In the ever-changing healthcare arena, AI holds the promise to transform how consumers interact with medical services. Currently, consumers in the United States face numerous challenges, from finding the right insurance to understanding healthcare decisions. Many spend significant time researching and seeking answers. In fact, a quarter of surveyed consumers couldn't get the care they needed when needed.

Unlock the Power of AI in Healthcare Consumer Experience

How AI Can Revolutionize the Healthcare Landscape

In the rapidly evolving healthcare landscape, AI has the potential to reshape how consumers engage with medical services. Consumers in the US often struggle with various aspects such as insurance coverage, doctor consultations, and cost management. They spend hours researching and consulting others to find answers. A recent study showed that healthcare professionals preferred AI responses in social media forums, highlighting its quality and empathy.Some good news is that the healthcare sector recognizes the AI opportunity. Sixty-two percent of healthcare leaders in McKinsey's survey believe consumer engagement and experience have great potential with generative AI. Yet, only 29 percent have started implementing it.AI can help address these issues by enabling personalized care, enhancing transparency, and giving consumers more control over their health decisions. With the industry having ample data and a growing data volume, AI can extract valuable insights and curate experiences for variable consumer journeys.

Tackling the Data Readiness Challenge

Successful AI use requires integrated and ready data. For healthcare, this is a challenging task as data is fragmented across multiple platforms and in different formats. Healthcare organizations need to know what data to collect and how to connect sources. Even with a large data volume, gaps exist that prevent a holistic view of consumers. For example, care continuity issues make it hard to understand patients' needs. AI outputs can be biased without diverse data. Complementing clinical and patient data with other information is crucial.

Prioritizing Consumer Experience for AI Success

While assessing data readiness, leaders should also prioritize areas for AI investment based on overall priorities. AI can optimize administrative processes to reduce consumer touchpoints and costs. For providers, it may lead to fewer cancellations, and for payers, fewer follow-up calls. Engaging cross-functional leaders is essential to avoid doing too much at once. Clinical leadership has valuable insights into patient pain points.

Optimizing Real-time Insights for AI-powered Interventions

After establishing the data foundation and setting priorities, organizations need to contextualize the gathered data. AI models can develop a closer representation of consumer behavior by combining details from various sources. By analyzing appointment preferences and outreach responses, AI can tailor recommendations. Gen AI enhances the effectiveness of timed interventions with personalized message content.

Mapping AI Risks and Developing Mitigation Plans

Healthcare leaders face unique challenges due to consent requirements, privacy risks, and regulatory oversight. Consumers have limited ways to review and adjust consents. Organizations need to establish governance processes and provide transparency. As consumer expectations change, healthcare organizations face increased pressure to manage data. Evolving AI regulations add to the complexity. Cyberattacks on data repositories are a concern.

Enhancing Team's AI Capabilities

In the long term, provider organizations and payers need to invest in capabilities and talent. They must balance upskilling existing staff and hiring for AI skills. Partnering with third-party vendors can help move quickly. A copilot model allows employees to work with AI tools for incremental improvements, mitigating errors and risks. Testing and learning within a small set of users before scaling is crucial.Today, the healthcare ecosystem is often cumbersome and lacks personalization. AI can change this by enabling consumer-centricity. Building successful AI solutions requires an iterative approach, a controlled launch strategy, and key performance metrics. Executive commitment is key. Although it requires investments and risk mitigation, the benefits are worth it. Healthcare AI implementation can improve organizations and benefit consumers.