
Tech
Breaking the Cycle: Can AI Succeed Where Electronic Health Records Failed?
A decade and a half ago, the United States embarked on a well-funded quest to digitize medical records. More than $30 billion in federal incentives were channeled into accelerating the adoption of electronic health records (EHR). The vision back then was straightforward: if every hospital and clinic went digital, each patient’s data could follow them seamlessly from one provider to the next, saving time, reducing errors, and improving outcomes. That dream never quite materialized. While it is true that EHRs modernized record-keeping—no more paper charts vanishing between departments—the fully unified patient experience remained elusive.
Today, artificial intelligence (AI) has become the new focal point for healthcare innovation. Hospitals deploy predictive models to anticipate staffing shortages, technology firms boast advanced image-recognition algorithms for radiology, and entrepreneurs paint a future where AI-driven triage replaces waiting rooms. Yet the underlying question has stayed the same: Will technology truly serve the person trying to manage their health, or will it mainly optimize the business of medicine?
What the EHR era revealed was not a lack of funding or ambition, but rather a missing piece in how incentives were structured. Massive resources went into digitizing files, but far less attention was paid to designing systems that could talk to one another, let alone care for the end user. Vendors built out proprietary features that met immediate organizational needs—like billing or compliance—while patients found themselves juggling multiple portals. A single portal that displays a complete medical history across providers was the grand idea, but not necessarily the winning business model at the time.
Now, AI appears poised to bring unprecedented analytical power to healthcare, but the lesson from EHRs remains. Unless it is profitable—or at least strategically advantageous—for organizations to adopt consumer-centric technology, the marketplace alone may not yield tools that genuinely simplify a patient’s journey. Investors, after all, seek clear paths to returns. That can mean backing AI solutions that reduce administrative overhead or identify high-risk claims, which do address real system inefficiencies. Yet, these solutions do not always translate into improved billing transparency or a single go-to interface for all relevant medical data.
Still, incentives can be shifted in meaningful ways. The federal government, for instance, could tie reimbursement not only to cost savings or quality measures but also to the interoperability and usability of AI systems. Imagine a scenario in which providers are rewarded for offering patients real-time cost estimates or integrated scheduling that makes hopping between specialists as easy as booking seats on a plane. Under those conditions, an AI startup that promises seamless patient experiences would stand out as a more attractive option for hospitals looking to capture these additional reimbursements. That, in turn, could spark investor interest in consumer-facing ventures.
Another force that can move the needle is the growing consumer expectation for convenience. People have grown accustomed to streamlined digital experiences in other areas of their lives—one-click checkouts, user-friendly banking apps, and tailored streaming services. Healthcare lags far behind. As frustration mounts, some health systems already market themselves on their superior patient portals or telehealth offerings, hoping to attract and retain individuals by emphasizing ease of access. If this type of brand differentiation proves valuable—if patients vote with their feet or their insurance plans—then technology that genuinely improves consumer experiences could become an essential competitive advantage. Savvy investors might see such solutions as an avenue for long-term growth rather than a risky sideline.
Even philanthropic and impact-driven capital may come into play. Several foundations and socially conscious funds have pivoted to prioritize healthcare projects that show promise for underserved communities. If those entities commit to AI models that address both social equity and patient usability, capital could flow to startups focusing on inclusive data sets, intuitive interfaces, and culturally sensitive care pathways. Although such investments may not yield the fastest returns, they can carve out new markets and open doors to collaborations that mainstream investors eventually follow.
This is not to suggest that all AI in healthcare must cater exclusively to the patient-facing side to be worthwhile. Forecasting emergency room capacity or automating routine administrative work can free up resources for direct care. However, one should remain vigilant against repeating the EHR pattern: building massive digital infrastructures that predominantly serve organizational efficiency while leaving patients to navigate disconnected portals for themselves.
The bold talk of “transforming healthcare through AI” needs to be matched by structures that reward user-friendly design and data portability—structures that go beyond buzzwords. If regulators, insurers, employers, and the public push for common standards and transparency, it becomes less viable for technology vendors to cling to siloed data. If the business case for genuine patient empowerment is strengthened—through policy shifts, competitive branding, or philanthropic commitments—then investors have a clear reason to put their money into platforms that genuinely serve those who rely on healthcare every day.
Ultimately, the lesson from the EHR experiment is that billions in funding alone cannot guarantee a cohesive, user-oriented system. With AI now poised for center stage, the opportunity to correct that oversight has arrived. Whether these new algorithms simply reinforce a fragmented status quo or finally deliver a more unified, accessible healthcare experience for the patient depends on how effectively the incentives are aligned. The technology is ready; the question is whether the industry has learned enough to ensure the people at the heart of it all truly benefit this time around.