While the ability for individuals with little to no coding experience to manage no- and low-code platforms is viewed positively , many of these platforms rely on pre-built content and do not offer much room for modification .
Consequently , businesses may have to settle for generic responses , chatbots that are not tailored to their specific needs , or voicebots that only admit specific commands .
Thus , the future of Conversational AI may involve the integration of no- and low-code platforms alongside pro-code platforms to achieve greater flexibility , scalability , and customization options .
NO- AND LOW-CODE VERSUS PRO-CODE PLATFORMS
No-code platforms provide a simplified way to create applications or workflows without requiring the user to write any code . They rely on pre-built templates with drag-and-drop features , which is a great option for individuals or businesses who need to create simple applications or automate basic processes , but who lack the technical expertise or resources to do so with programmatic coding .
Meanwhile , low-code platforms provide more flexibility than no-code platforms , but still require less coding knowledge than traditional pro-code development platforms . Low-code platforms typically provide a visual interface and drag-and-drop components that allow users to quickly build more complex applications or workflows , allowing for a higher degree of customization of content .
Pro-code platforms may also provide visual interfaces and pre-built components to help speed up the development process , but all components can be modified , and other custom components can be created .
Pro-code platforms therefore require trained developers who have advanced programming skills and can take full control over the development process . These platforms typically provide the most flexibility , scalability , and customization options , but also require a greater investment of time and resources to build and maintain .
To summarize , the value of no-code , low-code , and pro-code platforms depends on the user ' s skill level and the complexity of the project they are working on .
In the evolving landscape of Conversational AI applications in all business areas , such as contact centers where large amounts of customer requests are handled , businesses should strategically choose a platform based on their specific needs . They should consider factors such as the complexity of tasks to be automated and the level of customization required .
No-code and low-code platforms can be a great option for individuals or businesses with limited technical resources , such as start-up companies , while procode platforms provide the greatest level of control and customization for professional developers and enterprise contact centers .
... LOW-CODE PLATFORMS PROVIDE MORE FLEXI- BILITY THAN NO-CODE PLATFORMS , BUT STILL REQUIRE LESS CODING KNOWLEDGE THAN TRADITIONAL PRO-CODE DEVELOPMENT PLATFORMS .
LANGUAGE UNDERSTANDING MODELS MAY FALL SHORT
The language models powering no- and low-code chatbots have become much more sophisticated over the years . And with this there is an expectation that the language understanding of these platforms has also expanded . But you can ’ t have everything , right ?
The limit to customization means that businesses may not be able to fine tune no- or low-code language models to their specific requirements .
PLATFORMS
If there are certain parts of the user queries that are difficult to understand , such as product names or business-specific terminology , or responses that need adapting to suit the needs of a specific customer base , the code may be difficult or impossible to change .
A benefit of pro-code platforms is the ability to create a seamless experience in different channels , personalize them , and allow for integration with other language models such as GPT ( the model behind ChatGPT ), expanding on the possibilities for Conversational AI .
The launch of ChatGPT has put Conversational AI into the limelight due to its ability to understand and generate human-like text with fluency .
For those reasons , many have connected GPT with their technology . In the context of contact centers , this could mean leveraging advanced AI and linguistic modeling tools to enhance the automation of customer service processes and improve the CX .
ONE SIZE DOES NOT FIT ALL
No- and low-code platforms have been viewed as the future of Conversational AI development since they are agile solutions for businesses that want to incorporate bots into their customer service offerings .
But language understanding is just one part of the Conversational AI experience . In order for a conversational application to do its job successfully , it needs to respond in the correct way to deliver valuable customer outcomes . Otherwise , it will only make the customer frustrated and turn to customer service .
Chatbots and voicebots are used as an alternative to speaking to a live agent at a contact center . But if no-and lowcode bots are unable to answer customer queries , their value is very limited .
NOVEMBER 2023 15