Healthcare organizations need a new approach to data management to unlock GenAI’s potential

The last decade has seen its fair share of volatility in the healthcare industry. From the rise of value-based payment models to the upheaval caused by the pandemic to the transformation of technology used in everything from risk stratification to payment integrity, radical change has been the only constant for health plans. The emergence of generative artificial intelligence (GenAI) is the latest groundbreaking development to put payers to the test when it comes to staying nimble and competitive without taking unnecessary risks.

Since it burst onto the scene, GenAI has brought the potential to be a game-changing force for every industry it touches. But because of the expansive nature of its capabilities, many organizations are often paralyzed by the sheer breadth of possibilities. That’s especially true in the healthcare sector, where the dazzling future GenAI is trying to usher in is often limited by the shortcomings inside an organization’s legacy infrastructure.

In fact, a new report from Forrester Research found that most healthcare organizations are focused more on short-term experimentation than implementing a broader strategic vision for GenAI. The culprit keeping these aspirations in check? It is still the data.

Data management is the key

While GenAI adoption certainly has the power to unlock unrealized potential for all healthcare stakeholders, the reality is that the full power is never realized because of outdated data strategy.

The Forrester report found that companies’ key business goals are led by improving their member experience (42%), followed closely by improving customer data and security (40%) and boosting operational efficiency (35%). These are certainly all valid uses for GenAI, but the results reveal a surprising disconnect as well: just 19% of respondents want to enhance their ability to generate insights from customer data.

That’s a problem because operationalizing customer experience without a solid foundation of quality, findable customer data, and insights limits an organization’s opportunity to make a sustainable scalable impact. Ask any car enthusiast what it would like to own a Ferrari with a Vespa motor under the hood. That’s what it’s like to find a GenAI strategy on top of a poor data infrastructure.

Selecting the right AI partner

So how can organizations turbo-charge their AI efforts? For organizations to have responsible applications of AI, the technology needs to be woven into the fabric of their organizational strategies. Then and only then will AI be able to improve interoperability among payers, providers, and patients.

That starts with the realization of most healthcare organizations’ operational limits. These entities were established in an analog age, so before an organization can begin to implement any new technology, they must first look at the quality and integrity of their data. Our work at EXL has been focused on helping our healthcare clients craft a data-led approach to drive practical transformation. This includes how we deal with keeping private information private and how to eliminate gender and racial bias in any data-driven outputs.

Of course, to do that, an organization’s chosen AI partner needs to have the institutional knowledge that is required to interpret these specific data decisions. Healthcare organizations have so much data at their fingertips that trying to decipher it without an experienced partner can be akin to drinking from a fire hose. That’s why so many AI strategies simply don’t get off the ground. There simply isn’t enough time or resources to sift through the noise and see the bigger picture. With the right partner, that can change.

The time is now

The time has come for healthcare organizations to shift from GenAI experimentation to implementation. There is some evidence that this is happening on a smaller scale, as. But with the full power of GenAI behind them, that should just be a starting point.

As organizations continue to build on these initial successes, it is critical that leaders work with partners that can provide strategic, holistic support across data, analytics, and architecture, as they guide GenAI efforts for their organizations. As the complexity of health care grows with the explosion of data and protocols, the stakes have never been higher.

For more information about EXL’s solutions for the healthcare industry, click here.

Anita Mahon, executive vice president and global head of healthcare at EXL, a leading data analytics and digital operations and solutions company.