Conducting AI Counting: Three Ways Healthcare Leaders Can Drive True ROI

Healthcare C-Suite faces dilemma: Technological investments, especially in AI, continue to grow, but the returns from past implementations remain elusive. Many providers are asked to rationalize their incremental technology spending while still striving to realize value from their existing technology stacks. For example, according to Atomik Research's 2024 survey, 71% of hospital executives said that despite the implementation of digital tools, the costs have not been reduced.

The puzzles of healthcare leaders today: Where should they invest and where should they better maintain the status quo?

Reality: The correct answer probably won't come from the most gorgeous trending technology of the year.

To win the AI arms race, executives must identify the real gaps in their digital ecosystem and focus on solving root problems. However, organizations often use tools to address a single symptom, and end up with a fragmented, immeasurable technology stack.

For many provider organizations, the contact center remains a critical access point, an improved overdue access point. To ensure that AI and automation investment drive real value, healthcare leaders can adopt three strategies to achieve stronger ROI and more cohesive digital strategies.

1. Precise operational pain points, AI can provide value immediately

Provider organizations face the ideal storm of increasing demand for services and ongoing staffing shortages. Oliver Wyman's analysis predicts that by 2035, about one per four Americans will account for about one per person, greatly increasing the need for care, especially since almost all older people suffer from at least one chronic disease. The same analysis found that the ratio of healthcare workers to older adults will drop from 3:1 today to 2:1 in 2035.

Providers need to prepare immediately for the upcoming needs. In terms of core operational functions, scheduling is an example that presents challenges from the perspective of staffing and patient experience.

Today’s call center AI opportunities have been well documented. Recent bland analysis highlights cost savings from 20 full-time agents’ mid-sized enterprise call centers with AI-driven customer support operations: from $700,000 to $270,000 per year.

For a multi-center Ortho exercise, AI in a call center can not only reduce costs, but also help reduce abandoned calls. Within the first month of implementing the voice AI solution, the tool handled about 20% of daily patient calls, making it easier for patients to make appointment updates and schedules over extended periods of time.

2. Evaluate trade-offs before investing

There are many compelling AI solutions on the market. This is why it is important for provider organizations to avoid impulsive purchases and ask critical questions when considering the ROI of any investment:

• Will the solution reduce the dependence on people's repetitive tasks?
• Can it enable employees to work on top of their licenses?
• Is it a meaningful upgrade or a more polished version of the existing process?
• Will it directly improve patient acquisition and retention?

Self-making tools are a strong example of practical AI and automation investments that check all the boxes mentioned above. As patients increasingly expect these options, they naturally reduce inbound calls, allowing employees to release focus on advanced tasks.

3. Ensure AI solutions are integrated with existing systems and workflows

Over the past two decades, the healthcare industry has learned some hard lessons from technology investment. The evolution of EHRS is a good example. When the market becomes full of choices, many solutions end up in the IT cemetery, unable to keep up with the advancement of technology or provide the expected return on investment.

Amid all the AI hype and noise, healthcare leaders must adopt a thoughtful, forward-looking approach to ensure that technology strategies are both scalable and sustainable. This is especially important given the unique complexity in healthcare. A key question to ask: Will new technologies be seamlessly integrated into existing workflows and enhance the patient experience over time?

This may seem like a table problem, but in reality, many of the most gorgeous tools fail when faced with the reality of clinical operations.

Automated tasks such as scheduling or regular patient calls sound promising until it is obvious that the solution is working in the silo, ignoring existing provider rules or technical workflows. Leaders should not hesitate to ask tricky specific questions to ensure that AI “magic” will work in the real world.

Providers can make a lot of money by making smart AI and automated decisions, but that value depends on investing in the right place. It may be easy to insert a single point solution to solve direct challenges, but a more strategic long-term approach will unlock greater value. These strategies help ensure that AI investments provide a strong ROI, address underlying problems rather than surface symptoms, and scale to the needs of the organization.

Image: Woch, Getty Images

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