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The Truth About Conversational AI: 6 Myths Debunked

In today’s high-visibility, fast-paced world, healthcare providers (HCPs), patients and members of the general public want quick access to information about medicines, whenever they need it and how they want it. These needs have accelerated during the pandemic, with COVID vaccines and treatments being a hot topic for general discussion in the media, in conference rooms and at dining tables across the globe.

Life sciences companies have therefore faced unprecedented demand for information, unlike anything they have previously experienced. This has led them to set up medical information (MI) contact centers faster than ever before, staffed with more agents to handle the surge in inquiry volumes. Given that in-person interactions between sales representatives or medical science liaisons and customers have decreased during the pandemic, medical information contact centers and agents have become even more important, representing the face of the company. However, there is not an endless supply of qualified candidates well suited for work as skilled MI experts. Companies can no longer simply recruit more and more agents to handle inquiries and must look to digital solutions such as conversational AI-powered virtual agents to augment the customer experience.

The current generation of automated chat agents are nothing like the chatbots of the past. Today’s conversational AI agents use artificial intelligence and natural language processing to interpret even the most complex questions. They can instantly search vast databases to generate the exact right response using language that feels almost human. 

Yet many life sciences companies are still skeptical about how effective these AI agents are for use in MI applications – and what it will take to implement them. In many cases, their assumptions are incorrect, which is preventing them from taking advantage of the reduced costs, improved customer experience, and accelerated identification of adverse events and product quality complaints. 

AiThority Interview with Ingrid Burton, CMO at Quantcast

In response, our experts dispelled some of the most common myths they hear about conversational AI agents, to help industry leaders make more informed decisions about this groundbreaking technology.

6 Myths Debunked in Conversational AI

Myth #1: Healthcare Professionals Don’t Want to Talk to A Chatbot

While not universally false, many HCPs prefer engaging with an automated system over talking to a human representative. A 2020 Accenture survey found that 87 percent want either all-virtual or a mix of virtual and in-person interactions post-pandemic. 

The preference for automated agents has increased during the COVID-19 era, due to the fact that other information channels have become less accessible. The surge in inquiry demand has caused many life sciences companies to increase the utilization of conversational agents to support HCPs seeking fast and accurate information about COVID-related treatments and vaccines. It is a testament to the value of conversational AI in helping HCPs help themselves – but it only happens when manufacturers make these automated options visible and accessible to customers.

Myth #2: You Can’t Use The Same Conversational Agent Across Multiple Regions & Languages

The current generation of conversational AI agents are designed to meet the needs of global products and portfolios, through a combination of global and local training. 

When an agent needs to accommodate multiple languages and/or regulations, the global medical information team will first define a core set of master conversations, typically in English, that define acceptable responses to key inquiries. The local teams adapt the English masters for local languages and cultures, optimizing responses as needed. This interplay includes defining responses to common off-label questions and adjusting responses based on local labels, dosing measurements, and regulatory requirements. The local translations are then re-approved to ensure they are accurate and meet all requirements.

Myth #3: Conversational AI Agents Can Only Answer Basic Questions

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That might have been true ten years ago. But today’s conversational AI agents can answer a diverse set of complex questions with great accuracy. Because they are trained using the most relevant and recent data related to a product, they learn the correct answers to whatever questions are deemed pertinent and can reference that data in their responses. 

They can also access that data faster than any human agent, delivering easy-to-consume information about a product or condition in the channel of the user’s choice with no waiting. That leads to faster results and greater customer satisfaction. And when calls come in that AI agents aren’t trained to answer, they can escalate them and live agents have more time to focus on these unique, more demanding inquiries.

Myth #4: Conversational AI Agents Are Too Expensive for Small Companies

In reality, the cost of conversational AI is scaled to the scope and needs of the client. While large manufacturers may have multiple products, millions of requests, and a need for globalization, smaller companies often have smaller demands. 

Rolling out the technology for a smaller number of products, regions and languages will have lower costs. And these costs can be offset by the ability to reduce/ maintain the number of live agents currently on staff while continuing to meet the rising demands of customers.

Myth #5: Conversational AI Agents Will Steal Jobs

Life sciences companies will always need skilled human medical information professionals to answer inquiries, validate responses, and monitor the quality and flow of these interactions. Conversational AI agents can’t replace them, but they can take over many of the highly manual, time-consuming tasks, like responding to the same simple question over and over or listening to every recorded call to identify adverse event reports. Automated agents are better and faster at responding to simple inquiries and reviewing documents, freeing live agents to do more value-added work. They can also quickly translate content from multiple languages, making it possible for live agents to review every document in their preferred language. 

There aren’t enough trained medical information professionals to fill all the open positions in this industry. Conversational AI agents can pick up that slack without stealing anyone’s job.

Myth #6: Conversational AI for Medical Information Is Still Bleeding-Edge Technology

Conversational AI for medical information has become increasingly mainstream, especially during the pandemic. Life sciences companies are adopting these solutions to help them manage surging call volumes, while minimizing costs and risks in their workflows. And it won’t end when the pandemic ends.

AiThority Interview with Dhruv Asher, SVP of Business Development and Product Alliances at UiPath

Providers across various consumer industries have adopted digital solutions including conversational agents to manage customer interactions. HCPs and patients are no different than consumers and expect digital-first options from all their vendor engagements, including healthcare. They expect to be able to get answers in real-time, 24/7, regardless of the form or mechanism. The sooner life sciences companies adopt this technology, the more easily they will be able to meet customer needs, driving a better customer experience, while managing cost and risk across their product portfolio. The pandemic has heightened the need for digital solutions, and this is likely to become the norm moving forward.

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