The Rise of Conversationalization

A few years ago, enterprises experienced a significant shift in the way they developed and redesigned their applications. The rise of social media apps such as Facebook and Twitter led to the trend of “Appification,” where applications that were initially built for internal use were redesigned with the end customer in mind. The aim was to provide personalized and efficient services to customers while reducing the workload on employees. Today, we are on the cusp of another revolution in enterprise architecture, what I call it as – conversationalization.

Conversationalization is the shift towards using natural language interfaces to interact with enterprise systems and services. The demand for personalized and efficient user experiences, as well as the need for users to be more productive and efficient in their work, drives this trend. ChatGPT, an AI-powered conversational interface developed by OpenAI, has taken the world by storm and has taken the conversationalization trend even further.

ChatGPT and Open Source AI Models for Conversationalization

As a CIO, you know that your enterprise needs to modernize and stay ahead of the competition. By adopting ‘conversational’ interfaces such as ChatGPT or its open source equivalent, you can provide highly personalized and efficient services to your customers and users, while reducing the workload on your internal teams. ChatGPT or AI models for conversations are trained to understand natural language and provide highly personalized and efficient responses to user inquiries. By integrating chatbots and intelligent voice assistants powered by these models into your IT landscape, you can offer a highly efficient and personalized way to interact with your systems.
ChatGPT has shown the accurate power of ‘conversation’ in natural language towards user engagement and satisfaction. Now, we have many open source models that you can deploy within your enterprise IT landscape.

Steps: How to get Conversation-Ready with ChatGPT and Open Source AI Models

Let’s take a look at how enterprises get conversation-ready using ChatGPT and open source AI models?

Step 1: Choose the right open source AI model that fits the enterprise’s requirements. The solution must be reliable, scalable, and easy to integrate with the enterprise’s existing IT infrastructure. It must also meet the specific regulatory requirements of the industry.

Step 2: Build a training dataset that is representative of their specific use cases. The dataset will be used to train the model to understand the enterprise’s language and provide relevant responses. The dataset must be of high quality and it must be continually updated to ensure that the model stays accurate and relevant.
To provide the best possible user experience, it is essential to provide context to the open source AI model. Enterprises must ensure that the model is trained on the right data and understands the context of the user’s request. This can be achieved by integrating the open source AI model with other enterprise systems, such as the enterprise’s HR or IT support systems.

Step 3: Optimize workflows and processes for efficiency. Chatbots and intelligent voice assistants powered by ChatGPT can be used to automate routine tasks and provide real-time support, reducing the workload on employees and freeing up time for more strategic work.

Are you ready?

Conversationalization is the next frontier in enterprise architecture. By adopting chatbots and intelligent voice assistants powered by ChatGPT or open source AI models, enterprises can provide highly personalized and efficient services to their employees while also reducing the workload on their support teams. As a CIO, it is crucial to embrace these new technologies and continuously adapt to the changing expectations of users. The future of enterprise architecture is conversationalization, and the time to get on board is now.