Artificial Intelligence (AI) has existed since the 1950s1 but exploded in recent popularity as generative/conversational AI enables users to create written and visual content, flooding the educational and creative worlds with new capabilities but also placing the future of human content creation in question.
This level of AI integration may be years away from implementation – leading customer response companies like Twilio, Zendesk, and LiveAgent do not have the breadth of data training that conversational AI like Apple’s Siri, Amazon’s Alexa, and Google’s Assistant have access to – though partnerships are beginning like Twilio and OpenAI5 in 2023. Still, trends indicate a growing consumer acceptance of AI assistance. The percentage of customers preferring human interaction decreased from 86% in 20196 to 46% currently7 and organizations should explore how AI can free internal agents to prioritize the most complex member inquiries.
While customer-facing AI is still premature, companies like Tableau and Microsoft are targeting ways to integrate AI into analytics. Tableau’s generative EinsteinGPT assists dashboard builders in writing calculations and using features while Tableau Pulse uses Tableau AI to prompt more context for dashboard viewers8. Rival Microsoft is embedding AI capabilities in Power BI to detect anomalies and changes in Power BI9. Health plans, benefit managers, drug manufacturers, and other organizations will benefit from faster reporting to review drug pricing, rebate administration, and specialty utilization.
AI is also being used to potentially expedite drug discovery and delivery. A 2023 study titled “Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design” by Vora et al highlights how companies like BenevolentAI, Iktos, Insilico Medicine, and others are using AI to potentially discover new drugs and accelerate their development10. The authors stress that there is a strong need for human expertise to verify and refine algorithms, and developments may be stymied as the FDA expands their own framework for approving AI assisted drug development11.
The AI revolution will bring many advances to the pharmaceutical world in customer service, drug development, and internal operations, but adoption will be slower due to the complexities surrounding the drug delivery chain. United Healthcare12 and Cigna13 are both addressing lawsuits in their use of AI to deny claims, the FDA is still developing internal protocols for approving AI-assisted drug creations, and internal groups may struggle with the intricacies surrounding contractual guarantees but it is inevitable that AI will be embedded in all facets of the pharmaceutical world.