Cognitive AI enables healthcare organizations to enhance patient engagement, personalize messaging, and improve operational efficiency, driving better outcomes and stronger business performance
Artificial intelligence (AI) has rapidly become a transformative force in healthcare, reshaping not only patient care but also how healthcare organizations communicate with their audiences. At the 2024 Global AI Conference hosted by 1ArtificialIntelligence, a panel of leading experts, including Amy Inzanti, Global Chief Insights & Strategy Officer at GCI Group; Kristin Mengel Ryan, EVP, US Head of Digital & Innovation at GCI Health; Bailey Roy, GSVP, Head of Research & Analytics at GCI Health; Zachary Schwitzky, Co-Founder of Limbik; and Jeff Sears, Global Head of Strategy, Operations, and Communications at Astellas Pharma, explored how cognitive AI is redefining health communications and accelerating business performance.
The Strategic Advantage of Cognitive AI in Health Communications
The healthcare industry has long sought better ways to engage patients, healthcare providers, and other stakeholders. Cognitive AI, which simulates human cognition to analyze vast amounts of data and generate insights, offers an unprecedented opportunity to achieve this goal. During the panel, Amy Inzanti emphasized how cognitive AI enables healthcare organizations to deliver personalized, timely communications that align with the needs and behaviors of their target audiences.
“At GCI Health, we’ve been tracking how AI can revolutionize communication strategies for some time,” Inzanti said. “Cognitive AI allows us to deploy content that resonates with specific patient segments, creating more meaningful and impactful interactions.”
This shift in communication strategy moves beyond generic outreach to a more nuanced, data-driven approach. Healthcare organizations can now customize messaging based on real-time insights into patient sentiment, behaviors, and engagement patterns. The result is more effective communication that not only improves health outcomes but also drives stronger business results.
Cognitive AI vs. Generative AI: Clarifying the Difference
Much of the excitement surrounding AI in recent years has focused on generative AI models, such as OpenAI’s ChatGPT, which create content based on input data. While powerful, generative AI primarily focuses on automating tasks. In contrast, cognitive AI simulates human thinking and decision-making, offering more sophisticated capabilities that go beyond content generation.
Kristin Mengel Ryan, EVP of Digital & Innovation at GCI Health, highlighted the key differences between the two: “Generative AI helps automate content creation, while cognitive AI replicates how we think, allowing it to analyze and understand complex data in a way that can guide more strategic communication decisions.”
For healthcare communicators, this distinction is critical. Generative AI might assist in drafting content, but cognitive AI can help predict how that content will be received by different audiences. By simulating human thought processes, cognitive AI provides insights that enable organizations to refine their messaging, ensuring that communications are culturally relevant, emotionally resonant, and, most importantly, effective.
Enhancing Efficiency and Driving Business Results
The business implications of cognitive AI are profound. Bailey Roy, GSVP and Head of Research & Analytics at GCI Health, discussed how cognitive AI streamlines data analysis and improves decision-making. “We’ve been able to integrate cognitive AI into our research and analytics processes, allowing us to spend more time on human analysis and strategic decision-making,” Roy explained.
By leveraging AI’s ability to process large datasets in real time, healthcare organizations can quickly identify trends and insights that would have previously taken weeks to uncover. This leads to more informed, agile decision-making, which is essential in a fast-moving healthcare landscape. Cognitive AI can also predict potential issues, such as patient dissatisfaction or emerging public health crises, allowing organizations to proactively address challenges before they escalate.
In healthcare, where patient trust is paramount, this predictive power can make the difference between success and failure. Roy noted, “For many of our clients, the ability to foresee challenges and adapt communications strategies accordingly has not only improved patient engagement but also enhanced their overall business performance.”
Navigating Ethical Considerations
As with any disruptive technology, the integration of AI into healthcare communications raises important ethical questions. Jeff Sears, Global Head of Strategy, Operations, and Communications at Astellas Pharma, stressed the importance of maintaining transparency and integrity in the use of AI, particularly when it comes to patient data and communication.
“AI has the potential to enhance communications, but it must be done responsibly,” Sears said. “We need to ensure that the data we’re using is accurate and that we’re not inadvertently spreading misinformation or compromising patient trust.”
Sears pointed to the risks of AI-generated content, referencing a recent case in which AI was used to create an image for a healthcare report that ultimately undermined the credibility of the organization’s findings. “Transparency is critical,” he said. “Organizations need to be clear when AI is being used and ensure that human oversight remains central to the process.”
Real-World Applications: Cognitive AI in Action
One of the most compelling aspects of cognitive AI is its ability to deliver real-time, actionable insights. Zachary Schwitzky, Co-Founder of Limbik, shared several examples of how cognitive AI is being used to streamline health communications. His company’s AI tools allow healthcare organizations to test messages with specific patient groups before deploying them, dramatically reducing the time and cost associated with traditional methods such as focus groups and surveys.
“Cognitive AI allows us to test content with patient proxies in under 10 seconds,” Schwitzky said. “This enables healthcare organizations to fine-tune their communications in ways that were previously impossible.”
Beyond message testing, cognitive AI can also be used to detect misinformation and mitigate reputational risks. Schwitzky explained how Limbik worked with the U.S. Department of Homeland Security during Operation Warp Speed to monitor vaccine hesitancy and track the narratives fueling it. “We were able to identify which narratives were driving hesitancy in different communities, allowing us to tailor communications that directly addressed those concerns,” he said.
This ability to anticipate and respond to misinformation in real time is a powerful tool for healthcare organizations navigating today’s information-rich environment.
Overcoming Barriers to Adoption
Despite its clear advantages, the widespread adoption of cognitive AI in healthcare communications is not without challenges. Many organizations are hesitant to invest in AI due to concerns about cost, complexity, and the potential displacement of human jobs. However, as Sears pointed out, these fears are often based on misconceptions.
“There’s a common misconception that AI will replace human jobs,” Sears said. “In reality, AI is a tool that enhances human capabilities. It allows healthcare professionals to focus on higher-level tasks, such as strategic thinking and patient care, rather than getting bogged down in manual data analysis.”
Sears also emphasized the importance of training and education in overcoming resistance to AI adoption. “To fully realize the benefits of cognitive AI, organizations need to invest in proper training and create a culture of experimentation,” he said. “By empowering employees to engage with AI and understand its potential, businesses can unlock new levels of efficiency and innovation.”
The Future of Cognitive AI in Healthcare
Looking ahead, the panelists were optimistic about the continued growth and evolution of cognitive AI in healthcare communications. Kristin Mengel Ryan predicted that as organizations become more comfortable with AI, the focus will shift from generative applications to more sophisticated, cognitive use cases. “We’re going to see a move away from transactional AI and towards more meaningful, personalized applications that deliver real value to patients and healthcare providers,” she said.
Zachary Schwitzky echoed this sentiment, adding that explainability will be a key factor in the future of cognitive AI. “As AI becomes more integrated into healthcare, users will need to understand how AI models arrive at their conclusions,” he said. “This transparency will be critical in building trust and ensuring the responsible use of AI.”
The panel concluded with a shared vision of AI’s potential to transform not only healthcare communications but the entire healthcare ecosystem. As cognitive AI continues to evolve, it promises to enhance patient engagement, improve health outcomes, and drive stronger business results—creating a future where healthcare is more personalized, efficient, and effective than ever before.
