The AI Change Management Checklist: 4 Steps to Maximize ROI

Updated on April 20, 2024

You’re all in on AI for your practice. Maybe you bought a new solution or are considering one. Either way, you know big changes are coming to your industry. According to a Bain & Co. and KLAS Research report, around half of healthcare executives are developing an AI strategy for the near future. To keep up with your peers and competitors, you need to act now or risk falling behind, unable to keep pace with their improved patient experience, efficiency, and innovations. 

Even if you know the time to act on AI is now, there are still pieces to get into the right place. Knowing where to start can be overwhelming. You need to educate staff about AI, smoothly integrate it into your organization, and prioritize areas for improvement. So what’s the secret to implementing an effective change management strategy? 

4 boxes to check for a successful AI integration

Successful use of AI requires a game plan. It’s crucial to consider your practice’s unique needs, goals, and challenges. To that end, there is a straightforward framework to reap maximum ROI from AI through effective change management. Let’s look at how you can address four key areas.

1. Build organizational buy-in and set explicit goals.

People are vital to the success of your AI initiative. Your practice will feel the consequences if you can’t get employee buy-in – such as low morale among staff and slow adoption. As such, addressing the understandable concerns that some team members might have is critical. An efficient way to do this is with comprehensive training, open forums, and visible, accessible leaders to field questions and concerns. Fostering a culture of innovation and continuous learning can help encourage company-wide adoption.

With this backdrop, set explicit expectations for each AI project. Ensure all stakeholders are on the same page about what the project should deliver and, importantly, how these results will be measured. While this guidance may seem unremarkable, organizations occasionally allow their excitement about an AI opportunity to run ahead without pausing to set quantifiable expectations. By taking the time to anchor all stakeholders on measurable goals and a shared evaluation method in advance, your practice will have a smoother experience staying focused during implementation and arriving at meaningful ROI calculations.

2. Hold a great project kick-off meeting.

With the broader stage set at your organization, you now need to launch a specific project on a strong foot. Investing time and thought into coordinating the best kick-off meeting possible pays dividends for effective collaboration, adherence to timeline, and realization of project outcomes. While meeting and project styles vary by organization and vendor, some general tactics have proven effective in setting up the AI kick-off meeting for success.

First, before the kick-off, have project leads from the provider and the vendor meet to coordinate their roles and messages. Strong partnership between these visible leaders from the start sets the tone for joint ownership and a spirit of collaboration, framing both provider and vendor teams as on the same side, with shared goals.

At the start of the kick-off, build excitement by emphasizing the vision and your “why” for the AI project. Paint a picture of the future state: how it makes stakeholders’ day-to-day lives easier, improves outcomes for the provider organization, benefits patients, and any other relevant impacts. Then, establish working norms and processes, including means of communication, governance models, expectations around responsiveness, and other details. Reiterate the vision before proceeding to next steps so as to end the kick-off on a motivational note. By following these and other practices, you set your project up for success all the way from kick-off to go-live.

3. Engage in hyper-focused monitoring after go-live.

The secret to a successful integration begins in the early stages of implementation. Dedicating a period of time for intense monitoring helps to ensure alignment with your practice’s needs, identify areas for improvement, and control risks. By investing the time for this focused attention early on, your practice can build confidence in the solution and empower teams to lean into other projects.

Think of this period as a safety net where you catch any potential issues, such as data inaccuracies or workflow disruptions. This phase is your opportunity to stabilize the AI, ensuring it enhances your workflow seamlessly and performs as intended. You’re making the most of your resources available before people understandably need to allocate their time elsewhere.

By closely monitoring your AI system’s performance, you cultivate an environment where technology and staff can adapt together, reducing the likelihood that your employees will revert to old, less efficient workflows. This period of hyper focus is your commitment to making the transition as smooth as possible, and it allows you to demonstrate to your team that their efforts are supported. With the expected results achieved and validated during this phase, you can confidently scale up the AI project and begin to redirect resources to other organizational needs.

4. Capture learnings for a continuously refined AI playbook.

Whether a Chief AI Officer, AI governance group, or other in-house point person, selecting a person or group to steer the ship on your AI journey is critical to ensuring your AI efforts succeed and grow. This function centralizes leadership and accountability. It’s not just about navigating current initiatives, but mapping out AI’s role in your organization’s future.

Following the hyper-focused period for a new AI project, this group’s mission is to harvest valuable insights and distill them into a constantly evolving playbook for future projects, covering strategic goals, guidelines, team composition, performance metrics, and more.

This playbook will be an increasingly valuable asset as your AI system evolves. By updating it with every AI initiative, each iteration will be more informed and aligned with your organization’s goals than the last. These adjustments ensure that AI doesn’t just exist within your practice but thrives as a broader technological strategy while driving measurable value.

Benefits of a successful AI integration 

Getting started with AI can be intimidating, but it’s a proven way to enhance your healthcare operations. For example, the use of AI in medical coding is already dramatically transforming the healthcare industry, speeding up the revenue cycle, lowering costs, and making practices more efficient. Here are a couple of the benefits organizations will see. 

Transform coding from a cost center to a catalyst for growth: While remaining a necessity, what if medical coding could be a strategic function? AI accomplishes this by streamlining complex coding processes, significantly reducing the need for manual input and the associated overhead. AI in medical coding minimizes the likelihood of errors and rejected claims, freeing up resources. Doctors have more time to spend with patients and offer a higher quality of care, wait times are shorter, and patients have an overall better experience with your practice. 

Immediately impact ROI: AI coding’s impact on accuracy and efficiency can’t be emphasized enough. It’s like flipping a switch on ROI and seeing significant gains right away. AI’s accuracy and speed in coding mean claims are processed and reimbursed with fewer delays and denials, directly boosting your top and bottom lines. The technology optimizes coding opportunities, ensuring faster, more accurate reimbursements for all care delivered, while improving your practice’s cash flow. 

AI can be your catalyst for growth

Integrating any new technology into your organization can cause anxiety. But by following the steps outlined above, you can successfully deploy AI and realize the desired ROI.

Across administrative use cases, AI will streamline tasks so that your staff can spend more time on what matters most, like patient care. As for RCM, it’s no longer a bottleneck but a growth engine where claims are processed with unparalleled accuracy, minimizing delays and denials, translating directly to a stronger financial position.

As AI becomes more integrated into your operations, your practice will lead the charge in a new era of healthcare. Your early investment in AI will pay dividends, acting as a catalyst for change management and organizational growth.

Austin Ward copy
Austin Ward
Head of Growth at Fathom

Austin Ward is Head of Growth at Fathom, the leader in autonomous medical coding. He oversees the company's go-to-market efforts and client analytics. He brings broad experience in health systems, technology, and data science and has worked at BCG, the Bill & Melinda Gates Foundation, and in venture capital. He holds an MBA from Stanford University, MPA from Harvard University, and BAs from the University of Chicago.