Undoubtedly, companies looking to stand out in today’s fragmented world must be focused on forging deep connections and building strong relationships with customers. Conversational AI can be a great tool to help them get there. So, how did the technology reach this point? What can it do for modern enterprises? And where will it go next?
Let’s examine the evolving nature of its development.
Chatbots, Virtual Assistants and Time Loops: The History of Conversational AI
You’re probably familiar with the experience of interacting with a bad chatbot (if you’re unlucky, you may have even interacted with one recently!). It usually starts with something like, “Please listen to our entire menu, as options may have changed,” and ends with you feeling trapped in a never-ending loop — and like you weren’t actually helped at all.
In the beginning, these conversational AI challenges stemmed from front-end issues: Building a chatbot required a fairly specialized skill set, one with both data science and engineering expertise. It could cost a great deal of time and money — not to mention dozens of experts and chatbot-dedicated software engineers — just to keep first-generation chatbots up and running. And, of course, above all else, they were simply less effective than they had the potential to be.
The technology was emerging, but it was emerging slowly.
The World Turned Upside Down: Expectations in a COVID-19 Reality
Prior to 2020, conversational AI technology had already begun making significant strides. However, the rise of COVID-19 sped things up at a breakneck pace. With customer expectations surrounding personalized and optimized consumer experiences already previously set by digital leaders like Amazon, the pandemic simply stood as an opportunity for those expectations to harden—and grow.
Despite supply chain issues and tectonic shifts in what it meant to be a consumer, the reality was—and is—simple: Consumers want the product, and they want it now. This is not going to change anytime soon. With an unpredictable future on the horizon—one clouded by the ongoing pandemic, climate change and constant technological disruption (just to name a few)—it has never been more important for companies to wield an agile and adaptable approach, one that will enable them to evolve and innovate regardless of what the world might look like.
As a result, chatbots and conversational AI—often the first line of defense for companies when interacting with customers—find themselves at a turning point. In this new reality, they must be equipped to both address the needs of remote workers and satisfy the demands of customers.
Fortunately, the technology is well on its way.
Backs to the Future: Where the Conversational AI Conversation is Headed
Look where we’re at today:
- The conversational AI market is expected to grow to $13.9 billion (from $4.8 billion in 2020) by 2025
- The technology has the potential to generate more than $2.6 trillion in overall business value
- By 2022, a full 70 percent of customer interactions are expected to involve related technologies
In this new generation of conversational AI technology, chatbots and virtual assistants are better equipped than ever. Today’s enhancements not only enable them to respond to human interaction with accurate predictive capabilities and personalized, specific responses—they enable them to learn and improve from every interaction.
In other words, conversational AI can now help modern businesses cost-effectively retain and expand their user and customer bases, engaging people in aggressive and competitive new business models. This means opening up new avenues to revenue, improving cost savings and, inevitably, growing the business.
So, what will this actually look like? In my conversations with executives and business leaders, the same themes come up again and again. Companies want the ability to train, build, test, connect and monitor AI-powered chatbots in a single interface, one that enables them to simplify tasks for workers and experiences for customers.
One example I like to point to in this area is that of SAP Conversational AI. The end-to-end, low-code chatbot platform shows what kind of solution the enterprises of today should be seeking out in order to be successful. For instance, conversational AI and RPA capabilities in SAP technology can help create an autonomous process ecosystem for an enterprise set on driving down process cost and improving process efficiencies. All in all, any leading conversational AI solution should carry the following:
- Tools for both outstanding customer and employee experiences
- Capability for a quick build—with integration into the overall technology ecosystem
- Automation of time-consuming business processes enabling resources to focus on value-added tasks
- Integration with enterprise process solutions
Simply put, no one can afford to ignore the increasing relevance of conversational AI in the COVID-19 landscape. Solutions must be frictionless, fast and accurate, and relationships with customers and users must be deep, powerful and lasting. Because, in the end, the companies that transform their business to stay ahead will be the companies that transform the future of customer experience—and reinvent the future of business itself.