Healthcare’s AI opportunity is a lesson for every industry
Practical suggestions to make sure your business doesn’t fall behind.
The transformative potential of AI in healthcare is staggering. From streamlining administrative tasks that currently take clinical time away from patients to improving diagnostics and treatment, AI seems poised to reshape how we experience healthcare.
But what happens when workforces aren’t ready to work alongside AI?
Compared to other industries, healthcare has been slow to adopt AI. Regulatory barriers and understandable concerns about data privacy, security, and the challenges of integrating and operationalizing AI (known as “switchover disruptions”) have slowed integration.
Although multiple health systems have begun to introduce various AI tools across a range of clinical and non-clinical use cases, most healthcare workers still haven’t had the chance to explore using AI tools on the job.
That lack of opportunity can limit the return on investment many healthcare organizations stand to gain from AI adoption.
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“For an industry all too familiar with the negative effects of burnout, AI is a clear opportunity to address the administrative burdens their employees face.”
Hanna Patterson, Senior Vice President of Healthcare and Applied Learning, Guild
This opportunity isn’t unique to healthcare. AI will impact virtually every industry — and AI skills are already becoming a labor market commodity. Imagine if your workforce already had them.
Here are some early lessons from healthcare and AI that apply across industries.
Reducing administrative burden is the start line.
One of the most significant challenges healthcare faces today is worker burnout. The problem is so pervasive and severe that the U.S. Surgeon General, Dr. Vivek Murthy, issued an advisory on the dangers burnout poses to healthcare workers and patients.
One of the drivers of burnout Murthy identifies is the increased administrative burden on a workforce already stretched to its breaking point. "Inefficient work processes, burdensome documentation requirements, and limited autonomy can result in negative patient outcomes, a loss of meaning at work, and health worker burnout," Murthy says, calling on employers to reduce administrative burden by 75% within the next few years.
AI could alleviate a significant amount of that burden, operationally and economically.
A recent report from Citi Global Insights shows that AI-driven automation could save approximately 25%-30% of administrative costs. Less time spent on administrative tasks leaves more time for patient care.
Other industries see analogous benefits. In financial services, for example, a Nvidia survey found that 36% of executives have already saved at least 10% on costs thanks to AI. Across industries, automating certain administrative tasks seems to be the low-hanging fruit.
There’s just one problem: most healthcare organizations aren’t giving employees the opportunity to explore AI tools at work, and they’re not alone.
Although healthcare is significantly behind, multiple industries are lagging in offering their workforces the chance to learn AI skills. Guild found that only 1 in 3 employees in retail and financial services industries who have used AI have access to resources or guidelines for its application in the workplace.
Viewing the people who make a business possible as cost centers is a mistake. When employers take a people-centric approach to AI, the connection between overcoming barriers to efficiency and opening up internal talent pipelines becomes clear. Future-oriented skills now prepare employees for the roles companies will need soon.
Employees who want to explore AI don’t know where to start or what to trust.
Poor use of AI is, in itself, inefficient. Disaggregated use of AI tools can inflate operational costs and lead to inadequate implementation of AI solutions.
That’s because, as intuitive as AI tools can be, users failing to know best practices leads to missed opportunities and, often, redundancies.
Building this muscle takes time. For AI to provide the diagnostic, procedural, and preventative support that can save more lives, today’s healthcare workforce must start building AI literacy now.
AI use and guidance are decentralized in many companies. Some employees use generative AI, and some don’t. Most of us don’t fully understand the tooling and solution landscape. That lack of fluency and guidance can lead to mistrust and confusion.
Here’s the argument for healthcare organizations to step up and provide more training and clarity: AI stands to influence every role in healthcare. It has the potential to drastically reduce administrative burden and the negative impacts that accompany it — but the healthcare workforce needs to be ready to work alongside it.
No organization has the time to slow-walk AI skills.
The stakes are always high in healthcare, and the potential repercussions of implementing AI without a strong strategy are no exception. Poor oversight can lead to the use of datasets that fail to address (and therefore perpetuate) racial, gender, and other demographic biases.
Lacking an AI strategy can put any organization at risk. That doesn’t mean workforces should be kept waiting to start building job-relevant AI skills.
What these skills tend to look like is already known. A strategic approach to relevant skills — from foundational AI literacy to more technical use — is imperative.
What can be done now?
- Get ahead of the “hype cycle.”
As with any exciting new technology, employers have a short window before the “hype” dissipates to drive employee engagement, adoption, and the integration of new AI skills into daily work. Gartner calls this the hype cycle, which Guild’s Matthew Daniel discusses here. - Reduce the inefficiencies that hold employees back.
In healthcare, AI has the potential to reduce burnout-inducing administrative burden significantly. Beyond that, AI stands to impact all of healthcare — from systems and records to procedures to equity in patient care across diverse populations — meaning AI skills matter across roles in healthcare.
Regardless of the industry, leaders should consider the impact AI has on current role types. For example, technical teams may benefit from diving straight into hard AI skills. In contrast, non-technical employees may benefit most from foundational learning that builds AI literacy and covers ethical considerations. Executives may benefit from short-form learning on AI strategy. - Get strategic with education benefits.
Make sure education benefits cover AI upskilling, connect employees with job-relevant AI skills, and include options from trusted institutions for programs that don’t have prior education requirements. (No one should be required to get a degree to learn foundational AI skills.)
In combination, these steps can start to position employees to prepare for how AI may impact their roles and build business-aligned skills as organizations implement AI.
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About Alex Cannon
As a versatile writer and strategist, Alex is leaning into the productive tension between the future of learning and the future of work.
