When we picture AI in healthcare, it’s tempting to imagine tools so seamless and intuitive they practically set themselves up. But as we’ve explored in the first and second posts of our series on implementing AI in the operating room, integration is far from automatic. Behind every successful deployment is a network of individuals, each with their own expertise, responsibilities, and concerns. From surgeons to security analysts, this is a human-centered process. Understanding who these stakeholders are and when they become involved is essential for any hospital hoping to deploy AI successfully.
Setting the vision
The Clinical Champion: This is your internal advocate. They are typically a surgeon, an anesthesiologist, or another respected clinician who sees a clear opportunity to use AI to improve operating room performance. They build the initial business case, connect with peers across the organization, and ensure that the proposed solution aligns with clinical needs. They're focused on real-world value and remain deeply involved from pitch to pilot.
Departmental Leadership: As the idea gains traction, department leaders and perioperative services managers step in. These individuals, such as OR directors or chairs of surgery, help bridge the gap between frontline clinical staff and hospital administration. Their concerns focus on measurable improvements to surgical flow, as well as staff engagement. They know that without buy-in from nurses and techs, the initiative may falter, regardless of its technical merits.
Check out our Complete AI Implementation Checklist for Operating Rooms to plan and track the critical success factors at every stage of deployment.
Executive Leadership: The proposal eventually reaches the executive team, which includes the CEOs, COOs, CFOs, CMOs, and CNOs. These leaders evaluate whether the AI investment aligns with broader strategic goals, such as quality improvement, operational efficiency, and competitiveness. They also assess financial feasibility, resource requirements, and prioritization timelines. Hospital executives want clear ROI projections and reassurance that the technology won’t introduce risk. They often require proof from peer institutions or a phased approach to reduce exposure. Once they have conviction, they authorize funding, make allocations, and empower internal teams to move forward.
Laying the foundation
Finance and Business Strategy: These stakeholders, CFOs, and analysts help evaluate the business case from a financial perspective. They model return on investment, consider downstream cost savings, and align the AI deployment with broader budgeting objectives. Their input is essential in moving beyond pilot phases, especially if the technology will be rolled out across multiple departments.
Compliance, Privacy, and Risk Management: Throughout the process, compliance officers, privacy leaders, and risk management teams provide oversight. These professionals scrutinize everything from encryption standards to data retention policies, ensuring the technology meets institutional and regulatory requirements. Their concerns are rooted in patient safety and legal exposure. They typically get involved during the planning phase, reviewing vendor materials and approving contracts, and they remain engaged through go-live to monitor adherence.
Building the backbone
The IT Department: Integral to this process is the hospital’s IT department. From the CIO to network architects and interface engineers, this group of experts ensures that the AI solution integrates securely and reliably with existing systems. Their involvement is often a make-or-break factor in the implementation timeline. They’re responsible for setting up VPNs, configuring firewall rules, whitelisting devices, and establishing data transfer protocols. They should be brought in early and consulted often throughout the entire planning and deployment process. When IT professionals are looped in late, the project can hit unexpected delays or stall altogether. Their concerns are expansive, including cybersecurity, interoperability, and long-term system stability.
Check out our Complete AI Implementation Checklist for Operating Rooms to plan and track the critical success factors at every stage of deployment.
The EHR Team: Running in parallel with the IT team is the EHR group, typically consisting of two to three people who manage surgical scheduling data and reporting within systems like Epic or Oracle Health (Cerner). These individuals facilitate data integration by configuring interfaces and delivering the reference and historical data necessary to train machine learning models that power AI. These team members can be in high demand and sometimes resource-constrained, so their availability may become a bottleneck.
On the ground
Project Manager: A critical but often under-recognized role in successful AI rollouts, the internal project manager, typically from the hospital’s IT or perioperative operations team, keeps the entire effort on track. Project managers coordinate across departments, vendors, and clinical teams, build schedules, manage procurement, and troubleshoot blockers to ensure smooth transitions between phases. Their biggest challenges include juggling competing internal priorities, navigating unclear handoffs, and managing limited resources. Without a clearly defined project manager, even the best-planned implementations are at risk of delay or derailment.
Facilities and Installation Teams: On the ground, the facilities and installation teams are responsible for physical infrastructure and make the operating room deployment happen. This includes pulling Ethernet cables through ceilings, mounting sensors on OR walls, and coordinating night-shift work to avoid disrupting surgery schedules. Low-voltage vendors or hospital electricians often support these teams. They’re working against both logistical and budgetary friction, but the presence of a project manager on the hospital side can ensure that materials are procured and schedules are adhered to.
It takes a team
While having the right stakeholders in place is foundational, the way those individuals collaborate across implementation phases often determines whether a rollout is smooth or stalls. Across these phases certain implementation patterns consistently lead to smoother rollouts. Clear timelines that outline every stage, updated and revisited regularly, help everyone stay aligned, especially when resources are shared across departments. Shared goals and measurable ROI metrics encourage cross-functional prioritization, not just siloed contributions. And assigning dedicated liaisons for each function ensures continuity: even after one team has handed off its part, that liaison remains plugged in to support downstream needs and avoid blind spots. When these structures are in place, they create a rhythm of collaboration that transforms complexity into coordinated action.
Implementation of AI in the OR is an organizational transformation. And at the heart of that transformation is a diverse, cross-disciplinary team of people. Each stakeholder brings a different lens and, when they’re engaged at the right time with clear communication and purpose, implementation becomes not just possible, but successful. Just as important is having the right partner by your side. Vendors do far more than deliver a product as they support configuration, troubleshoot issues, observe installations, provide training, monitor outcomes, and evolve the system over time. Choosing a vendor with real-world experience and a deep understanding of perioperative environments can make all the difference. If you're planning to implement AI in your OR, connect with Apella to see how we can help you succeed.
Check out our Complete AI Implementation Checklist for Operating Rooms to plan and track the critical success factors at every stage of deployment.