Digital transformation has upgraded customer and employee experience unlike anything we’ve seen in a generation, putting data at everyone’s fingertips. Online interactions are becoming so smooth that often we can’t tell where the chatbot ends and human intervention begins. And this is only the beginning of what’s to come.
Generative AI promises to accelerate these changes. Trained on massive data sets, algorithms will grow more sophisticated and smarter, ultimately creating new frontiers in digitally enabled customer and employee experience.
Intelligently applied, generative AI will boost customer conversions and retention, elevate employee experience (EX) and customer experience (CX), and boost both efficiency and the bottom line. Where will the changes be felt most?
In wide-ranging conversations about the future of AI in the workplace, four experts point to the technology’s impact on employee training, self-service, and information sharing—though one questions whether AI is overhyped.
It may feel like generative AI is simply speeding things up, but it's actually changing HR processes completely. It has the potential to transform everything from hiring and onboarding to training and internal knowledge sharing. Companies can use AI to build instructional materials to train people and create automated quizzes, but it can also become a teaching assistant—so an employee can ask a bot, rather than the training manager, a question along the way. Companies can also build their own chatbots similar to ChatGPT, drawing on data from internal documents and HR information, so employees can do more than ask a question and be directed where to find the answer; they can take action, such as get a link to an HR form after asking about medical leave.
All this is powerful, but leaders will also need to address the challenge of controlling access to sensitive information. For instance, the AI must ensure that it provides executives with certain financial information that it restricts a junior employee from accessing. Most companies are just starting to figure this out, and it will involve IT lending a hand because there is no single off-the-shelf program that can do this now.
Josh Bersin, CEO, The Josh Bersin Company
Today, the customer journey is highly fragmented. There are multiple systems of engagement, and customers are interacting through support cases, chat, phone, forums, social media, and more. Similarly, support, engineering, and customer success teams are each using different tools. This fragments the information and experience for customers. Add to that a disparate workforce with employees with different skill sets who therefore aren’t able to provide a consistent experience for customers. When you introduce virtual agents, you produce even more fragmentation.
With AI, companies are highly focused on providing a complete, consistent, and unified experience for customers. Gone are the days of fragmented interactions, fragmented understanding of the customer, and incomplete solutions. Data insights can be part of daily workflows and allow a constant revisiting and reimagining of the entire customer journey. Such insights can now be used to impact our strategy, what we build, how we service, and how we ultimately support and retain our customers.
Judith Platz, Chief Customer Officer, SupportLogic
The promises of AI in the past involved allowing customers to self-serve because a worker shortage and low productivity meant a mediocre customer experience. It was always about trying to help customers so they could take care of themselves.
We've leapfrogged that technology and have arrived at machine learning, which can automatically act on behalf of the customer, marrying disparate data from inside an institution and remediating or responding to a situation in advance of a problem.
Generative AI will transform and expand self-service in areas like healthcare. In fact, it’s already happening. For example, AI can scour a patient’s medical records and identify conflicting recommendations without involving the patient. Oftentimes, doctors rely on patients to fill in the blanks and provide additional information, but patients don’t always know all the details or understand the complexity of the situation.
AI takes the burden off the consumer by automatically alerting providers of potential problems, such as adverse drug interactions. Doctors can look at the whole patient from a higher level, which can help them determine an appropriate course of action. This will improve the entire experience for the customer.
Kathy Sobus, Senior Director of Product Marketing, ConvergeOne
Generative AI will enhance systems and, using knowledge bases and unstructured data, improve functions like CX and EX. But it will not fundamentally change everything, as some people predict. When it comes to AI, we’ve been caught in a perpetual hype cycle. At the moment, it’s this notion that generative AI is going to change everything. That is mostly due to excitement about large language models and specifically ChatGPT, which is basically search and content generation on steroids.
Businesses must remember that embracing generative AI will require training and overhead, such as more cybersecurity and data management. Businesses must also decide how much control to give to these systems and whether they will trust the technology with brand messaging, customer service, and managing employees. I'm guessing the answer is very little, unless they’re reducing the cost to serve to zero, or almost zero, to save money. And that’s always a terrible idea.
Artificial intelligence as a whole will improve efficiency and help us find patterns in data. But we must always come back to the fact that it is humans who use the tools. Could we use AI to help us design a better customer service system? Yes, absolutely. But it’s going to be part of our tool set that enables us to do the analysis to best deploy how we engage customers and how we think about customer journeys.
Nikolas Badminton, Generative AI expert and Chief Futurist, Futurist.com
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For more than two decades, Jennifer Alsever has contributed to a wide variety of national publications, including Fortune Magazine, the New York Times, the Wall Street Journal, Wired, and Fast Company.