AI In Healthcare Comms: Enhancing Trust, Efficiency, And Compliance

By Jenna Phillips

Pharmaceutical companies are responsible for providing accurate, balanced, non-promotional information about their products to both patients and healthcare providers. In these points of contact, organizations also respond to reported side effects and product complaints and provide accurate and compliant information regarding in-market and in-development products. Contact center capabilities may be outsourced to vendors or partners that answer the queries on behalf of the pharmaceutical company or delivered by the company itself.

As AI becomes more commonly used in various healthcare settings, medical communication services are adopting new approaches to provide high quality information and customer experience for patients, caregivers, and healthcare providers who use the services.

Across industries, analysts report that 80% of companies are expected to have adopted or will be planning to adopt AI-powered chatbots or other AI-driven tools to support customer service use cases. In healthcare contexts, industry stakeholders report that automated call handling is an early use case for AI in contact centers with around 80% of calls already managed by AI platforms within defined scopes of work. Industry analysts expect the global healthcare call center AI market to grow at a CAGR of over 20% by 2030.

Introducing AI capabilities into call center operations produces efficiency gains and is reshaping how many parts of telehealth and virtual patient support services are delivered. Moreover, AI-based predictive analytics are being used to identify at-risk patients, proactively offer support, and predict appointment no-shows, further improving trial retention rates and outcomes.

By automating tedious processes like data entry, call routing, and post-call summaries, AI reduces average call handling times significantly and slashes labor costs. This is true across industries: Microsoft, for example, reported $500 million in annual savings after its transition to AI-driven systems. Furthermore, AI is enhancing customer engagement and experience, including for patients. Modern systems employ advanced natural language processing (NLP) to understand patient queries, provide personalized responses, and direct patients more accurately. Solutions such as RadiantGraph’s AI Voice Studio use HIPAA-compliant, individualized voice calls to support enrollment, medication adherence, and closure of care gaps. These approaches help boost metrics correlated with improved patient satisfaction and loyalty, including first-call resolution.

Challenges To Adopting AI Communications

However, the adoption of AI in this space is not without hurdles. Privacy concerns, potential algorithmic bias, and regulatory compliance are ongoing challenges. The implementation of laws like California’s AB 3030, which mandates transparency in AI-generated communication, reflects a growing scrutiny over the ethical use of artificial intelligence in healthcare. There is also some skepticism of its effectiveness upon adoption. A recent survey in the Journal of the American Medical Association, asked physicians about their views on the use of artificial intelligence tools in a clinical context. While the portion of physicians surveyed who reported that their enthusiasm exceeded their concerns with health AI increased between 2023 (30%) and 2024 (35%), a large segment remains unconverted to the value of fully embracing AI, citing reliability and potential impacts on patient trust as leading concerns.

As AI continues to develop, future advancements in agentic and generative models, coupled with improved data governance and regulatory clarity, are set to drive even greater adoption. The integration of multimodal AI that is capable of processing voice, text, and data simultaneously may offer the next leap in personalization and efficiency for healthcare call centers and, by extension, clinical trial success.

Tips For Transitioning To AI Communications

There are several best practices focused on operational readiness and implementation that can facilitate the transition and support pharmaceutical organizations’ need to meet regulatory requirements. Whether organizations take an insourced or outsourced approach, following these best practices will ultimately reassure patients, clinicians, and other stakeholders that AI is trustworthy and able to provide external-facing information about critical medicines in use or in development:

• Prioritize patient trust and compliance: Organizations must establish strict data governance policies, transparent communication practices, and regular audits to ensure privacy, security, and adherence to new regulations. Policies and procedures should be communicated to internal staff, as well as external stakeholders who are interacting with the AI tools. While it may seem obvious that AI chatbots should disclose that they are not a medical professional, recent analyses show that AI tools increasingly do not inform users that they are not human clinicians when interacting with users. Research published by the Kaiser Family Foundation found that most American adults are not confident that they can tell whether information from AI chatbots is true or false, raising a risk that patients will take unvalidated or inappropriate medical guidance from an AI chatbot, potentially resulting in negative health impacts. Furthermore, lack of disclosure presents a brand risk as well as a behavioral risk to patients who may not seek advice from healthcare providers for serious conditions.
• Upskill and engage staff: As AI tools appear poised to take over many of the human-driven, manual functions of call center and/or customer service operations, there is significant concern among frontline workers that they will lose their positions or have their experience devalued. These fears are not misplaced: A 2023 report by the World Economic Forum forecasted that AI will create 69 million jobs in the next five years but also will eliminate 83 million jobs. These sorts of statistics can be alarming to employees and can be detrimental to morale and productivity. To preserve organizational culture, morale, and efficacy, training and change management programs can help. These programs, delivered in a thoughtful way to staff can help to address concerns, build confidence in AI tools, and highlight their benefits to both patients and employees.
• Consider AI a supporter, not a replacement, of critical information-sharing capabilities. AI-enabled contact center organizations are likelier than their non-AI-enabled counterparts to grow quickly because of their speed, quality and scalability. The improved customer experience and issue resolution that the rapidly improving AI agents can deliver will necessarily change the ways of working for contact center staff. Legacy call center organizations must be prepared to pivot operational strategies as new AI-driven innovations and regulatory changes emerge. They must pay attention to the changes in technologies, capabilities, sales, and delivery approaches of their new competitors and adapt accordingly so they remain competitive, adopting technology quickly where it can make a difference to their operations.

Instead of treating AI as a competitor to their operations, legacy contact center companies should view AI as a partner that can automate the repetitive tasks of contact center management with effective tools, enabling the human workforce to focus where empathy and judgement are most essential. The capabilities of empathy, management of complex situations with good judgement, and sensitivity are especially critical in healthcare contexts, so human-driven contact centers in healthcare may be better able to thrive in an AI context than contact centers that operate in other industries.

As contact center organizations adopt AI tools to augment their operations, taking a phased approach that integrates AI in an incremental way can enable organizations to monitor results, gather feedback, and continue to adapt to the new ways of working.

About The Author:

Jenna Phillips is a health and life sciences expert at PA Consulting.