging to close that gap,not the conversational chatbots many practices already use, but intelligent “digital agents” that navigate systems (EMRs, Payers, Communication channels), make workflow decisions and complete the operational tasks autonomously.
The future of healthcare AI is not conversational AI. It is autonomous AI agents that do the work, operating inside existing enterprise systems just like a trained workforce, but faster, continuously, and at scale.
In a featured session sponsored by Orbit Healthcare Inc at Becker’s 23rd Annual Spine, Orthopedic and Pain Management-Driven ASC + The Future of Spine Conference, leaders made the case for moving beyond chat-based assistants into autonomous agents shifting from conversational AI to task-completing agents. The panelists included:
- TJ Wiles, COO, Orbit Healthcare Inc
- Krishna Velaga, CTO, Orbit Healthcare Inc
- Jack Cavanaugh, ASC and Pain Management Consulting Advisor, Orbit Healthcare Inc
Below are four takeaways from their conversation.
Note: Quotes have been lightly edited for length and clarity.
1. Digital agents augment staff rather than replace them
The panel drew a sharp line between conversational AI, which many provider groups have already adopted, and digital agents that operate across enterprise healthcare workflows, interacting directly with payer systems, EHRs, and operational platforms. . Roughly 80% of the provider groups Orbit Healthcare works with have adopted conversational AI, while only 10% to 20% have moved to digital agents, according to Mr. Wiles. He stressed that the goal is not headcount reduction but unblock operational capacity.
“You’re not really replacing, you’re augmenting that staff,” Mr. Wiles said. “The objective is not workforce reduction. It is giving teams digital capacity so they can focus on higher value work while automation handles repetitive operational tasks.”
The framing matters for adoption: Mr. Cavanaugh noted that staff fear of being made redundant is one of the biggest cultural hurdles, and that agents tend to win acceptance once teams see them absorb repetitive work.
2. Security and data isolation are foundational, not afterthoughts
Because AI agents require access to protected health information, Mr. Velaga said security was the first design consideration at Orbit. He described Orbit designed its AI infrastructure with enterprise-grade security as a core architectural principle combining encryption of data both at rest and in transit, secured connections through VPN and two-factor authentication, and built on Microsoft Azure carrying healthcare-grade compliances including high-trust and SOC 2 Type 2 standards.
One of the most common concerns enterprises raise is ensuring strict tenant isolation across AI workloads., Mr. Velaga said records are isolated and not retained: “Data never, ever gets shared between two clients,” he said. Processing data exists only for the duration of task execution and is automatically purged immediately after workflow completion, minimizing persistent data exposure.
3. ROI of agents should be modeled upfront and revisited continuously
Mr. Cavanaugh said centers typically target a first-year return of 20% to 30%, measured against the cost of acquiring, training and retaining staff as experienced employees age out. He cautioned that the figure has to be mapped to each provider’s existing staffing model rather than assumed.
According to TJ Wiles, organizations also need workload-based ROI models that account for the reality that administrative staff divide their time across referrals, insurance verification, scheduling, and other fragmented workflows. Without that operational context, financial leaders risk underestimating the true value created by autonomous AI agents.
Mr. Velaga emphasized that the biggest mistake organizations make is measuring AI only against headcount. The real value comes from increasing operational capacity, improving accuracy, and scaling workflows without adding equivalent labor
4. Phased, team-driven deployment determines success
Both Orbit Healthcare leaders emphasized that deploying autonomous AI agents is not a simple software rollout. Successful adoption requires a phased implementation strategy beginning with controlled pilot execution, workflow validation against live operational data, continuous exception analysis, and gradual production deployment with active monitoring.
TJ Wiles noted that organizations achieve the strongest outcomes when operations teams actively participate throughout deployment and validate agent performance before automation expands. Implementations driven by cross-functional operational alignment consistently outperform initiatives led by isolated executive sponsorship alone.
In one referral-processing engagement, Orbit reported that its agent increased new referral patients by 42% and claimed revenue by 22%, , while automating more than half of the administrative referral workload and eliminating a three-to-four-day operational backlog..
AI workforce deployment is not a technology project. It is an operational transformation project. Technology succeeds only when the operations team learns to trust the digital workforce.”
What this means for ASC and practice leaders
A recurring theme throughout the discussion was that successful AI adoption depends as much on organizational trust as on technology itself. Krishna Velaga described Orbit’s approach of intentionally humanizing AI agents as digital team members, assigning them operational identities such as referral agent “Reggie” or or Prior authorization agent “Tracey,” allowing staff to view them as part of the workflow rather than as external automation tools. Each agent operates with its own system credentials, permissions, and audit trail, much like any newly onboarded employee.
Mr. Cavanaugh made a similar point about process: building the deployment together surfaces the “why” behind each workflow, rather than defaulting to “that’s how we’ve always done it.” For leaders weighing the move from conversational AI to agents, the panel’s message was that the technology is ready, but the returns depend on disciplined, team-owned rollout — not on flipping a switch.
For healthcare leaders evaluating the next generation of AI, the message was clear: the industry is moving beyond assistive AI toward autonomous operational systems capable of executing real work. Success, however, depends not on the technology alone, but on treating AI deployment as organizational transformation, where digital workers become an integrated extension of the existing workforce rather than another software tool layered on top of it.
At the Becker’s 32nd Annual Meeting: The Business and Operations of ASCs, taking place October 29-31 in Chicago, ASC leaders, surgeons and healthcare executives will explore strategies to drive growth, enhance operational performance, navigate reimbursement challenges and prepare for the future of ambulatory surgery. Apply for complimentary registration now.
