What Is The C-Suite Getting Wrong About AI Strategy?

A new survey of the healthcare C-Suite finds that different executives have different ideas on governance. And they’re not sure about ROI, either.

A new survey of healthcare C-Suite executives finds that while many are taking a good look at generative AI, they’re not doing what they should to support scalability or sustainability.

The survey of 300 executives from American healthcare organizations, conducted by Accenture Managing Directors Tejash Shah and Kaveh Safavi and Health Industry Lead Researcher Daniel Owczarski, indicates 83% are piloting gen AI tools, but only 10% are investing in the data infrastructure needed to deploy the technology beyond the pilot.

There’s also a disconnect on who should oversee AI strategy. Some 28% of CEOs said they’ should be responsible for redefining jobs and roles impacted by AI, but only 5% of C-Suite executives agree. About 80% say the Chief Digital Officer or Chief Digital and Artificial Intelligence Officer should have that role, and less the 4% believe the CNO or CMO has any part to play in this.

“This perception overlooks a crucial reality: The labor shortage is most acutely felt by the clinical workforce, particularly nurses,” the report’s authors stated. “Clinical leaders will play a pivotal role in ensuring that gen AI-driven workflows deliver sustainable value and improved efficiency.”

“The true benefits of gen AI come from fundamentally changing how work gets done, which requires collaboration across leadership levels,” they continued. “Clinical leaders, such as CNOs and CMOs, should play a central role in redefining work models, identifying tasks for automation and empowering staff with tools that simplify their jobs. These efforts will help address the pressures faced by frontline teams and ensure that gen AI-driven solutions enhance care delivery.”

Who’s Piloting The AI Ship?

The biggest takeaway here is that health system and hospital leadership doesn’t appear to have a firm AI governance strategy in mind. They’re differing not only on who should be in charge, but downplaying the infrastructure needed to ensure growth.

Healthcare executives taking part in the HealthLeaders AI in Clinical Care Mastermind program have voiced those concerns as well. William Sheahan, SVP and Chief Innovation Officer at MedStar Health, said leadership has to understand how data is gathered, stored and managed to get a good handle on the transformative potential of AI. That may include investing in data management technology that hasn’t been updated in decades.

"How do we get our people, our nurses, our doctors, our clinicians, our revenue cycle teams, to understand how the technology supports the future of their work?" he told HealthLeaders during an interview last year. "We can't just focus on deploying the fun new technology and expect that organically it's going to change your business, right?"

The survey’s authors say the industry’s conservative approach to technology is playing a role in this disconnect. Only about half of the executives surveyed report strong alignment between the organization’s overall strategy and its technology goals. And while 60% expect an ROI for AI within a year, 95% are anticipating only moderate ROI over the next five years because they aren’t investing enough in the infrastructure needed to maintain that pace of growth.

“This underinvestment puts healthcare organizations at risk of falling further behind — both in meeting the growing demand for care and in keeping pace with competitors who integrate technology and strategy seamlessly,” the authors noted.

What To Do About ROI?

The survey also offers interesting insights into how ROI is being measured.

When asked how gen AI would impact healthcare, executives were bullish on administrative improvements but not so sure about either clinician well-being or clinical outcomes.

According to the survey, when asked how gen AI would improve their organization, 83% cited increased employee efficiency and 82% said the technology would drive revenue growth, yet only 17% cited improved clinical decision-making and only 6% said the tools would empower patients.

In terms of outcomes, 82% of those surveyed listed revenue growth, while 77% mentioned productivity gains, but only 20% cited employee satisfaction, 9% cited either cost reduction or employee retention, and 6% cited error reduction.

This goes against the grain for a vast number of health systems and hospitals launching AI scribes, many of whom are focused on reducing clinician stress and burnout and improving workflows. It could also point out that while many are targeting workplace well-being, the emphasis is still on financial ROI.

Mastermind participants Roopa Foulger, Vice President of Digital and Innovation Development at OSF HealthCare, and Jonathan Handler, MD, OSF’s Senior Fellow for Innovation, said healthcare leadership is struggling to understand what ROI really entails.

“How do we measure it?” Handler asked during a HealthLeaders interview last year. “How do we assess it? How do we validate it? And I think that gets harder, not easier, with some of the new large language models and the generative AI that’s out there. Because now, instead of algorithms built on a use case by use case basis, you’ve got this general purpose model – how do you evaluate all the things that it can do?”

“There are so many other ways to measure the value that is created,” he added. “Determining the right things to measure, which may not always be the easiest things to measure, is critical.”

Plotting The Right AI Strategy

In its report, Accenture offered four steps that healthcare executives should take to make sure they’re on the right path for AI development:

1. Build a reinvention-ready digital core. “Leaders should prioritize initiatives and technology investments such as enhancing data quality, democratizing data access, migrating to the cloud and building robust data governance frameworks,” the report said. “These actions will create a flexible and adaptive digital core, ready to support emerging technologies.”
2. Strengthen data quality and strategy. “Organizations seeing strong returns on technology investments prioritize centralized data management and data modernization,” the report noted. “They ask critical questions such as: Are processes and tools connected across functions to provide shared access to data and analytics? Is the data standardized, secure and easy to use?”
3. Prioritize responsible and secure AI deployment. “An organization’s readiness to scale gen AI depends on its ability to manage, mitigate and protect against these and related risks,” the report said. “Proactive strategies can minimize downtime and reduce the risks posed by evolving threats and expanding attack surfaces. Continuous monitoring and assessment of technological constraints, data integrity and cybersecurity measures are essential for building resilience and enabling faster, more efficient recovery in the event of an incident. Secure scaling of AI also requires deploying tailored LLMs and developing a workforce skilled in harnessing these tools.”
4. Expand your base of expertise beyond your own people. “Increasingly, external influencers are driving transformation across healthcare, helping shape standards and practices that promote innovative approaches,” the report said. “Healthcare providers partnering with academic institutions or leading researchers are already seeing tangible benefits. One such collaboration led to the development of advanced care protocols, resulting in reduced patient recovery times and higher satisfaction rates. This effort also attracted additional funding and support, accelerating innovation and establishing a robust framework for future advancements.”