Artificial intelligence is not the next big thing after healthcare. It is already here and in the waiting room, OR and back office. From AI-enabled EHRS to automated scheduling, predictive billing tools, to diagnostic support systems, the technology touches almost every part of the care continuum.
Even concerns about costs, privacy and ROI have not slowed down adoption. 35% of doctors say their enthusiasm for health exceeds concerns about it. And many people realize that adopting AI is just a business necessity.
But here's the rub: AI adoption moves faster than most labor is ready to use it.
The AMA reports that physicians' use of AI jumped 78% in a year. The World Health Organization (WHO) says its ability to effectively implement AI is lagging behind the speed of technological advances. Microsoft also shows a big gap between employees who use AI every day (75%) and employees who provide employer-sponsored training (39%).
Important, but often missed the step in recruiting healthcare AI: Workforce-up skills
Doctors say that “proper training and education” is important to employ AI. The healthcare industry is already facing retention issues and labor shortages (strong debate for investing in existing talent). And the pace of AI adoption in healthcare supports training that maps directly to daily workflows. So why can't there be any more healthcare organizations that use AI training programs to ponder and reskill employees?
Here are some things that may be in the way:
Training Costs In addition to already significant investments in AI software and infrastructure. The misconception that AI is plug and play (intuitive as there is no training required). The leadership idea that AI is “intentional to do the job” does not support workers in helping different concerns that the time spent training is either reduced productivity or overflowing staff will make them more marketable and difficult to retain.
To encourage these concerns to train a training decision is a risk associated with ironic sidecars. Without training, you are not implementing AI. And without using it, AI under delivery. Clinicians may feel distrustful of output, leaving workflow fragmented, and document gaps may persist. Rather than mitigating the administrative burden, AI can create new frustration. And without formal training and guardrails around AI, healthcare organizations risk inconsistent use of technology, wasteful investments, potential privacy and compliance issues, and missed opportunities to improve patient care.
Thankfully, we are beginning to see the shift… there is a growing demand for AI training from employees as well as employers. Not just from providers, but from payers. In an article on AI opportunities for healthcare payers, McKinsey & Company outlined six focus areas for payers to achieve success in AI and automation. One of these was ensuring that talent has the skills and abilities needed to execute and innovate. The other was to properly employ AI and enable organizations to maximize the value of their investment.
So the question is, which training works across the healthcare ecosystem, so employees not only learn about AI, but maximize their use and value?
Finishing the skill gap
Healthcare requires dedicated AI training programs for healthcare, and requires a guidance-based, practice-based approach and immediate application as the ultimate goal. This means looking for practical AI training as well as theoretical AI training. What is the difference?
Theoretical training focuses on concepts, principles and knowledge about the subject. The goal is to build understanding. Practical training is practical applied learning that focuses on what you do rather than just knowing. The goal is to build skills. If theoretical training teaches us what is and why it is important, then practical training teaches us how to actually use it.
For healthcare AI, sweet spots are blend training. Their theory to understand how AI works, where it can and cannot, and where the risks lie, combined with practical training that embeds AI into your daily workflow, will stop adoption.
A practical AI program dedicated to medical use
Recently, I had the privilege of reviewing two online training programs from Chegg skills that absolutely fit the bill, and hearing practical AI for medical management for clinicians, practical AI. These programs are built with healthcare professionals as well as healthcare professionals, and are practical, role-specific, and designed to allow learners to apply new skills to their jobs the next day. This is an AI upskill for busy mission-driven professionals tailored to the complexity of the clinical and managed environment. It's not because of curiosity, but because it directly affects their work and the success of the organization.
For each program, academic success coaches are ready to help learners set goals, establish learning routines, and navigate obstacles. Learners can also get real-time guidance and feedback via live tools such as live chat, AI-powered simulations, and personalized lessons with industry experts.
Practical AI for Clinicians
In this program, nurses, doctors, and alliance health professionals will learn how to:
Automate documents and EHR tasks without losing bedside connections.
Use AI to support diagnosis, treatment planning and patient communication.
Writing HIPAA compliant AI requires safe and ethical use.
A balance between AI efficiency and caring care.
Examples of practical projects to complete the program: Use AI to implement mock patient intakes to document, summarise and communicate care plans while maintaining compliance and empathy.
Practical AI for Medical Management
The program assists healthcare administrators, managers and operations teams.
Streamline scheduling, claims and insurance processing.
Build a governance framework for AI use in sensitive data processing.
Optimize your revenue cycle with predictive analytics.
Improve patient communication systems using AI tools.
Examples of a practice project: Redesign the clinic's scheduling system using AI to improve patient flow, reduce wait times and incorporate strict privacy safeguards.
Example Results
In one case, a large healthcare system implemented AI to streamline documents, analyze data and improve communication, but it had not yet implemented official AI policies or AI training. However, the organization had employee benefits that provided educational opportunities, including online training programs from Chegg Skills. Several employees considered taking the AI program from Chegg Skills, known as AI Fundamentals (healthcare-centric programs were not available at the time). Learners who complete the AI foundations have achieved a 4.5/5 CSAT score (50% higher than comparable healthcare organizations), with 95% achieving course goals, 17 points above their peers. This shows that healthcare workers were very hoping for AI skills, and they sought them out on their own. And even in programs that did not focus on healthcare, employees received such relevant, well supported training, they thrived. More reason to appreciate the new healthcare-centric AI options from Chegg skills.
Important differentiators
These programs are as follows:
Learner-centered experience – A short form of interactive lesson for adult learners that balance competing priorities.
Focus on technical and human skills – Integrate AI learning with communication, emotional intelligence and problem solving.
AI and Human Coaching – Personalized support from award-winning academic success coaches and on-demand AI feedback tools.
Flexible Format – Access anytime, anywhere, 3-5 hours a week for 2-3 months.
Results Prioritization – A real-world project that directly improves work performance.
Thoughtful design
That's what makes Chegg skills stand out. What do I say? All of the above, and some.
A comprehensive build process with healthcare professional engagement, a rigorous educational design that took time to get real-world examples correctly, and robust quality assurance to ensure key decision makers are confident in providing educational opportunities for staff.
Plus, thoughtful design. This was not a “copy and paste” from other industries. Chegg Skills already has a strong track record of high-class adults in high-demand areas, from high-tech to business operations, but they knew that one of healthcare's existing AI curriculum would not work. Healthcare's unique requirements, such as regulations, privacy concerns, and various workflows, are simply different. So they rebuilt from scratch and became certain as follows:
Skills are durable throughout the system. Instead of teaching people to track the latest vendor tools and software updates, Chegg Skills focuses on durable skills that last longer than platforms and technology. These are transferable and deeply human abilities, no matter how fast AI is evolving, or whatever system controls the market. Rather than train someone to master the latest version of EHR or CRM, for example, their team emphasizes skills such as problem solving (navigating ambiguity and tackling novel challenges), data literacy (interpreting information, asking the right questions, asking the right questions), ethical decision-making (creating healthy choices in complex, high-stakes environments), and ethical decision-making. it affects trust and outcomes). Programs are role-specific to ensure immediate applicability. The learning paths for clinicians and administrators address fundamentally different use cases. Practice environments are accessible without institutional paywalls (many healthcare tools are behind demo-friendly platforms that include paywalls, Chegg skill integration freemiums, and AI simulations, allowing learners to practice without institutional barriers). HIPAA compliance is a through line, not an afterthought (even simulation designs were reviewed to avoid the risk of PHI being recognized).
Chegg's skills have also grown deeper from day one to small and medium-sized businesses. The build team had nurses, doctors and healthcare administrators actively working in this field. They discussed everything from quick phrases to PHI safeguards, ensuring that they embedded their actual expertise. One doctor SME reviewed post-shift scripts and course materials from the parking lot. This is because flexibility is built into the development process, preventing the stone from being turned over.
And finally, pricing. This medium-level upskill space (practical, interactive, and volume prices available for less than $5,000 per learner) is surprisingly underserved. On the one hand, there are low-cost content libraries like LinkedIn Learning (if you have low completion and retention rates). Meanwhile, there is high-five and expensive executive coaching. Chegg's skills fill the gap with strict, applied learning that actually sticks to.
Healthcare Leaders: Next Steps
AI is not waiting for your strategic plan. Your team has already encountered AI. The question is, are they ready to use it effectively, ethically, and confidently?
Training is important. These programs are designed for frontline and mid-level professionals, but we know that success starts from the top. Advocating for AI upskills sends a message that you are preparing your workforce for being a medical AI-enabled future and you want to grow with them. In return, maximize your AI investment, improve performance in your current role and achieve stronger retention.
Reach out to Chegg skills to discuss training for individuals, teams, or organizations as a whole. If you have large registrations, you can customize everything from customized live sessions to employer-specific case studies. Also, if you want to test Waters, Chegg Skills offers several tester sheets that you have registered for free in exchange for feedback and testimony. It's a limited offer, so act fast.
Join my hospital membership! If you are a VP or Director working in Strategy or Corporate Development in a hospital, health system or provider organization, you can get a lot of value from the community as it is intended for content, fireside chats and conversations in this group. Please apply here.
