Using Digital Humans to Cut Costs, Provide Stronger Customer Experiences and Grow Faster

Digital humans represent the next stage in the evolution of “conversational AI”, a branch of artificial intelligence focused on understanding and responding to human language. Conceptual descendents of the humble chatbot, digital humans are capable of interpreting both spoken and nonverbal language, like body language and tone of voice, understanding context, and even interpreting emotional cues.

Paired with life-like, highly emotive, digitally animated human faces, digital humans are already being used by companies to provide a wide range of services to customers and employees. They have been built from the ground-up to be cheap and scalable, and to integrate easily with existing data structures and digital platforms.

To truly benefit from the use of digital humans in Pharma, however, businesses must understand their strengths and limitations, and especially how best to implement them. In this article, I explain what digital humans are and how they work, examine use cases in Pharma (and beyond), and cover three key steps for proper implementation.

What are digital humans and how do they work?

Digital humans are a type of “conversational” artificial intelligence, so called because they are designed to understand and respond to humans in a conversational fashion. In other words, in plain, spoken language.

However, there are few key characteristics that set them apart from more basic kinds of conversational AI, like early-generation chatbots.

First, they are able to understand both verbal and nonverbal forms of communication. Thus, a digital human analyzes not only what you’ve said—but how you said it, the expression on your face, and the position of your body. This gives digital humans the ability to interpret, understand and respond to emotional cues, and an emphasis on emotional intelligence has been central to the development of digital humans.

Next, digital humans excel at understanding context and lexical semantics. The best-in-class conversational AI Amelia, for example, exhibits deep contextual understanding, such that the order of information or the presence of multiple or conditional meanings is interpreted correctly. Amelia also features intelligent context switching, so that switching from questions on, say, how much a drug costs to known interactions to existing biosimilars doesn’t cause it confusion.

Third, digital humans are able to intelligently with structured or unstructured information and provide reasoned, intelligent responses to queries. Commercially available digital humans on the market today have been built to “plug and play” with virtually any dataset on the planet, be that patient medical records, a comprehensive drug interaction database, or practitioner customer data.

Finally, digital humans are usually paired with a digital “avatar” — an expressive, animated, three-dimensional face on the screen. Advances in 3D rendering, paired with the impressive computing power of modern devices like smartphones and laptop computers, has made it possible for digital humans to wear photo-realistic faces that can smile, frown, nod and everything in between. Presented with such a life-like interlocutor, humans tend to be more engaged, more trusting, and more satisfied with their digital interactions.

 
Digital humans vs chatbots

Digital humans are often seen as the successors of chatbots, and while that may be true in some sense, there are significant conceptual differences.

Think of it this way: chatbots are a bit like those old cars on a track they have at amusement parks. They can go forward and back, speed up and slow down… but the route itself is fixed. This is because chatbots are largely pre-scripted and pre-programmed. True, decision trees allow for some flexibility, but it’s not an inherently scalable model. And when a human says something unexpected, the car, frustratingly, is prone to stall (not a great customer experience).

Digital humans are more like an autonomous car with GPS. They can take you from some starting point—a request or query—and figure out a path from A to B to satisfy that request. It may require making a few turns, getting onto the freeway, or even making a quick U-turn if you just realized you forgot something back home. Rather than running on a track, digital humans are able to understand an objective and seek out the appropriate solution.

In terms of customer experience, it’s night and day.

Benefits of using digital humans

There are a number of benefits to adding digital humans to your business. They are very cheap, compared to equivalent human labor, especially when one considers that digital humans are always on, always available, and do not fatigue. They are easily scalable, and can serve five, five hundred or five thousand customers, provided sufficient computing power is at hand.

As mentioned above, commercially available digital humans are able to “plug into” APIs, databases and data lakes. Amelia, a digital human from the company Amelia.ai, can “connect to any system that has an API” and “run on any device that has a web browser, as well as in native mobile apps.” In a way, it’s like being able to transform any dataset into an interactive, intelligent, digital representative.

As an artificial intelligence deeply rooted in machine learning and natural language processing, digital humans are capable of learning from past experiences. Thus, they get better and better at whatever interactions they have been assigned to, be they practitioner- or patient-facing, clinical or marketing, internal or external.

Finally, many early adopters of digital humans have reported significantly improved customer satisfaction rates as a direct result of their implementation. Improved, even, from human customer service interactions. For example, Bank of America reduced their call center staff by 50% with a digital human and subsequently achieved higher customer satisfaction scores using the digital human rather than humans.