By Johnny Hecker, CRO and EVP Operations, Consensus Cloud Solutions.
“This is the year we must find ROI from AI.” That’s a common refrain at industry conferences this year, including in healthcare, where 77% of leaders believe the right moves around AI alone could boost productivity, reduce costs and improve revenue.
But too often, organizations aren’t getting the value they seek from their technology investments. That’s a challenge leaders must solve in 2025 if they are to gain immediate and long-term dividends from their approach.
Signs of “buyer’s remorse” around AI have become increasingly common. For instance, a recent Black Book survey found most AI systems aren’t living up to the hype in healthcare. Among IT execs surveyed, 96% say they’ve had trouble pinpointing the ROI from their investments. Nine out of ten say the AI systems they put into play are “not accurate or actionable enough in clinical settings.”
Meanwhile, 85% of early adopters that have deployed AI to automate diagnostics or treatment plans “saw little to no ROI.” Typically, this is because the technologies don’t match the complexities of a real-world clinical environment and aren’t focused on investments that can garner the greatest amount of return. Much of that may be due to the uncertainty a few years back regarding the best uses for AI. While the industry was noting they were developing an AI strategy, where to deploy was still a question.
The impact: Some organizations have reverted to manual processes to push “reset” on operational efficiency or have slowed implementation altogether, according to the survey. It’s an example of why leaders should look at AI investments not just from the perspective of what’s easy to implement, but also which technologies are likely to match the complexities of a real-world environment while keeping pace with rapid innovation.
A Cautionary Tale
The dangers of making the wrong decisions around technology investments extend beyond a blow to an organization’s bottom line. They also have the potential to cripple future investments.
In healthcare alone, Black Book estimates healthcare organizations are losing $8 billion annually to IT systems that are inefficient, ineffectively integrated with other technologies, and plagued with system downtimes. The failure of healthcare IT systems is predominantly attributed to poor user experience, cited by nearly half (48%) of professionals, which contributes significantly to provider burnout and decreased efficiency. The second most critical factor, identified by almost a quarter (24%) of respondents, is the lack of interoperability between systems. This deficiency results in data silos and hinders the seamless exchange of crucial patient information, further impeding effective healthcare delivery.
Interoperability breakdowns aren’t limited to healthcare, and they underscore the need to carefully consider which tech offerings to take on an organization’s digital journey. That means looking under the hood to make sure AI-powered technologies deliver expected results now, not soon. It also means questioning vendors about the extent to which its AI offerings match the organization’s needs, not just during the early adoption phase, but also long term.
Here are key considerations in determining which offerings to take on your AI journey.
How well will the AI offering complement other systems or workflows?
One of the reasons IT systems fail is that they don’t integrate well with other platforms. This leads to data silos—a problem leaders can’t afford to have if AI is in play, given that much of AI’s value depends on access to comprehensive, accurate data. Before investing in a new AI tool, whether from an existing vendor or another source, make sure that the tool will be a “team player” with other technologies and established workflows.
How does the offering fit within your business road map?
Adoption of an AI tool or platform should be viewed within the organization’s business needs and strategy. This requires a road map for AI adoption that guides leaders’ decision making, protecting the organization from decisions made in haste. To realize the potential of AI in the near future, a well-defined strategy is essential. Without a strategic approach, projects could die in the planning stage.
Prioritize vendors with a strong track record and demonstrated success.
A vendor with deep-rooted experience in your industry and a substantial customer base possesses a nuanced understanding of its unique challenges, data landscape and regulatory requirements. Consequently, their AI offerings are more likely to be tailored, effective and less prone to industry-specific pitfalls. Financial stability is a good indicator and ensures viability as a long-term strategic partner, and commitment to ongoing innovation and development.
By taking a pragmatic, carefully thought-out approach to AI investment, your organization can avoid instances where what seems like a good investment now lacks the intended value just a few years down the road.
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