Driving Long-Term Value: The Role of Customer Success in AI Adoption

In healthcare AI, the spotlight often falls on the technology itself, focusing on its speed, precision, novelty, and outcomes. Yet, behind every seamless deployment and every radiologist who embraces a new tool is a team that supports lasting impact: customer success.

Customer success is not a peripheral function but a core discipline that defines how a vendor collaborates with customers and ensures meaningful, lasting outcomes. To understand what this work looks like behind the scenes, we turned to Ana Bass, an Enterprise Customer Success Manager who specializes in supporting Rad AI Reporting customers.

Her perspective reveals the depth of expertise and cross-coordination required to support radiology teams in adopting new AI solutions, as well as understanding how success is defined and measured.

Understanding What Success Actually Means

Every organization defines success on its own terms. For this reason, one of the earliest priorities for healthcare AI onboarding is gaining a clear understanding of what the customer hopes to achieve, even before implementation begins.

For some, success is rooted in measurable efficiency gains. Others look for a clear return on investment. Some want their radiologists to feel more supported and less burdened throughout their day. Bass and her team use these insights as a guide, shaping both the implementation strategy and the ongoing partnership approach.

“Everyone has a different definition of success…it gives us the benchmarks we need to show value and to show that the investment they’re making is a good one,” said Bass.

This clarity eliminates assumptions, aligns expectations, and ensures that the tool delivers outcomes that genuinely reflect each customer’s priorities, rather than relying on a one-size-fits-all standard.

Trust and Workflow Fit Matter More Than Anything

Modern radiology relies on workflows that are inherently complex, interdependent, and highly sensitive to disruption. Introducing new technology into this environment requires deliberate planning and consideration. Clinical routines must remain stable, information must flow smoothly across systems, and radiologists must be able to maintain their pace without added friction.

This level of integration cannot happen in isolation. It requires a partner that understands how radiologists work and one that can integrate new tools into existing processes without adding complexity. Bass’ role centers on this alignment. She works closely with teams to anticipate workflow needs, resolve friction points early, and ensure that AI feels like a natural extension of the radiologist’s existing routine.

Trust naturally emerges from this process. Radiologists are more inclined to embrace a new tool when they see that it supports rather than hinders their workflow. As Bass notes, “You can’t have engagement if they don’t have trust in you and your products.”

Making AI Adoption Feel Effortless

By the time radiologists access the product, the vendor and customer’s IT teams have completed the foundational setup and configuration processes for a seamless go-live experience. This preparation enables users to recognize the value immediately, which is particularly important for those who may be cautious about new technology.

“We work hard to ensure this isn’t a heavy lift for them, and we take on the bulk of the work to make that happen,” said Bass.

Radiologists have different levels of comfort and experience with AI. Because any integration complexity has been resolved behind the scenes, the customer success team can focus on providing support tailored to each user’s needs, from a brief introduction for early adopters to more hands-on guidance for those seeking additional reassurance.

What Radiology Teams Should Know When Considering AI

Beyond confirming a new AI tool aligns with priority needs and goals, radiology teams must consider whether the conditions for successful adoption are in place. 

Clear alignment on objectives, expectations, and desired outcomes shared between the organization and the AI partner builds a strong foundation for AI adoption. This allows for adoption that feels steady, supported, and well-integrated into daily practice. It also sets the stage for the change management required when a new technology becomes part of daily practice. 

If your organization is preparing for AI adoption, take the next step with confidence. Let’s connect to discuss your specific needs. Click here to schedule a meeting at RSNA 2025.