When Will ChatGPT Be Ready for Business?
OpenAI, an artificial intelligence research lab, on Nov. 30 released ChatGPT, a prototype large-language AI chatbot that lets users ask questions and receive real-time answers. Users can ask follow-up questions and even challenge answers they feel are incorrect. ChatGPT can hold conversations, write essays, and even program computers. It can even remember the history of the conversations through contextual carryover.
The AI-powered chatbot, which has been programmed to simulate human conversation, is still in the research review phase, but it has already garnered a lot of attention. The ChatGPT software surpassed 1 million users less than a week after its launch.
While ChatGPT technology seems to be entertaining, there is some doubt about whether it can effectively be applied to the customer experience journey.
Even OpenAI CEO Sam Altman approached the technology with a cautionary tone. “ChatGPT is incredibly limited, but good enough at some things to create a misleading impression of greatness. It’s a mistake to be relying on it for anything important right now. It’s a preview of progress; we have lots of work to do on robustness and truthfulness,” he said in a blog post.
Beerud Sheth, CEO of Gupshup, a provider of conversational messaging, sees ChatGPT as “an impressive example of the training that goes into the creation of conversational AI.”
Sheth also thinks AI chatbots like ChatGPT could eventually yield high payoffs, citing a recent study by McKinsey & Co. that found companies are shifting their workloads away from transactional, repetitive queries to solution-oriented interactions.
Jaya Kishore Reddy Gollareddy, chief technology officer and cofounder of Yellow.ai, credits ChatGPT for mainstreaming generative AI, but warns that for companies to connect with their end users and drive business impact, a more comprehensive end-to-end conversational AI solution is needed.
“Businesses need to have control over the conversational flow. There must be control and understanding of the various conversational flows, intents, and utterances within each use case, which varies by business and industry,” he says.
“Conversational AI solutions also need to support integration with back-end systems, such as payment gateways, CRMs, and contact center platforms, to pull and push relevant information to users,” he continues.
“ChatGPT can, as of now, only fetch information and respond to users’ prompts based on the knowledge fed to it during its training, but it lacks the ability to perform a relevant action or integrate with back-end systems. For it to perform an action like fetching policy details or booking a flight, it needs access to third-party systems,” the Yellow.ai CTO says.
He also maintains that because all businesses are highly distinct and have their own unique domain knowledge and sources, “for them to leverage ChatGPT, they would need to access the API to fine-tune ChatGPT with their own data and create their own variants of ChatGPT.
“Essentially, there is still ground to cover for ChatGPT to be used effectively and accurately for enterprise use cases to solve real business problems at scale,” he concludes.
Yves Normandin, vice president of AI technologies at Waterfield Tech, shares that view.
“Though ChatGPT is an evolution of previous large language models, it really feels revolutionary because it’s uniquely optimized for conversations. It is actually remembering information exchanged in previous interactions. While that’s completely mind-blowing, for businesses wondering how they can leverage ChatGPT for their own benefit, it’s not yet clear how this technology can be effectively used to help create virtual agents, as its current limitations would be unacceptable for use in customer service,” he says.
ChatGPT, Normandin explains, “only knows the data it was trained on, so it cannot easily leverage external information, like customer data.
“There is also little control over what responses the model will generate, and it will often produce, with great confidence, incorrect or nonsensical answers that appear totally plausible,” he says further.
Customer-facing virtual agents, on the other hand, “must be trained to not only optimize conversation but to enhance business performance and elevate customer experience by leveraging a wide range of data. And the information they provide cannot be misleading or inaccurate,” Normandin says.
“While ChatGPT is undeniably interesting, there is still much to be learned before we can expect to see it practically applied in business without human oversight,” he concludes.