Virtual assistants are valuable, transformative business tools that offer a compelling ROI while improving the customer experience. By 2030, conversational AI chatbots and virtual assistants will handle 30% of interactions that would have otherwise been handled by a human agent—up from 2% in 2022.[i] So why haven’t more companies adopted this solution? 

Due to the maturity and complexity of the technology, it can take years to reap the full benefits of developing a conversational AI platform. One challenge to implementing conversational AI from core Natural Language AI technology is that it requires expensive technical specialists. These specialists (data analytics, AI and graph technologies) are often in short supply and typically require annual salaries of $175,000 or more.[ii] But for most companies there is a simpler, cost-effective way to create a chatbot for the ideal support experience.  

A multitude of solutions to create and maintain virtual assistants to improve customer service.  

Keep in mind that not all pre-built tools are the same. Historically, conversational AI solutions have fallen into one of two categories:  

Simple to use solutions

These tools make it easy to start working with conversational AI but in the end offer sub-par customer experiences. Typically, the answers are hardcoded or use minimal AI or machine learning. These chatbots are programmed to give exact answers to specific questions — if client says this, then say this, if client says that, then say this. 10 times out of 10 they will give the same answer regardless of whether it is right or wrong.  

Robust solutions that can create powerful experiences

On the other end of the spectrum are these tools which allow you to create the type of experiences your customers expect, but they’re often very complex (and expensive) to use. For instance, they may have robust natural language processing powering their AI but to build a customer facing solution requires a degree in computer science and a front-end developer to create the experience and embed it into your website. 

watsonx Assistant changes the game with actions and the low code/no code interface  

You may feel limited by expensive AI solutions that require a wide variety of tools and technologies to build, integrate with existing systems, and operate at scale to meet peek customer demand. If your organization is not equipped to develop conversational AI applications to handle dialog and process and understand natural language, consider a Conversation AI platform with “low code” and “no code” interfaces that line-of-business (LOB) users can use to quickly develop conversational AI applications that are ready for your enterprise.   

Breaking the code: Get started fast with a Conversational AI platform 

watsonx Assistant’s new no-code visual chatbot builder focuses on using actions to build customer conversations. It’s simple enough for anyone to build a virtual assistant, with a build guide that is tailored to the people who interact with customers daily.  

Pre-built conversation flows

First, we focus on the logical steps to complete the action, with AI that is powerful enough to understand the intent, recognize specific pieces of information (entities) from a message and keep the user on track, all without being redundant. For example, a customer may write, “I want to buy one large cheese pizza.” Should the assistant ask then “What size pizza?” “What toppings?” and “How many?” No, it should just skip to the payment. watsonx Assistant AI will understand that if you start on part 3, parts 1 and 2 should be skipped.  


It’s simple to design a virtual assistant that asks clarifying questions. If you say something in the chat and the virtual assistant doesn’t understand it, it will automatically ask clarifying questions to get the conversation back on track. Which means that developing your bot doesn’t have to be perfect right out of the box. It will automatically get the conversation back on the rails. You can also have predetermined responses. The chatbot could ask: “What is your account?” and if it’s not getting a number, it will automatically clarify and say, “I’m looking for a number only, please.”


With watsonx Assistant, you can identify and address any chatbot problems in a matter of minutes, as opposed to the traditional development cycle.  This allows you to avoid the wasted time and resources associated with going to IT, assigning a developer, and waiting weeks or even months before the changes are actually made. 

Low-code and no-code interfaces like watsonx Assistant’s visual chatbot builder go beyond professional developers and seasoned technologists to open up a whole new class of citizen developers. Companies can take back control to quickly and easily build chatbots for customer service, no code needed. 


Learn more about Visual Chatbot Builder with IBM watsonx Assistant

Was this article helpful?

More from Watson

IBM and ESPN use AI models built with watsonx to transform fantasy football data into insight

4 min read - If you play fantasy football, you are no stranger to data-driven decision-making. Every week during football season, an estimated 60 million Americans pore over player statistics, point projections and trade proposals, looking for those elusive insights to guide their roster decisions and lead them to victory. But numbers only tell half the story. For the past seven years, ESPN has worked closely with IBM to help tell the whole tale. And this year, ESPN Fantasy Football is using AI models…

Five benefits of a data catalog

5 min read - Imagine walking into the largest library you’ve ever seen. You have a specific book in mind, but you have no idea where to find it. Fortunately, the library has a computer at the front desk you can use to search its entire inventory by title, author, genre, and more. You enter the title of the book into the computer and the library’s digital inventory system tells you the exact section and aisle where the book is located. So, instead of…

The importance of governance: What we’re learning from AI advances in 2022

3 min read - Over the last week, millions of people around the world have interacted with OpenAI’s ChatGPT, which represents a significant advance for generative artificial intelligence (AI) and the foundation models that underpin many of these use cases. It’s a fitting way to end what has been another big year for the industry. We’re at an exciting inflection point for AI. Adoption of AI among businesses is increasing, and research and AI development on foundation models is enabling use cases like generative…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters