Generative artificial intelligence (AI) offers significant promise as healthcare organizations seek innovative solutions to meet evolving consumer preferences, lower costs and address workforce shortages. While organizations are eager to realize the potential benefits of tech investments, prioritizing speed over other outcomes during an implementation can prevent long-term success and poorly affect culture. Huron’s research shows that three of the top five factors inhibiting ROI relate to people and culture, including lack of training, cultural aversion to change and lack of technical staff to drive implementation.
Forward-thinking organizations are approaching AI implementation differently by mitigating staff concerns and resistance with integration plans that provide employees with much-needed support. Three proven strategies equip healthcare institutions with the necessary foundation to simultaneously improve culture and technology.
1. Develop a clear, achievable road map
As healthcare organizations consider where to implement generative AI, selecting use cases that address specific pain points is the first step to gaining the most value from their investment. Maintaining a nuanced understanding of their risk profile and availability of data to train the AI model should also aid health systems in determining use cases. From there, setting realistic and trackable goals to reach before, during and after implementation ensures critical milestones are met.
Involving staff from different levels during the road map development phase can provide leaders with necessary feedback and foster a culture poised for transformation. Integrating staff from the beginning demonstrates a level of organizational transparency that can set the groundwork for determining and developing future AI use cases. Leaders can take this strategy further by weaving cultural milestones, not just ROI and productivity metrics, into the conversation.
2. Cultivate organizationwide support
As leaders seek to achieve strategic goals for generative AI implementations, how do they cultivate buy-in from staff who aren’t as invested in change?
Drawing a line from how staff will use AI on a day-to-day level to the positive impact expected for their specific roles, including improvements to care delivery, patient outcomes and community health, can encourage engagement. Creating an organizational communications plan – highlighting successes, pain points and key metrics – keeps staffers informed of how implementation projects are progressing and encourages teams to connect and share feedback more frequently.
3. Empower staff to own the transition
While it’s easy to be enthusiastic about AI's potential use cases — including managing clinical claims appeals, patient data analysis and disease prediction — staffers are often skeptical of potential disruptions to their daily work or additional workload burdens. Leaders can minimize concerns by instilling a sense of ownership and demonstrating how the new AI tool can aid productivity, and enhance career growth, rather than disrupt existing processes.
Investing in comprehensive training and implementing an organizationwide readiness network can empower staff members to own the transition. Functioning as early adopters of new AI tools, network members can assist colleagues and project teams, serving as communication liaisons to create a positive culture of people and technology enablement.
For organizations aiming to foster an environment that welcomes emerging technologies like AI and minimizes disruptions throughout implementation, a fresh approach is essential. By dedicating more time to comprehensive planning, establishing a persuasive sense of organizational purpose and easing staff concerns, they can position themselves for success and cultivate a culture that not only withstands change but thrives within it.