Since the San Francisco-based research company OpenAI released its Conversational AI chatbot ChatGPT last month, the new bot, which leverages a mix of Artificial Intelligence (AI) and Machine Learning (ML), has gone extremely popular globally in a very short span.
Not only that, a media report claimed the new ChatGPT has forced Google to rethink the future of its search engine due to ChatGPT’s more advanced abilities. Does this make ChatGPT mature enough to solve real business problems?
Though that question sounds pretty straightforward, its answer isn’t that simple and linear. The fact that ChatGPT has further mainstreamed Generative AI by making it more accessible and yet enterprises would still need comprehensive Conversational AI solutions to make a business impact.
“For enterprises to connect with their end users and drive business impact, a more comprehensive end-to-end conversational AI solution is required,” says Jaya Kishore Reddy Gollareddy, CTO and Co-Founder of Yellow.ai – an enterprise conversational AI solutions provider.
“The success of conversational AI solutions depends on their ability to deliver a high-quality user experience. This includes being able to understand and respond accurately to the user’s input or perform a relevant action, and that too in a natural, human-like manner,” adds Gollareddy.
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.
“Conversational AI solutions also need to support integration with backend systems such as payment gateways, CRMs, and Contact Centre Platforms to pull and push relevant information in order to provide high levels of automation and subsequently greater ROI,” Gollareddy explains the technical aspects of Conversational AI.
In comparison, Gollareddy points out that ChatGPT (Generative Pre-trained Transformer) can as of now only fetch information and respond to the user’s prompts based on the knowledge fed to it during its training, but it lacks the ability to perform relevant action or integrate with the backend systems.
“For it to perform an action like fetching policy details or booking a flight, it needs access to third-party systems.Not only that, each business is highly distinct in nature; they have their own domain knowledge and sources that are very specific to their products and services and to the industry they operate in,” Gollareaddy elaborates on the real business scenario and technical challenges.
For businesses to leverage ChatGPT, Gollareddy says they would need to access the API to fine-tune ChatGPT with their own data and create their own variants of ChatGPT.
And that’s where Conversational AI companies like Yellow.ai, according to Gollareddy will be needed to bring in the orchestration of the chat layer and back-end systems, and allow enterprises to bring in their domain knowledge and create highly controlled conversational experiences.
“This will enable a fluid conversational experience customised for each business’s unique use case. Essentially, there’s still ground to cover in order for ChatGPT to be used effectively and accurately for enterprise use cases to solve real business problems at scale,” concludes Gollareddy.
(Image credit – Getty Images)