The healthcare C-suite faces a dilemma: technology investments, especially in AI, continue to grow, but returns from past implementations remain elusive. Many providers are being asked to rationalize their incremental technology spend, while still struggling to realize value from their existing technology stacks. For example, 71% of hospital executives said expenses have not decreased despite implementing digital tools, according to a 2024 survey by Atomik Research.
The conundrum for today’s healthcare leaders: Where should they invest more, and where is it better to maintain the status quo?
The reality: The right answers likely won’t come from this year’s flashiest, trending technologies.
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To win the AI arms race, executives must identify the true gaps in their digital ecosystems and focus on solving root problems. Yet too often, organizations bolt on tools to address a single symptom, only to end up with a fragmented, unscalable tech stack.
For many provider organizations, the contact center remains a critical access point that is overdue for improvement. To ensure AI and automation investments drive real value, healthcare leaders can apply the following three strategies to achieve stronger ROI and a more cohesive digital strategy.
1. Pinpoint operational pain points where AI can deliver immediate value
Provider organizations are facing the perfect storm of rising demand for services and ongoing staffing shortages. An Oliver Wyman analysis projects that by 2035, seniors will make up about one in every four Americans, significantly increasing demand for care, especially as nearly all older adults have at least one chronic condition. The same analysis found that the ratio of healthcare workers to seniors will drop from 3:1 today to 2:1 in 2035.
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Providers need to prepare now for the coming spike in demand. When it comes to core operational functions, scheduling is one example that presents challenges from both a staffing and patient experience perspective.
The AI opportunity in today’s call centers is already well documented. A recent Bland analysis highlighted the cost savings between a midsize enterprise call center of 20 full-time agents and an AI-powered customer support operation: from $700,000 to $270,000, annually.
For one multi-center ortho practice, AI in the call center delivers more than just cost reduction, it also helps reduce abandoned calls. Within the first month of implementing a Voice AI solution, the tool handled about 20% of daily routine patient calls, making it easier for patients to get through for appointment updates and scheduling without long hold times.
2. Evaluate the trade-offs before investing
There are many attention-grabbing AI solutions on the market. That’s why it’s important for provider organizations to avoid impulse purchases and ask key questions when considering the ROI potential of any investment:
- Does the solution reduce reliance on staff for repetitive tasks?
- Will it enable staff to work at the top of their license?
- Is it a meaningful upgrade or just a more polished version of an existing process?
- Will it directly improve patient acquisition and retention?
Self-scheduling tools are a strong example of practical AI and automation investments that check all the boxes above. Because patients increasingly expect these options, they naturally reduce inbound call volume, freeing up staff to focus on higher-level tasks.
3. Ensure AI solutions integrate with existing systems and workflows
The healthcare industry has learned some hard lessons from technology investments over the past two decades. The evolution of EHRs is a prime example. When the market became saturated with options, many solutions ultimately ended up in the IT graveyard, unable to keep up with advancing technologies or deliver the expected ROI.
Amid all the AI hype and noise, healthcare leaders must take a thoughtful, forward-looking approach to ensure technology strategies are both scalable and sustainable. This is especially important given the unique complexities within healthcare. A key question to ask: Will the new technology integrate seamlessly into existing workflows and enhance the patient experience over time?
It may seem like a table-stakes question, but in practice, many of the flashiest tools fail when faced with the realities of clinical operations.
Automating tasks like scheduling or routine patient calls might sound promising, until it becomes clear that the solution was built to work in a silo, ignoring existing provider rules or technology workflows. Leaders should not hesitate to ask tough, specific questions to ensure the AI “magic” will work in real-world conditions.
Providers stand to gain a lot by making smart AI and automation decisions, but that value depends on investing in the right places. It may be tempting to plug in a single-point solution to fix an immediate challenge, but a more strategic, long-term approach will unlock greater value. These strategies help ensure AI investments deliver strong ROI, address foundational problems rather than surface-level symptoms, and scale with the needs of the organization.
Picture: Warchi, Getty Images
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