Is “execution paralysis” limiting AI success in healthcare?

There’s never been a shortage of incredibly powerful technologies designed for use in the healthcare industry. But there’s also never been a shortage of barriers, roadblocks, and caveats that have stopped many of these technologies from achieving broad adoption in a timely manner. 

Artificial intelligence is no exception to the rule, according to a new report from Guidehouse, which analyzed survey data collected by HIMSS in the summer of 2025. 

An AI environment filled with tensions

The report confirms the obviously strong interest in bringing AI tools into clinical and administrative workflows as quickly as possible, with 78% of health system leaders saying their organizations are already engaged in some type of AI implementation. 

But that doesn’t mean they’re comfortable with their odds of success. A large number of participants hinted that their organizations might be in the middle of “execution paralysis,” with particular concerns around safety and governance, that may be limiting success in the real-world operational environment. 

About half (48%) of respondents cited cybersecurity and data privacy as major impediments to AI implementation, while 42% said issues with governance and data quality were among their top organizational barriers. 

Just over a third (36%) said they weren’t internally aligned on strategy or didn’t have the in-house expertise to support successful AI implementation at scale.  That number becomes less surprising in light of the fact that C-suite executives are the ones pushing hardest for implementation, with 64% of execs eager to adopt AI compared to just 20% of non-executive IT leaders. 

The result is an environment of uncertainty in many organizations, where real concerns about viability and execution are rubbing up against a high-level vision for a more efficient, effective, automated healthcare ecosystem. 

“Healthcare is ahead of other industries in deploying AI with point solutions, but many leaders are struggling to articulate a cohesive enterprise-wide strategy,” said Erik Barnett, Guidehouse Partner and Payer/Provider Technology Leader. “This must be a priority for the entire C-suite—not just the CIO. Provider organizations need to identify the changes needed in their workforce, infrastructure, and processes to get the most value from both current and future AI investments.”  

The challenge will be closing these gaps in a way that balances appropriate safety and governance with the market forces compelling health systems to adopt AI as fast as they can. 

Strategies for getting on the path to AI success

Overcoming barriers around governance, cybersecurity, and strategic alignment will require organizations to take a close look at their existing processes and carefully select the most appropriate AI tools to soothe specific pain points, the report suggests.  

Establishing a comprehensive AI roadmap should be the first step. Start with evaluating the current digital environment and taking an inventory of applications, including both legacy tools and any AI-powered tools that have been adopted so far. 

Map these applications to an enterprise strategy that identifies where newer AI solutions could produce the most value, and don’t forget to develop standardized metrics to gauge whether these solutions are actually hitting their goals. 

Next is communicating the strategy to key stakeholders – not just before it gets put into action, but frequently and consistently during the process, as well.  These stakeholders should include leaders outside of just the IT department, such as representatives from clinical, administrative, compliance, finance, and other operational areas. 

Guidehouse suggests that organizations start with targeting easier wins that can produce measurable results to build confidence, work out any bugs, and provide tangible evidence of success to the executive team. Documenting everything as thoroughly as possible can help organizations start to create playbooks for future implementations so that they don’t have to reinvent the wheel every time. 

By taking a holistic and strategic approach to implementation, organizations can methodically worth through their challenges and achieve better results from AI solutions.  

Jennifer Bresnick is a journalist and freelance content creator with a decade of experience in the health IT industry.  Her work has focused on leveraging innovative technology tools to create value, improve health equity, and achieve the promises of the learning health system.  She can be reached at [email protected].