Jenny was three months into her first job as a sales rep at a tech company when a question came up during online training about a new product feature that she didn’t fully understand. Her nerves took over, and she leaped into hard-sell mode, sounding like a used-car salesperson trying to unload a lemon. Sensing her discomfort, her trainer, a “digital human” named Sophie, provided gentle support, offered tips on how to handle the question and asked Jenny to try again.
Costly and inefficient training are pain points for managers. According to the Accenture Immersive Learning Survey, over 90% of executives agree that employee training methods must be more effective. They understand that training is best face-to-face, with lots of role-playing and empathetic feedback.
However, HR departments are challenged to deliver emotional feedback at scale, so it’s often done via video and text box-checking. Digital humans—delivered through life-like avatars—can help solve that problem.
What are digital humans?
Even though we depend on computers to live our lives, we’ve designed them to be mostly functional. We type into them, which is not a natural way to communicate. In 10 years, we won’t be typing much; we’ll be interacting with machines as if they are real people. Think about how far chatbots have come. Digital humans can engage and interact with people naturally and intuitively.
Generative AI will bring the next evolution, and computers will have more human qualities that can meet more of our emotional needs. The implications for training and performance feedback across an enterprise are far-reaching.
This is true especially for companies with large, disparate sales forces that sell complicated products and solutions. How can the lessons delivered through training be uniform, and still help individuals learn how to deal with other types of people with distinct and varied personas? They need those soft skills—like the ability to read other people’s cues, to listen actively and to not take rejection personally.
Making training and education more human is one thing that generative AI can do efficiently. Leveraging digital humans can help people develop soft skills essential for career success, like curiosity, patience and empathy. At scale.
Here are five ways.
Gaining trust with face-to-face interactions
People feel safe when they can see someone reacting to them because we’re hardwired to connect through nonverbal cues. It’s eye-to-eye contact, along with demeanor and posture, where emotions are assessed and reactions are formed. Think about the time that your snarky (but not mean) text was misunderstood. While what people say is important, it’s how they say it that matters most.
Digital humans powered by generative AI can mimic human emotions, like looking pleased, surprised or amused, which builds trust for the trainee. It also teaches the trainee how to read those nonverbal cues. And, because the training provides performance feedback, it tells you what you got wrong so that you can practice and improve.
Learning to adapt to different personas
The workplace is filled with different personalities, not all of whom are easy to deal with. AI can be designed for role-playing with “types”—from the easily persuaded to the persnickety to the skeptical. Unlike videos or text-based learning modules, AI can engage in nuanced conversations that flow.
To aid learning, the AI assesses soft skills like how objections are handled. What happens when you don’t know the answer? The simulations can include how to react to someone who is angry or frightened. It can teach how to help lower someone’s flight or fight risk.
It’s difficult to do that through voice only and almost impossible to teach that through text. It’s important to put up guardrails and guidelines. Watching how people react—even digital people—enhances how you learn to deal with people and their emotions.
Finding ways to communicate without judgment
Coaching via a digital human is suggestive, not prescriptive. Psychologists theorize that human-to-computer interaction can help comfort users and reduce negative emotions, perhaps because computers listen and respond, but they don’t judge. There’s a long history of psychology studies that show that people who are lonely, for example, have been comforted by chatbots because they are non-judgmental.
AI-generated people go a step further, adapting those theories and actually simulating human conversation.
Striving to eliminate bias by providing choice
When companies conduct in-person training, that trainer is a human being who likely comes in with biases and perspectives. Their personality and approach may not be a good fit for all. The AI trainer can represent multiple cultures, races, ages and sexes, and trainees can choose to be coached by a digital representation of someone they feel comfortable learning from. Similarly, AI can also be programmed to reflect different target audiences that people are more likely to interact with, amplifying the real-world impact of the training.
See also: Driving leadership development forward with a focus on relational skills
Humanizing feedback for performance reviews
Data that are collected provide crucial information and enable a real, live person to step in and offer assistance. The AI will deliver feedback and help achieve the goal of “practice makes perfect.” It also generates data about performance, noting where people are performing well and where they might need more support. Managers can use this data to help guide their own hands-on training, supporting their team members where they need it most.
Conversational AI helped Jenny learn about all of the ins and outs of the products she’s selling while simultaneously building her confidence to deal with many types of people. She became an effective salesperson far faster than the typical six to 12 months that it generally takes.
With remote and hybrid work environments the norm, there are many ways generative AI, like digital humans, can assist HR departments, whether it’s to better scale the onboarding of new employees or to reskill workers in fast-changing industries. We are all dependent on computers, so combining machines with human qualities to meet our emotional needs is a natural progression for the future of work.
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