These days the term Artificial Intelligence (AI) is thrown around like so many other buzzwords of the past decade. Healthcare industry experts see it as “the next big thing” or as the ultimate disrupter on par with Uber. But how will it really change the state of healthcare? We sat down with QliqSOFT CEO and resident machine learning expert, Krishna Kurapati to get his take on the 5 Ways AI is changing healthcare.
What's the state of AI in the healthcare industry today?
Compared to other industries such as Retail and Finance, Healthcare lags in the use of AI. Probabilistic approaches, which AI is all about, do not work well in healthcare as it is often a question of life and death. Due to HIPAA compliance and the business practices of healthcare, particularly in the US, data lives on islands.
What's the #1 trend shaping AI in healthcare this year?
Natural Language Processing, which helps in reducing screen time and improves face to face encounters with patients has been the dominant use case of AI in Healthcare. Symptom checker has been popping up as the next wave of AI application.
What's the #1 challenge to AI adoption in healthcare?
AI thrives on Data. Lack of interoperability and data sharing are the reasons why it’s hard to get quality data to train AI models. Healthcare organizations and vendors need to work closely to find secure ways to share and utilize this data. In fact, I feel that hospitals are willing, but the vendors, especially the developers of many EHR platforms are reluctant to unlock their APIs for true interoperability to occur.
Technology is supposed to relieve bottlenecks and improve efficiency. Unfortunately, healthcare technology initiatives tend to create the opposite effect. Physicians today spend more time in front of their computer than in front of the patient. The greatest benefit Artificial Intelligence provides is the ability to free clinicians from devices and bring them closer to patients and aid in diagnosing and treating conditions based on the latest research.
What's the future of AI in healthcare?
Due to rising costs and cheap computing worldwide combined with an aging population, AI can manifest in many applications. We are already seeing shoots of such applications as Conversational AI Bots to help navigate patient journey to diagnosing cancer. AI will make significant strides as the US mandate to interoperability of healthcare data goes mainstream.
Krishna’s thoughts published here are just the tip of the iceberg when it comes to Healthcare and Artificial Intelligence. From natural language processing to “smart” agent escalation, the future holds great potential for this technology and QliqSOFT plans to be part of the conversation. Stay tuned to qliqsoft.com over the coming months to see how we are addressing AI and how we plan to incorporate Artificial Intelligence into our family of products.
Frequently Asked Questions (FAQs)
AI is increasingly appearing across many areas of healthcare, but the industry still lags behind sectors like retail and finance. Because care decisions can be a matter of life and death, and data is highly regulated under HIPAA, many health systems are cautious, and their data remains siloed on separate “islands.”
Healthcare adoption is slower mainly because AI requires large, high-quality datasets, which are hard to access in a HIPAA-regulated environment. Interoperability gaps and limited data sharing between EHR vendors and health systems make it challenging to train and deploy AI models at scale.
The biggest challenge is access to usable data. AI “thrives on data,” but a lack of interoperability and reluctance from some EHR vendors to open their APIs make it hard for organizations to securely share and use that data for training AI models.
AI’s most significant benefit is its ability to relieve bottlenecks and improve efficiency, allowing clinicians to spend more time with patients rather than on screens. By surfacing the latest research and insights at the point of care, AI can support diagnosis and treatment while bringing providers “back to the bedside.”
As computing costs drop and the population ages, AI will appear in more patient-facing use cases, such as conversational AI bots that guide patients through their journey, help schedule visits, or even assist with early cancer detection. Over time, improved data interoperability will enable these tools to leverage richer clinical information and deliver more personalized experiences.
Conversational AI bots are already being used to answer common questions, help patients navigate their care, and escalate complex issues to the proper care team member. According to the article, these bots are an early example of how AI will be embedded in routine healthcare workflows in the coming years.
Organizations can prepare by improving interoperability, working with vendors that support secure data sharing, and choosing HIPAA-compliant platforms built for AI-enabled workflows. Establishing strong data governance now makes it easier to safely deploy tools like NLP, symptom checkers, and conversational AI in the future.
The Author
Ben Henson
A lifelong communicator, this Tennessee native got his start in broadcast news before branching out into public media, corporate, communications, digital advertising, and integrated marketing. Prior to joining QliqSOFT as the company's first marketing team member, Ben shared his talents with organizations that include the University of Alabama, iHeartMedia, and The Kroger Company.