Generative AI in healthcare: 3 urgent opportunities

The World Economic Forum estimated this week that 25% of all jobs will change¹ over the next five years, and AI will play a large part in this monumental reorganization. That shift is already underway in the tech world: IBM CEO Arvind Krishna said he expects AI to replace as many as 7,800 workers and the company paused hiring² for back-office job functions that AI can replace. What’s more, Alphabet, Meta and Microsoft executives have signaled³ that AI will render some jobs extinct — and those are just the most recent examples. 

That reality coupled with the rise in generative AI as witnessed at the HIMSS health IT conference, which included an intriguing deal that would see Epic and Microsoft jointly integrate GPT-4 into Epic’s EHR⁴ as well as a number of other significant announcements, has many leaders wondering what all the attention to AI actually means to healthcare? 

The near-term answer is that generative AI has the potential to drive meaningful impact in three critical areas of healthcare: workforce, economics and member or patient engagement — all against a significant risk of not adopting the technologies quickly enough. 

Let’s delve into each of those individually. 

AI and workforce 

The most pressing issue in healthcare today is the shortage of trained professionals⁵. This is significantly impacting both health plans and health systems  in terms of outcomes, revenue and business operations. In Philips’s most recent state of healthcare report⁶, the company found that executives are increasingly investing in AI to alleviate the pressure health systems are facing when it comes to clinical workforce shortages. AI can help address this workforce problem by automating routine tasks, such as data entry, processing and analysis, which can free up clinicians to focus on more complex and critical tasks. 

Additionally, AI can help health systems better manage their workflows and schedules, reducing the burden of administrative tasks and enabling them to see more patients. Generative AI also has the potential to assist clinicians with digital patient interactions and has even been shown to offer competent and empathetic communications⁷ to common questions. All of this will be particularly important as healthcare providers face increasing demands on their time and resources, and as patient volumes continue to rise. By augmenting the workforce with AI-powered tools, providers can deliver better care to more patients while reducing the workload on their staff.

AI and healthcare economics

The application of AI in healthcare has significant economic implications, both in terms of cost savings and revenue generation. For example, AI-powered chatbots can provide immediate and personalized support for members and patients, reducing high-cost ER visitations and increasing access to preventative care. Predictive analytics can identify patients who are at risk of developing chronic conditions, enabling providers to intervene early and prevent more costly treatments down the line. Additionally, AI can support population health management by identifying patterns and trends in large datasets, enabling healthcare organizations to tailor their services to the needs of specific patient and member populations. Overall, the use of AI in healthcare can help to drive down costs, increase revenue, and improve the quality of care.

AI and member/patient engagement

Generative AI in particular has the potential to transform patient care and consumer experience in healthcare by allowing organizations to create personalized and efficient solutions for each of their individual healthcare consumers. By analyzing consumer data and learning from previous treatments and outcomes, generative AI can create tailored treatment plans that take into account an individual’s unique health history, genetics and a number of other factors. Additionally, generative AI can be utilized to orchestrate personalized health journeys, guiding individuals through specific healthcare experiences and providing them with relevant resources, recommendations and support at each step. Whether it’s helping patients navigate complex treatment options, managing chronic conditions, or promoting preventive care, generative AI can play a crucial role in ensuring that each member and patient receives the appropriate care at the right time.

This personalized approach can lead to improved health outcomes, particularly when it’s paired with a CX platform like League that is built to support consumer engagement and enable secure data liquidity. Overall, the potential for generative AI to impact member and patient CX and outcomes is enormous, and it is exciting to see how this technology will continue to evolve and improve the healthcare industry in the coming years.

AI concerns and ethical considerations 

All of these potential benefits are not without concerns. One of the biggest issues is the potential for AI to exacerbate existing healthcare disparities, particularly for vulnerable and underrepresented populations. Additionally, there are concerns about the transparency and accountability of AI algorithms and how they make decisions. It’s important that healthcare organizations and AI developers prioritize transparency, fairness and broad representation in the development and deployment of AI technologies. There are also concerns about the potential for AI to replace human interactions and the impact that could have on the doctor-patient relationship. Finally, there are concerns about data privacy and security, particularly as member and patient data is collected and analyzed by AI algorithms. It’s crucial that healthcare organizations prioritize data security and privacy to ensure that patient data is protected and used ethically. These are real concerns that League has been focused on for a number of years and why we have developed an ethical framework that guides our AI and machine learning. 

The opportunity cost of slowing AI adoption

There is certainly reason for caution when applying new technologies, especially for something as transformative as AI. However, there is also another ethical concern to consider and that is the opportunity cost of slowing AI adoption, which is significant for both healthcare organizations and consumers. AI advancements are occurring not just rapidly, but exponentially. New processes, insights and discoveries are continuously materializing through AI that directly impacts the lives of healthcare consumers. 

By being overly cautious and not keeping pace with AI, healthcare organizations also risk falling behind competitors leveraging the technology. In radiology, for instance, AI is already being proven as more effective than humans⁸ at reading images. Executives that do not deploy such tools will ultimately lose consumers shopping for the most accurate results and potentially spend more over the long-term on personnel. That’s not to suggest AI will replace radiologists anytime soon but those organizations and individuals who augment their abilities with AI will thrive — particularly with workforce shortages projected to worsen in the years ahead.  

The potential benefits of AI in healthcare are too significant to ignore, and it is mission-critical for healthcare organizations to think strategically about how to integrate this technology while also considering its ethical implications.

Conclusion 

Healthcare executives watching and waiting to see what happens will quickly find their organizations moving too slowly. Generative AI is already here in healthcare, aiding providers in delivering patient care and payers with critical communication with members. It’s moving the needle when it comes to patient engagement and knowledge transfer among clinicians. Plus, it’s bringing a new level of intelligence and efficiency to everyday tasks like data collection and processing. AI sophistication and efficacy are advancing exponentially along with its adoption throughout the healthcare industry. 

The risks — including but not limited to human lives — of inertia far outweigh the risks of moving too quickly. Instead, now is the time to be thinking strategically about AI and identifying the critical areas where the application of generative AI can meaningfully impact your organization.

The next step for C-suites

Executives embarking on digital and CX transformation initiatives to address healthcare consumerism are undertaking the most significant technology and change management projects the industry has seen in more than a decade. 

For comprehensive, actionable insights on leveraging CX transformation to advance business objectives, download the C-Suite Guide to Leading Healthcare CX Transformation.