Chief Development Officer
Is your revenue team ready for what's next?
Artificial intelligence (AI) holds a lot of promise. But not every business or technology has made good on the potential AI offers. There is no question about the value Conversational AI can offer; namely, the ability to automate human-like, two-way conversations with real people. But there are concerns about the actual generation of responses.
There are lots of examples of AI-driven chat delivering substandard responses in the past five years; Microsoft Tay and Nabla are prime examples. As a consequence, chat experiences are forced to stay dumb or limited to fixed definitions. Better to keep bots highly limited rather than toxic, right? Of course, this results in low utility, impersonal communication, and unsatisfying results. For better or worse, these once-promising chat experiences are only memorable for how bad they are.
But I’m not here to deflate your enthusiasm for AI-powered chat. On the contrary, I want to discuss how we can make good on the promises AI chat and Conversation Automation have to offer. This is what we’re calling next-gen chat—and it could make all the difference for your business, your revenue teams, and your customer experiences.
AI is already a part of our daily lives. Siri and Alexa can do some useful things for us—like setting timers, sharing calendar notifications, managing home devices, creating shopping lists, and conducting simple searches. These technologies have evolved quite a bit since they first hit the market and are continuing to improve with time.
Even so, the truth is that AI will be far more engaging if solutions can generate responses rather than just searching for them. What people want—and what businesses need—from AI is authentic and autonomous conversations that deliver real answers to questions, engage contacts, and drive contacts toward taking action.
GPT-3 (Generative Pre-trained Transformer 3) launched in mid-2020 and ignited enthusiasm about AI-powered chat all over again. The technology boasted the ability to use deep learning to intake text as a prompt, and then produce text that continues from that prompt. This is really cool because it allows a chat solution leveraging GPT-3 to deliver more natural responses.
For example: If an ecommerce customer is on the Nike website and asks, “What makes Michael Jordan an all-star?” The chat solutions, backed by GTP-3, could answer something like, “Michael Jordan is talented. He stressed the fundamentals and was a team player. Can I help you search for Air Jordans?”
Regrettably, the last two-plus years have—at times—felt more like just missing that winning Powerball number combination; so much anticipation, but then the realization that we need to go back to the status quo. Using that same Nike example, a customer might ask about “basketball shoes” and get served an answer about Adidas; which Nike surely wouldn’t appreciate. Clearly, we need a little more focus on specific audiences rather than just general audiences.
But does that mean it’s time to hit the brakes on AI-powered chat? Far from it. According to Jeff Burt, at The Register: “The AI space is expanding rapidly, with IDC analysts this year predicting the global market will grow an average of 18.6 percent a year through 2026, when it will hit $900 billion. OpenAI is focusing on what’s called artificial general intelligence (AGI), which is aimed at creating cognitive capabilities in software so that an AGI-based system could find a solution to an unfamiliar intellectual task in a fashion similar to humans.”
In this way, AI chat is essential to stay competitive and relevant with your customers. All the companies—from OpenAI to Facebook, Google to IBM, HuggingFace to Vectara—are making huge strides in their capabilities. Most notably, the ability to detect, filter, and exclude harmful and inappropriate information has evolved a millennium in a matter of months.
Nothing is perfect, but things are improving so rapidly that now is the moment to get into the game. To make these technologies a slam dunk, chat providers need to:
When you can achieve the goals addressed in the four bullet points above, you create truly engaging, personalized experiences that people remember and feel good about. As Brian Solis says in his book X: The Experience When Business Meets Design, “Experiences are more important than products now. In fact, experiences are products.” Applying these solutions to controlled domains around Conversation Automation is a perfect example of how you can drive remarkable and memorable experiences for your leads, customers, and contacts.
The best place to begin in the pursuit of this goal is finding ways for people to work alongside AI technologies—thus making people more productive and technology more human. LinkedIn Founder Reid Hoffman said recently, “In the next 5 years, every profession will have an AI co-pilot.” At Conversica, we are already seeing how AI and people work together to bring out the best in each other. Whether that’s in how our own revenue teams use our technology to how our customers use our technology.
By automating and scaling two-way, human-like conversations with our Revenue Digital Assistants, customers get the attention they need, when they need it—and revenue team members get to focus on the high-value conversations and relationship building that only people can deliver.
I want to quote Peter Diamandis one more time: “By the end of this decade, there are going to be two kinds of companies: those that are fully utilizing AI and those that are out of business.” That’s what we here at Conversica enable our customers to do. We empower businesses like yours to leverage Artificial Intelligence, Natural Language Understanding, and Natural Language Generation technologies to deliver iconic customer experiences that result in revenue opportunities. We are excited about the continued adoption and evolution of AI. And we dare say, next-gen chat is AI ready for prime time!
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