Navigating the emergence of Generative AI in health care

Potential treatments for the industry’s biggest challenges

The health care industry is facing a complex set of challenges, from labor shortages and clinician burnout to declining profitability and worsening health outcomes, particularly among underserved communities. To address these challenges and ensure the sustainability of health care organizations, as well as the well-being of consumers, organizations can leverage groundbreaking technologies while re-establishing genuine care and trust in health care practices. Generative AI technology holds the promise to help overcome these obstacles, offering solutions for both enterprise and direct-to-consumer applications.

In recent years, natural language processing and machine learning have found applications in various health care use cases, but new Generative AI models are taking health care technology to new heights. These models demonstrate unprecedented capabilities in natural language generation, summarization, translation, insight retrieval, reasoning, and managing unstructured, unlabeled data. Generative AI technology has the potential to democratize knowledge, increase interoperability, accelerate discovery, and enable true personalization in health care.

Consumer trust hangs in the balance

Perhaps most importantly, Generative AI can either deepen and restore trust or exacerbate mistrust and introduce new skepticism among consumers and health care stakeholders alike. To successfully address the challenges facing health care organizations, Generative AI must be designed, deployed, and scaled using a transformational approach that incorporates organizational change, ethics, and trust.

Generative AI in health care also holds promise across industries to streamline operations, from discovery through commercialization—enhancing efficiency, compliance, and consumer-centricity. By harnessing Generative AI, companies can achieve a competitive edge, accelerate innovation, and ensure more agile and informed decision-making across their value chain.

An enterprise ‘road map’ to deploy Generative AI in health care

Organizations can begin a Generative AI activation strategy from multiple starting points. The key is to rethink how to frame the challenge and desired outcome, taking a problem-first, technology-second approach, rather than a technology-first, problem-second approach.

We propose a five-part approach to actualizing Generative AI with a set of Trustworthy AI^™ considerations within your business, where organizations can begin in any of the five areas and pursue parallel progress. Download our full report to gain additional insights into each of these parts.

Part 1: Infuse AI into your organization
Part 2: Establish an AI operational foundation
Part 3: Develop an AI infrastructure plan
Part 4: Initiate experimentation and pilots
Part 5: Develop production-ready solutions and operational systems

Striking the right balance for the future of AI in health care

Successful integration of Generative AI into health care hinges on effectively balancing the potential for impactful improvements against the inherent risks. Leaders should conduct a rigorous, case-by-case assessment of each potential Generative AI application, carefully weighing the potential benefits against the associated hazards.

Given the rapidly accelerating pace of this technology—coupled with its complexity—Generative AI is challenging for organizations to implement effectively. That’s where the role of a trusted third party becomes invaluable. By working with specialists who have an in-depth understanding of the technology, health care leaders can navigate the complexities, maximize their return on investment, and ensure the technology is tailored to meet their unique needs.

If you’d like to learn more about the benefits of AI in health care or how your organization can better leverage the technology to add value, let’s set up a conversation.