How to Implement AI in Clinical Practice

Artificial Intelligence (AI) is transforming the health care industry, offering unprecedented opportunities to improve patient outcomes, streamline administrative tasks, and enhance operational efficiency. However, adopting AI tools into clinical practice requires a well-defined strategy to ensure both successful tool selection as well as implementation. Failure to take a structured approach can lead to wasted resources, unmet expectations, frustration for all parties, and even possibly some ethical pitfalls. This comprehensive “How-to” guide will walk you through the essential steps of creating a robust AI strategy tailored to your clinical practice.

First understand that AI is a general term used to cover a wide array of technological tools aimed to help augment your clinical practice during both clinical care delivery and in some cases how you manage your business. But AI is just that, a tool. If you use the wrong tool for the wrong job, the job does not get done more efficiently or maybe at all. AI is comprised of many components such as machine learning, natural language processing, predictive analytics, and robotics. Many of these capabilities can be integrated into other technologies or can be used as stand-alone tools to make your life as a health care provider easier. AI tools can be used to detect diseases with greater accuracy, chatbots in the form of virtual health assistants can suggest tailored treatment regimens, and devices integrated with predictive analytics will be able to identify patients at risk of developing chronic diseases.

Step 1: Assessing Your Needs and Goals

Before adopting AI, evaluate the specific needs of your practice. Here is a checklist and explanation of your next steps. Ask yourself this series of questions in this order (do the work):

1. List the problems you currently struggle with in your business. See the “Issues Checklist” at the end of this article or download it here to see if your business currently struggles with these issues.
2. Prioritize the issue list according to the most important to solve now. Use the space next to your checked items to prioritize your issues 1-10 with 1 being the most urgent issue.
3. Define EXACTLY what your overarching goals are. Do this before you even consider an AI tool or another piece of technology. By defining what your goals are, you are also creating an objective measuring stick to judge what technology promises actual versus what it will actually deliver. People fail to write down goals for many reasons, but most people skip this step because they lack clarity about what they want. Be specific. Write it out. Use it as your guide! Examples might include:
   1. Enhance your social media presence by increasing views by 20%.
   2. Decrease the average exam time by five minutes per encounter.
   3. Improve patient online scheduling by 15%.
   4. Increase revenue per exam by $10.
   5. Decrease coverage eligibility time or determination by three minutes.

Step 2: Selecting the “Right” AI Tool

Now it is time to do a little research and select the right technology to solve your chosen issues. Remember, not all AI solutions are suitable for every clinical setting or every medical practice. Consider technologies that align with your needs and integrate seamlessly with existing systems. There are new AI tools being developed and released weekly, so be sure to visit AI in Eye Care for updated information on which tools might best serve your needs. Below is a list and explanation of a few key considerations as you do your research. It is a long list, but each item is a potential hurdle, so it is important to do the research now to avoid frustration later.

1. Integration/Interoperability: Does the technology or AI solution integrate with other technologies you currently have? Will you require other interfaces to connect technologies such as your EHR? In some cases, AI technologies may not require integration and may function as a stand-alone or completely different operating system. The take home is to be sure exactly what you are researching meets your needs without extra steps or headaches. This interoperability is essential.
2. Is the technology scalable to both the size of your current operation, and does it have bandwidth to expand as your business expands?
3. What type of data accessibility is necessary to reap the full benefit of the AI tool? Do you have access to this data, or does your EHR or diagnostic device effectively lock you out of access? Do you have sufficient volume of high-quality data to train and deploy the AI model that you are choosing? Where is that data coming from, and is the data accurate, complete, and consistent? The adage “garbage in garbage out” holds true here. Lack of good quality data will just lead to frustration.
4. Do you have the necessary IT infrastructure to support AI development and deployment? This includes computing power, storage, internet bandwidth, and software.
5. Do you have the in-house expertise to develop and manage AI projects? If not, will you need to partner with external vendors or hire specialized talent?
6. Do the “true” potential benefits outweigh the costs associated with acquiring and implementing AI solutions? This cost-benefit ratio is a key consideration.
7. Will this tool improve workflow efficiency? How does the company measure efficiency, and does that correspond with how you measure efficiency in your day-to-day activities?
8. Is the tool easy to use with minimal training or will there be extensive training necessary for each of your health care teams to be functional with the tool?
9. Is the AI tool compliant with regulations such as HIPAA and GDPR?
10. Is the tool easy to use for all parties in your practice who might be asked to use it? There is no quicker way to fail at implantation than to choose a technology that only a select few people have the training or ability to use.
11. Does the AI tool protect from outside attacks? Does the tool use encryption and other access controls to prevent unauthorized access to your patient data? (See our article this month February 2025 “The Battle for Security” for more details.)
12. Will the tool help reach goals or is it just cool? Talk to other people currently using the specific technology you are researching to get their feedback on the positives and negatives.
13. Finally, the gut check question! How likely is it that the project will be successful given the available resources and expertise? It is important not to let your emotions cloud your judgment in either a positive or negative way. Be aware of atychiphobia (fear of failure) and metathesiophobia (fear of change) that may prevent you from trying a truly game-changing technology that will alter your business trajectory. On the other side of the spectrum be cautious not to overestimate both what the tools can provide and how much work will be necessary to fully and correctly implement these technologies to see the gains that you are searching for. It takes equal parts of optimism, pessimism, and realism to achieve your goals.

Step 3: Staff Training and Change Management

Successful AI implementation depends on the willingness of staff to adopt innovative technologies. There are a few key steps in change management as it relates to your staff that are essential to your success.

1. Foster a culture of change and adoption. Successful implementation requires a cultural shift within your organization.
2. Have a meeting to introduce and educate your staff about AI and its potential benefits in your organization. Be prepared to answer questions about how it will impact what they do. Be sure to encourage them by sharing how these tools will positively affect both the care they provide and the happiness they derive from their jobs. Layout the general timeline and plan to implement. Do not rush this stage! It is important to get emotional buy-in if you want a successful implementation.
3. Conduct an AI literacy workshop where basic AI concepts are discussed. The purpose of this is to make your staff comfortable with terms. People are always much more likely to accept something they understand. Also remember that the staff will typically be the front line to explain the new AI tools to your patients and how they work. Create a glossary or cheat sheet! Allow them to ask lots of questions and provide answers in writing so they will be comfortable explaining it to patients.
4. At the time of your pilot testing (see below) have a meeting to demonstrate how AI will benefit them in their individual daily tasks. Give them tangible positive outcomes so they are more open to adoption. Always encourage feedback to refine AI implementation.
5. Have formal “implementation” staff training prior to full-scale implantation. Review how the tool impacts each step of the workflow. Leave time to discuss how these tools may positively or negatively affect the current workflow. Provide training on how to use the tools. Be sure to leave enough time to address any concerns or resistance to AI adoption.

Step 4: Implementing AI in Phases

To ensure a smooth transition, adopt a phased approach that includes these four steps:

1. Pilot Program: Before full-scale deployment, conduct small scale pilot tests to evaluate the performance of AI solutions in real-world settings. This involves selecting a representative sample of users, both patients and staff, to take part in the pilot program.
2. Evaluation: Assess AI performance, gather feedback, and address any challenges and adjust where necessary to improve utilization and ease of use.
3. Full Implementation: Once pilot testing and evaluation are complete, deploy AI solutions to the designated part of your business. This involves scaling up your infrastructure so you can successfully implement a full version of the tool. This is often the same time that full systemic integration with other tools and technologies such as EHR or other appropriate operating systems is necessary. This may often require additional training of your staff and in some cases necessitate minor changes in your existing workflow.
4. Continuous Improvement: Regularly update AI tools and refine workflows as discussed below.

Step 5: Monitoring and Evaluating AI Performance

Continuously monitor the performance of AI solutions to ensure they are meeting their objectives. This may initially be a weekly or even daily task. As both your staff and patients become more familiar and comfortable with the AI tools AND you work out many of the quirks of the tool this interval may extend to monthly or quarterly. Items that you will want to monitor include tracking key metrics that you established in the initial assessment stage. It also should include gathering user feedback, both positive and negative. Then you need to address and make positive steps to enhance and highlight the positives while planning to address the negatives. AI is an ongoing process. Continuously iterate and improve your AI solutions based on performance data and user feedback.

Step 6: Celebrate and NEXT

Congratulations, you are now an AI Innovator! Do not forget to celebrate your success with your team. You have now accomplished one of the greatest challenges in business: CHANGE! Take advantage of your success and the positive emotions and productivity associated with the change and focus on the second “issue” on your list. Follow the same rules. You are well on your way to a positive evolutionary shift in your business.

Developing an AI strategy for your practice requires careful planning, from assessing needs to implementing and evaluating solutions. By taking a structured approach, you can harness AI’s potential to enhance patient care, improve efficiency, streamline operations, and stay ahead in an evolving health care landscape. Remember that AI is a journey, not a destination. Continuous learning, adaptation, and collaboration are essential for realizing the full potential of AI in health care.

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