A Guide to the Use of AI in Healthcare: Deploying a Realistic Approach

AI offers healthcare organizations a unique opportunity to improve both operational performance and patient outcomes. From predictive analytics and clinical decision support to workflow automation and enhanced patient experiences, AI has the potential to fundamentally transform healthcare delivery. Yet despite the excitement surrounding the technology, many healthcare organizations remain in a discovery phase, working to determine which AI solutions deliver meaningful value and how to deploy them effectively.

As healthcare leaders evaluate AI investments, the greatest challenge is no longer whether AI can create value, but rather how to implement it strategically. Success requires moving beyond industry hype and focusing on practical use cases, organizational readiness, governance, and alignment with clinical and operational goals.

The following best practices can help healthcare organizations establish a realistic framework for AI adoption and deployment.

Assess current organizational challenges

While the healthcare industry has historically been slow to adopt new technologies, AI’s potential has created a sense of urgency to implement this technology. However, when developing an AI program, HIT executives must first evaluate top organizational obstacles to pinpoint where AI might have a tangible impact. While AI tool selection will ultimately be unique to each organization, it is helpful to understand common healthcare challenges that AI is solving.

Common pain points already being addressed through AI include:

• Administrative burden: Time spent on administrative tasks detracting from direct patient care. After-hours admin time often leads to low job satisfaction, clinical burnout, or employee turnover.
• Patient experiences: Evolving consumer-driven expectations push for more seamless, convenient, and efficient healthcare experiences.
• EHR workflow inefficiencies: Inefficient EHR system workflows often lead to issues like end user click fatigue, burnout, and patient safety concerns.

By understanding and prioritizing these organizational pain points, leaders can develop a more focused AI strategy that aligns technology investments with business needs.

Build strong governance with an AI steering committee

As healthcare organizations begin exploring AI solutions, establishing data governance early is critical. One of the most effective ways to do this is by creating an enterprise-wide AI steering committee. This committee should bring together experts from across the healthcare organization to jointly make AI decisions. Stakeholders should include leaders representing — but not limited to — operations, patient experience, ethics and health equity, compliance, data analytics, legal, security, and nursing/clinical champions. Once an expert internal team is aligned, consider inviting several AI experts from external markets, who better understand the complexities of AI models and algorithms. Collectively, a strong steering committee can help establish clear AI policies within a healthcare organization, addressing concerns such as privacy, bias, and safety.

Start small and scale strategically

According to a recent study, the number of healthcare AI product options are expected to expand five-fold by 2035. When considering numerous options, a best practice recommendation is to start with a modest approach and gradually scale in size or scope. By first referencing current use cases across the industry, healthcare organizations can select tools that have been proven to work in the healthcare space. Notable AI solutions that address clearly defined industry challenges include:

• Reducing administrative burden by introducing: Ambient clinical documentation, natural language processing (NLP) for EHR data input, or after visit summarizes powered by AI.
• Boosting patient experiences by introducing: Personalized patient support tools like interactive chatbots or SMS/texts, automated medical coding and billing support, or data-driven patient insights.
• Optimizing EHR systems and workflow by introducing: AI-enabled EHR integrations, automated data entry or patient records management, augmented clinical data parsing for greater diagnostics support, or AI powered treatment recommendations.

Ultimately, HIT leaders should take peer reviews or recommendations into consideration when making purchasing decisions. Selecting established tools will allow AI’s value to be more easily proven to various stakeholders, likely generating buy-in for custom solutions or additional AI utilization in the future.

Align AI initiatives with strategic goals and desired patient outcomes

AI should never exist as a standalone technology initiative. Instead, every deployment should directly support broader organizational priorities such as improving patient outcomes, expanding access to care, increasing operational efficiency, or enhancing clinician satisfaction. Technology leaders must evaluate each AI opportunity through the lens of the healthcare organization’s strategic roadmap and digital transformation objectives.

Healthcare organizations can achieve this alignment through several early-stage best practices. First, prepare for the evolution of this budding technology by utilizing AI tools within existing vendor partnerships, including your EHR vendor. Because partnerships are already in place, opportunities for AI collaboration will naturally expand, without significant risk. Next, it’s crucial to communicate to end users that skilled individuals are still essential for overseeing, operating, and managing AI. Consider adopting terms like “augmentation” within your organization, emphasizing that the goal is to support individuals, not substitute them. Also, prioritize the reduction of cognitive burdens for both clinical and non-clinical staff when implementing AI. Not only will end users be more inclined to adopt this technology, but the solution will garner maximum utilization.

Invest in organization-wide AI education

While 87% of healthcare professionals do not know the difference between machine learning and deep learning — according to research from the National Library of Medicine — 79% of respondents still believe that AI could be useful in their field of work. These results show that building technical awareness and emphasizing AI education is highly important in a healthcare organization’s AI journey. Therefore, HIT executives must prioritize education initiatives that help staff understand different types of AI technologies, appropriate use cases, potential benefits and limitations of AI tools, privacy and security considerations, and best practices for responsible use. These efforts can also help identify clinical champions who can advocate for future AI initiatives and provide valuable frontline feedback.

Patient education is equally important. In fact — according to the Pew Research Center — 60% of Americans would feel uncomfortable if their healthcare provider relied on AI for medical care. Healthcare organizations can offer educational materials and FAQs to emphasize the value of various AI solutions, potential health outcomes, as well as safety of new technologies to get patients on board. Teaching patients that AI is intended to support clinicians — not replace their expertise — can help reduce apprehension and foster greater trust in the technology.

Empower healthcare staff to find areas of opportunity for AI solutions

Some of the most valuable AI use cases are discovered by the individuals closest to the work. Frontline clinicians, nurses, administrative personnel, and support staff possess unique insights into workflow inefficiencies and repetitive tasks that may benefit from automation or augmentation. HIT executives might consider leadership rounding, departmental discussions, focus groups, innovation workshops, or AI idea-submission programs to gather employee feedback. Creating a collaborative environment between IT and non-IT staff can help build enthusiasm around technology initiatives that often feel overwhelming or disruptive. By involving employees early in the process, healthcare organizations can uncover valuable opportunities for AI adoption while fostering stronger engagement and ownership of new initiatives.

Strengthen vendor management and contract review processes

As AI capabilities become increasingly embedded within healthcare technology platforms, organizations must maintain rigorous vendor oversight. Leaders should review and update vendor contracts to address AI-specific considerations such as data ownership, data usage rights, security requirements, and regulatory compliance responsibilities. Additionally, vendor AI policies should align with a healthcare organization’s governance framework and risk management strategy. Establishing these expectations early helps protect organizational and patient interests as AI adoption grows.

Prepare for a rapidly evolving AI vendor landscape

According to research by Fortune Business Insights, the global market value for AI in healthcare is expected to grow from $19.54 billion in 2023 to $490.96 billion in 2032. Along with the projected growth, the AI vendor market will likely become increasingly saturated. Thus, we can expect vendor consolidation to ultimately occur.

Healthcare leaders should remain flexible and prepare for potential changes by maintaining visibility into:

• Which vendors access organizational data
• How data is being used
• Third-party relationships and dependencies
• Contingency plans for vendor transitions

Understanding the full data ecosystem will enable healthcare organizations to adapt more effectively as the market evolves.

Putting AI into practice

AI represents one of the most transformative technologies healthcare has seen in decades. However, successful adoption requires far more than simply purchasing new tools. Healthcare organizations must build a strong foundation through governance, education, strategic alignment, staff engagement, and risk management.

By assessing organizational challenges, establishing a steering committee, starting with proven use cases, investing in education, empowering frontline teams, strengthening vendor oversight, and maintaining a disciplined approach to risk, healthcare leaders can move beyond the hype and build AI programs that deliver meaningful value for patients, providers, and organizations alike. As AI continues to evolve, healthcare organizations that prioritize practical implementation and thoughtful governance will be best positioned for long-term success.

 

Ready to evaluate AI opportunities within your healthcare organization?
Med Tech Solutions helps healthcare leaders assess organizational readiness, strengthen governance, optimize workflows, and align emerging technologies with strategic goals. Connect with our team to discuss your healthcare AI initiatives.