Healthcare’s technology crisis is no longer hypothetical, but a daily reality shaping everything from patient safety to workforce morale. Frontline clinicians describe a workplace environment defined by sluggish systems, disjointed tools, and manual workarounds that add friction to even basic tasks and make it harder to deliver safe, timely care.
Presidio’s new report, “Unlocking Healthcare’s AI Potential,” brings together the voices of more than a thousand physicians and nurses across the U.S., U.K., and Ireland who live with these shortcomings every shift. Their experiences paint a picture of a system that is straining under the weight of outdated tools, even as new approaches offer a way to rebuild on stronger ground.
This article offers a high-level look at what those clinicians are saying, why it matters for organizational leaders, and how the full report can help you benchmark where you stand.
Use of Technology in Healthcare: Why Modernization is No Longer an Option
Across care settings, digital systems that once felt “good enough” are now clearly getting in the way. Many clinicians report that the tools they rely on are slow to respond, difficult to navigate, and poorly connected to one another, leaving them juggling multiple logins, duplicate data entry, and resorting to unsanctioned workarounds. A staggering 87% of those surveyed report that their current use of technology in healthcare does not meet their needs.
It’s a matter that goes far beyond convenience. Clinician respondents consistently link these day-to-day struggles to a deeper concern about patient safety, saying that outdated systems have become a source of errors and delays in care. When basic actions like accessing records, documenting patient notes, or coordinating with colleagues are delayed, the ripple effects show up in patient wait times, communication gaps, and missed opportunities to intervene sooner.
That connection between technology performance and clinical risk is what makes modernization absolutely essential. Today, leaders must look beyond incremental fixes and consider how a more connected, responsive, and intelligent digital environment could reduce friction and better protect the people in their care.
As the use of technology in healthcare moves from legacy to AI-powered systems, it’s important to reframe modernization as a core safety issue, rather than one of simple convenience. Today, fragmented tech systems are a structural vulnerability, and the organizations that move fastest on modernization will be best positioned to leverage healthcare AI for both short- and long-term resilience.
Related Read: Healthcare Data Fragmentation: The Patient Experience Problem Nobody Talks About
Why Frontline Voices Are Calling for Change
The strongest case for change comes from those closest to patients. Surveyed respondents emphasize how often they feel slowed down by their tools, and how frequently they find themselves building their own shortcuts just to get through the day.
Common examples include:
- Waiting on slow record systems to load or update information.
- Jumping between multiple platforms that don’t share data well.
- Lacking easy access to key details when working away from a desktop.
Over time, this constant friction takes a toll. Many clinicians describe feeling that their tools are working against them rather than for them, adding to cognitive load and contributing to emotional exhaustion. They also recognize that improvised fixes (e.g., exporting information into personal spreadsheets or using consumer apps to stay organized) can introduce new vulnerabilities for privacy, security, and compliance.
Frontline teams aren’t simply asking for more digital transformation tools, they’re asking for better ones: systems that are faster, more intuitive, and more aligned with real workflows at the bedside, in clinics, and in emergency settings.
Emerging Healthcare AI Trends that Will Shape the Future
Against this backdrop, interest in new forms of automation and data-driven support is growing quickly. Nearly all respondents (99%) in the report believe more advanced tools could have a positive impact on their organization if they were implemented thoughtfully and integrated with existing systems.
Clinicians see particular promise in tools that help them:
- Turn information into insight in real time, rather than relying on static reports.
- Reduce the number of repetitive, low-value tasks that eat into time with patients.
- Spot risks and opportunities sooner, based on patterns in the data that are hard to see manually.
At the same time, the report found that relatively few organizations have moved beyond pilot programs or narrow deployments. Many are still experimenting in specific departments or use cases, rather than weaving more advanced capabilities into everyday workflows.
This gap between perceived value and actual deployment is where healthcare AI trends are likely to move next. Organizations that accelerate AI technology integration — while staying grounded in clinical priorities — will set the pace for quality, safety, and competitive differentiation.
The full report digs into where early movers are focusing their efforts, how adoption varies by region and organization size, and which types of teams are feeling the benefits first. For leaders, those comparisons provide a useful lens on where the field is heading, and how far they may still need to go.
AI Applications in Healthcare: From Admin to Outcomes
One of the clearest themes to emerge from the survey is where clinicians most want and need help, and how AI applications and healthcare can support. When asked which tasks they would prioritize for intelligent automation or augmentation, they point first to work that feels necessary but draining: entering information, transcribing notes, navigating complex EHR systems, validating coverage, and handling routine documentation.
By reducing the amount of time spent on these repetitive tasks, clinicians hope to redirect attention to the parts of their role that matter most: talking with patients, collaborating with colleagues, and making complex decisions. Respondents also highlight opportunities for digital tools to surface recommendations, highlight potential concerns earlier, and support more consistent decision-making at the point of care.
Key Data Points:
- Real-time clinical decision support and workflow automation are identified as the AI applications with the quickest and broadest ROI.
- 52% cite automating data entry as the most critical opportunity for improvement, with similar interest in automating transcription and electronic health record (EHR) navigation.
- Teams already adopting AI cite measurable improvements to documentation, reporting, and even clinician satisfaction.
In organizations already deploying these capabilities, many clinicians report seeing improvements in areas like documentation quality, data analysis, and administrative workflows. This suggests that more advanced tools, when applied to clearly defined problems, can ease pressure on staff while setting the stage for better patient outcomes.
However, the report also underscores that the impact is not automatic. The difference between “hype” and real value often comes down to careful selection of use cases, robust training, and close alignment with clinical workflows.
The specific “what works” scenarios and use-case statistics are available for those ready to dig deeper. Download the full report.
Related Watch: Turning Clinical Conversations into Real-Time Action
Advantages and Disadvantages of Technology in Healthcare: Complex Realities
The survey findings make it clear that the advantages and disadvantages of technology in healthcare depend on how digital tools are designed and deployed.
While the majority of clinicians are quick to list the advantages: smoother operations, quicker access to the information, fewer manual steps, and more time for direct patient care; many also note that better tools can enhance their organization’s reputation and make it a more attractive place to work.
At the same time, the disadvantages of technology in healthcare are hard to ignore. Respondents link outdated or poorly implemented systems to increased stress, a higher risk of mistakes, and a sense that they are constantly fighting their tools. The report connects these experiences to broader themes like physician burnout, staff turnover, and difficulty recruiting and retaining skilled professionals.
Security and compliance add another layer of complexity. When people feel they cannot rely on official systems to get their work done, they often turn to unsanctioned apps or informal processes, which can leave sensitive information exposed. Leaders must therefore weigh both the advantages of implementing new tools as well as the risks of delaying upgrades or allowing improvised workarounds to proliferate.
Download the report to explore these tradeoffs in more detail, learn where organizations are seeing the greatest gains from modernization, and uncover where unintended consequences are already occurring.
Risks of AI in Healthcare and the Leadership Imperative
With shadow IT, privacy, and compliance surfacing as top issues, the mandate for responsible AI governance has never been clearer — or more critical.
As more organizations explore advanced analytics and automation, questions about oversight and accountability come to the forefront. The report found that risks of AI in healthcare don’t just come from tools themselves, but also from how they are selected, configured, and governed.
Examples include:
- Sensitive information being fed into external applications without proper safeguards.
- Staff using new tools without adequate training, leading to inconsistent or misunderstood results.
- A lack of clear policies about who is responsible when automated outputs influence decisions.
Leaders are being asked to navigate an increasingly delicate balance. Moving too slowly can leave clinicians stuck with failing systems and growing frustration, while moving too fast and without guardrails can introduce new risk. The healthcare systems that navigate this balance well will do so by creating governance structures, defining success metrics up front, and investing in communication and change management — not just in the technology itself.
Download the full report for AI in healthcare trends, stats, examples of what a responsible approach looks like in practice, and a starting point for organizations ready to move forward with confidence.
Technology, Talent, and Tomorrow: Preparing for What’s Next
Cumulatively, these findings suggest that decisions about digital tools are now inseparable from decisions about workforce and strategy. Clinicians in the survey repeatedly stress how much easier their work could be if they had reliable, real-time access to the right information and spent less time tied up in manual processes. They also connect better tools to reduced stress, lower risk of burnout, and a greater sense of professional satisfaction.
For healthcare leaders and organizations, this means investing in modern, intelligent systems to create an environment where staff can do their best work and patients can receive the best possible care. Those that move decisively to replace outdated, fragmented setups with more cohesive, responsive solutions are likely to stand out over the next several years.
This article only scratches the surface of what our recent research uncovered. The full report, “Unlocking Healthcare’s AI Potential,” offers a detailed view of where different regions and organization types are struggling, where they are succeeding, and which specific next steps leaders are taking to close the gap.
For teams looking to move from awareness to action and to help turn everyday frustration into a concrete roadmap for change, download the report today.
