4 Critical Steps to Scale Generative AI

As health care organizations grapple with rising operational costs, an aging population and a worsening workforce crisis, the need for transformative solutions has never been greater. A new Accenture report, “Gen AI Amplified: Scaling productivity for health care providers,” highlights how generative artificial intelligence (AI) can offer a critical path forward — unlocking unprecedented productivity gains, enhancing patient care and reshaping the future of care delivery.

Health Care’s Inflection Point

Health care providers face a historic staffing shortage: By 2033, the U.S. is projected to lack as many as 139,000 physicians while the global nursing shortfall could reach 13 million. Traditional solutions like increased hiring and training alone cannot meet this demand. Providers must embrace innovative technologies to scale human capacity.

Generative AI presents a powerful opportunity. According to Accenture’s survey of 300 U.S. health care C-suite executives, 83% view boosting employee efficiency as the biggest opportunity of generative AI, and 77% expect it to drive direct revenue growth productivity gains. Early pilots show promise — automating routine tasks, improving data analysis and enhancing decision-making — but widespread adoption remains limited.

Despite high awareness, a major execution gap exists. While 83% of health care organizations are piloting generative AI, fewer than 10% have invested in the infrastructure needed for enterprise-wide deployment. Without decisive action, health care risks falling behind industries like automotive and finance, where AI-driven gains are already significant.

A Road Map for Action

The Accenture report outlines four critical steps to help health care leaders move from fragmented pilots to scaled implementation:

1. Build a reinvention-ready digital core. A robust digital infrastructure — including cloud integration, seamless data access and scalable AI capabilities — is essential. Organizations with a strong digital foundation are poised to reinvent twice as many functions with generative AI over the next three years compared with those without.
2. Strengthen data quality and strategy. High-quality, centralized data are a prerequisite for reliable AI outcomes. Health care providers must prioritize data cleansing, standardization and accessibility to empower AI to deliver clinical and operational benefits.
3. Prioritize responsible and secure AI deployment. As the use of generative AI expands, safeguarding patient privacy and preventing cybersecurity breaches are nonnegotiable. Embedding responsible AI governance is critical to building trust among patients, providers and regulators.
4. Forge strategic partnerships. Scaling generative AI requires expertise beyond internal capabilities. Collaborations with technology leaders, academic institutions and specialized vendors are key to accessing cutting-edge tools and accelerating innovation.

The Productivity Promise

Accenture estimates that 70% of health care workers' tasks could be reinvented through technology. In nursing alone, automation could free up 20% of repetitive tasks.

Examples already abound:

• Generative AI can automate clinical documentation, giving physicians back minutes to hours per day — time that can be redirected to patient care.
• Generative AI-augmented call centers have reduced patient wait times and improved first-call resolution rates without compromising security.
• AI-enabled clinical appeals processes have achieved a 70% reduction in handling time and a 30% decline in misrouted claims.

However, staying in pilot mode comes at a cost. Piecemeal implementations prevent providers from achieving the full operational efficiencies that scaled deployment can offer and widen the gap between health care and faster-moving industries.

Leadership Alignment Is Critical

A unified C-suite vision is essential. While CEOs recognize the transformative potential of generative AI, clinical leaders like chief medical officers (CMOs) and chief nursing officers (CNOs) are often underutilized in planning and deployment efforts, even though clinical workflows are among the most impacted.

The report stresses that everyone from board members to front-line clinicians must be involved in redefining roles, automating tasks where appropriate and reskilling teams to work alongside AI tools.

Key takeaways for health care leaders

• The time to act is now. Scaling generative AI can drive productivity, reduce burnout and enhance patient care — all while improving financial sustainability.
• Build the foundation. Investment in cloud infrastructure, high-quality data and responsible AI frameworks are nonnegotiable prerequisites.
• Don’t go it alone. Strategic partnerships will be critical to closing skill gaps and accelerating deployment.
• Empower clinical leadership. CNOs and CMOs must play a central role in redesigning work processes to ensure that AI initiatives improve, not burden, care delivery.
• View generative AI as an ongoing journey. Scaling technology is not a one-time event, but a continuous reinvention of how health care operates.

Generative AI is no longer a futuristic concept; it’s a present-day imperative. Health care organizations that act decisively today by scaling generative AI strategically and responsibly will define the next decade of health care delivery. Those that hesitate risk being left behind.

Additional Resource

The AHA recently released a report to guide hospital and health system executives on using AI and AI-powered technologies to transform their organizations’ operations. The report, “Building and Implementing an Artificial Intelligence Plan for Health Care,” features insights from 12 health care AI experts and leaders, published health care articles, presentations, reports, research and surveys on health care AI.