AI is already transforming the healthcare industry. Not only is AI analyzing data to support clinicians in their decision-making and driving operational efficiencies in administrative tasks in healthcare settings, but it’s even creating personalized treatment plans and empowering patients to monitor their health from home. There’s no shortage of use cases as healthcare organizations continue to explore AI’s potential at every level.
But despite the excitement that comes with integrating the technology, enterprises around the world are worried about the risks that come with AI in their operations – risks that are even more acute in highly regulated industries like healthcare. To mitigate these risks, healthcare organizations must build robust compliance frameworks before integrating AI into their operations. By doing this, clinicians and patients alike can more confidently benefit from AI across the healthcare journey.
High stakes of AI in healthcare
While many employees are eager to adopt AI, the industry as a whole is moving cautiously. According to Wolters Kluwer’s recent report titled “Generative AI: Balancing today’s needs and tomorrow’s vision,” data found that 63% of health professionals are prepared to use generative AI to optimize workflows within their departments, but only 18% were aware of any clear AI policies or trainings at their organizations. This gap highlights that while clinicians feel ready to use AI, healthcare businesses don’t have the right guardrails in place to safely leverage the technology given the heightened risks and sensitivities specific to the industry.
Patients are sharing this wariness. According to a recent Prosper Insights & Analytics survey, 86.7% of respondents on average across Boomers, Gen-X, Millennials and Gen-Z prefer to communicate with a live person over an AI chat program when looking for customer service assistance for health care matters. Beyond that, privacy violations are another major roadblock.
Prosper’s recent findings also noted that 87.7% of respondents are at least slightly concerned about privacy violations that stem from AI using their data, with 31.2% being extremely concerned.
These patient and clinician concerns about AI’s role in healthcare point to a broad hesitancy to leverage the technology across the industry. In fact, Wolters Kluwer’s recent survey found that 57% of health professionals overall believe generative AI may produce an “erosion of clinical decision-making skills caused by overreliance” on automated technologies.
To overcome these barriers, healthcare businesses must deploy AI responsibly, while prioritizing safety and creating a patient-centric experience. As organizations look to fully address AI’s transformative potential, these concerns must be addressed without compromising trust or quality of care.
Complying with AI regulations and standards in healthcare
AI in healthcare holds enormous promise, but amidst concerns from clinicians and patients, enterprises need to make risk mitigation a top priority to avoid costly missteps.
With privacy being a major concern on the patient side, healthcare businesses must implement safeguards for any interactions involving protected health information (PHI) due to HIPAA. For healthcare businesses looking to integrate AI and remain HIPAA compliant, they must prioritize the authorization, data minimization, and purpose limitation of PHI in AI technology, as well as data integrity and confidentiality clauses within HIPAA’s regulations. To ensure compliance, it is recommended that healthcare businesses develop and implement policies and procedures to cover the use of PHI in AI, such as AI governance, updated contracts, trainings, and more.
Infusing these guardrails into AI operations doesn’t just address privacy concerns, it also reduces patient hesitation when interacting with AI chatbots and provides clinicians with guidance where AI policies may be lacking.
“As AI increasingly plays a role in healthcare, safe integration isn’t just about meeting industry standards like HIPAA,” said Matt Blumberg, CEO at Markup AI. “Implementing proper safeguards addresses patient hesitation about interacting with AI tools, and ensures clinicians have clear AI policies to follow. Embedding this kind of oversight into workflows builds the trust and consistency patients expect across the entire healthcare experience.”
By embedding these safeguards and governance frameworks, healthcare organizations can safely unlock AI’s potential while protecting both patient trust and operational integrity.
Compliance shaping the future of healthcare
In any highly regulated industry, there are regulations and standards that must be upheld in many parts of the business, especially within the content an enterprise is producing. Compliance frameworks must be at the foundational level of any AI integration strategy to ensure alignment with these set rules and regulations, such as company AI standards, industry regulations, and brand guidelines. By leaning on them, healthcare organizations are relying on accurate information that aligns with company and industry standards.
Without a robust compliance strategy, businesses are at risk of legal, regulatory, and reputational issues. Particularly in healthcare, the consequences of non-compliant AI can result in incorrect treatment plans and privacy and security breaches, which ultimately result in negative patient interactions.
“Compliance frameworks are a necessity for any healthcare business looking to adopt AI responsibly. But having the right strategy is only part of the equation; you also need the right technology. Especially in high-stakes settings like healthcare, organizations need guardian agents – AI systems that monitor other AI – to ensure compliance in every interaction. Looking ahead, guardian agents will play a critical role in enabling smarter, safer, and more transformational healthcare interactions,” says Blumberg.
The missing link for responsible AI
With how quickly AI is continuing to change, the concerns and risks that come with the technology will only grow, and so too should the guidelines that are used to guide the technology. By leveraging these frameworks, healthcare businesses can protect confidential information, increase patient trust, and mitigate the variety of risks that come with AI use in their businesses. These frameworks will soon no longer be optional for businesses across industries; they will be a necessity.
