Do you think AI is the future of healthcare?

If you’re still thinking of it as “the next big thing,” you’re falling behind. AI (Artificial Intelligence) is not the future; it's today’s reality.

In 2024, 43% of medical groups had adopted AI tools, and in 2025, 32% are making it their top priority. The investment trend underscores this shift: global funding for AI-driven digital health companies surged from just 7% in 2015 to 42% in 2024.

AI has proven to boost practice efficiency, improve patient outcomes, and cut administrative costs. But what many fail to understand is that AI isn’t a magic fix. Successful implementation requires a strategic AI blueprint, without which organizations risk wasted investments, failed integrations, and serious security vulnerabilities. A foolproof strategic plan is the key to unlocking AI’s full potential in your practice.

So why wait? Here’s a structured action plan to ensure AI adoption leads to measurable, lasting improvements.

1. Evaluate Existing Systems

First off, congratulations! You’ve already laid the foundation for AI in your practice.

Don’t believe me? Think about it. Your existing cloud systems, medical devices, EHRs, and digital tools were all implemented to streamline workflows and improve efficiency. In many ways, these are the building blocks of AI.

On paper, they should make your job easier. But are they seamlessly working together or creating more headaches?

Many healthcare organizations still struggle with outdated EHRs, fragmented data silos, and inefficient workflows, creating bottlenecks that slow down operations.

Analyze your existing systems and identify the pain points where AI can make the most significant impact. Ask yourself:

• How much time do staff spend on non-clinical tasks?
• Are administrative tasks (scheduling, billing, documentation) automated or still manual?
• How easily can providers access and retrieve patient records?
• How long does it take to process insurance claims and payments?
• Is your current EHR system AI-compatible?

2. Spot The Gaps

Once you’ve assessed your existing infrastructure, the next step is to locate areas where AI remains underutilized and identify opportunities for meaningful impact. A thorough gap analysis will help uncover inefficiencies, redundancies, and overlooked AI capabilities that could optimize workflows and improve outcomes.

Evaluate whether you’re maximizing the potential of your existing technology. You may have AI-powered tools embedded within your systems without realizing their full potential.

Here are some common areas where AI capabilities often go untapped:

• Medical Imaging Systems: Many systems have built-in AI-driven analysis to enhance diagnostic accuracy. Yet, some practices rely solely on manual interpretation, missing opportunities for faster and more precise readings.
• Scheduling Platforms: AI-powered predictive tools can optimize appointment scheduling and reduce no-shows. However, if these features aren’t activated, inefficiencies may persist, leading to lost revenue and gaps in patient care.
• Data Centers, Cloud Services, and Network Systems: AI is often built into these platforms for security monitoring, threat detection, and system performance optimization. Yet, many organizations fail to tap into these advanced capabilities, leaving their infrastructure vulnerable to cyber threats.

AI is often scattered across different systems in medical practices, operating in silos instead of working together seamlessly. This fragmentation holds back its full potential. These gaps aren't just inefficiencies; they highlight missed opportunities to streamline workflows, improve patient care, and cut costs. Identifying areas where AI is underutilized or disconnected helps you take a more strategic approach to integration. The goal isn’t just to have AI but to ensure it works cohesively across your practice, enhancing efficiency, supporting clinical decisions, and delivering real value where it matters most.

‎3. Define Clear Objectives

Your medical practice has unique goals and challenges. That’s why adopting a blanket approach to AI adoption doesn’t work; it rarely delivers optimal results and is a wasted investment. 

Instead of adopting AI just because it’s the latest trend, define specific, data-driven outcomes that AI should help you achieve. These objectives should be SMART (Specific, Measurable, Achievable, Relevant, and Time-bound). It could be:

• Reducing administrative workload by 30% within six months 
• Improving diagnostic accuracy by 20% 
• Decreasing no-show rates by 25% 
• Cutting revenue cycle delays by 40% 
• Enhancing patient triage and treatment planning 

Setting measurable benchmarks helps track AI’s effectiveness, justify investments, and refine strategies. A clear roadmap ensures AI isn’t just another tech upgrade but a strategic asset driving real improvements. 

4. Roll Out In Phases

A rushed, all-at-once AI overhaul is a recipe for disaster. Implementing AI across all systems simultaneously can lead to workflow disruptions, staff resistance, and costly integration failures. Instead, a phased approach ensures smoother adoption, minimizes operational risks, and allows for continuous refinement based on real-world feedback.

Start with the low-hanging fruit. Many healthcare organizations already have AI-powered features built into their existing systems, which remain unused. Activating dormant AI capabilities in EHRs, scheduling platforms, revenue cycle management tools, and imaging systems can deliver immediate value with minimal effort. It also builds confidence in AI adoption while demonstrating quick, measurable improvements.

Simultaneously, it's imperative to invest in staff training. AI is only as effective as the people using it. Many AI projects fail not because of flawed technology but due to poor adoption rates. Often, staff lack the expertise to use it in their daily workflows. Comprehensive training programs empower your team to harness AI's full potential.

Next, focus on interoperability; connecting AI across different departments. AI thrives on data, and its effectiveness depends on the quality and accessibility of that data. Without integration, AI remains trapped in silos, producing fragmented insights that fail to support accurate decision-making. To unlock its full potential, AI requires seamless access to comprehensive data, making interoperability vital.

For example, an AI-powered EHR that integrates with scheduling and billing systems can automate prior authorizations, optimize staff allocation, and reduce claim denials. Similarly, AI systems can prevent unnecessary ER visits by alerting physicians to high-risk patients based on real-time vitals from remote monitoring devices. Simultaneously, they can notify the billing teams to verify coverage for necessary interventions. Such interconnected AI solutions break down silos, improve workflow automation, and enhance provider and patient experiences.

5. Lock Down Security

No matter how advanced your AI systems are, data security is non-negotiable. Healthcare organizations handle vast amounts of sensitive patient information, making them prime targets for cyberattacks. The Change Healthcare breach, which affected 190 million individuals, is a stark reminder of the risks involved.

AI adoption brings incredible efficiencies, but it also introduces new vulnerabilities. Without robust security protocols, AI-driven systems can become entry points for cyber threats, data leaks, and compliance violations. 

Bolster your cybersecurity measures and ensure you:

• Adhere to HIPAA privacy rules.
• Employ advanced encryption techniques to secure patient data at rest and in transit.
• Leverage AI-driven threat detection for proactive security.
• Restrict system access to authorized personnel only.

Time to Activate AI!

Success with AI is more than about jumping on the trend; it’s about integrating it with purpose and precision. Glenwood Systems has spent decades navigating the complex healthcare landscape, helping private practices overcome operational hurdles with cutting-edge practice management technology.

Now, with the power of AI, we’re taking efficiency and accuracy to the next level. Our AI-driven practice management tools (GlaceEMR, GlaceRCM, GlaceScribe, GlacePhoneSmart, and GlaceBillSmart) automate tedious administrative tasks, streamline revenue cycle processes, and enhance clinical decision-making. With expert guidance and hands-on support, we guarantee a seamless AI integration process tailored to your practice’s unique needs. Whether you're unlocking dormant AI capabilities in your existing systems or expanding AI’s role in clinical and administrative workflows, we help you harness its full potential.

The future of healthcare is here. It’s time to work smarter, not harder! Let AI drive your practice forward.