A visit to any of the major websites is incomplete without a small greeting, often accompanied by questions’ How-may-I-help-you’ or ‘Happy-to-assist’ by friendly chatbots. It is quite impressive that more organisations have handed over the baton to virtual assistants or chatbots, at least at the most primary and initial level of customer service. To provide unparalleled customer service, organisations are progressively leaning towards these chatbots as an effective replacement for human counterparts in a variety of industries, from BFSI, healthcare, to entertainment and governance.
With this, we also are witnessing a steady rise in bot-as-a-service. It refers to using bots or conversational interfaces to interact with the companies, sometimes even without having to open apps individually and through a messaging app already in use.
Rise Of Chatbots & Bots-As-A-Service
The rise in AI-driven chatbots has been primarily credited to the need for leveraging human intelligence, capabilities, and efforts towards interesting and challenging tasks instead of repetitive and mundane jobs. The advancement in conversational AI has helped in automating conversations that are simple and repetitive. With such conversational AI in place, it is believed that as much as 80 percent of the traffic can be routed away from human agents.
Especially during the partial to complete shutdown of major countries worldwide, the demand for chatbots has increased manifold. As per a report, as employees continued to work remotely, chat queries saw a massive upswing, particularly in the health and performance-related queries which saw a 100 per cent increase. This surge further gave rise to up to 40 per cent rise in the AI-driven chatbot queries across industries such as BFSI, retail, pharma, and IT.
When it comes to bots, they are not very different from other software types that read and write files, use databases and APIs, and perform other computational tasks. What makes them unique is that they are generally reserved for human-to-human interactions.
Some of the significant bot framework and platform providers are:
- Released in 2016, the Microsoft Bot Framework is used to develop intelligent applications. The major advantage of this framework is the Direct Line API for connecting the app to the bot. This makes it the best choice for a framework that can be quickly deployed across channels such as SMS, Office 365 Mail, Slack, Facebook Messenger, etc. Along with Azure Bot Service, the Microsoft Bot Framework provides tools to build, test, and deploy bot. The framework includes a modular and extensible SDK for building bots, tools, templates, and related AI service.
- Watson Assistant from IBM is an AI product that helps build, train, and deploy conversational interactions in any application, device or channel. It can be deployed on both cloud and on-premise environments.
- Oracle’sDigital assistant helps build bots, particularly to support existing Oracle EBusiness Suite users and other Oracle ERPs. It can build bots that can be run on any modern messaging platform.
- The Slack framework uses Node.js, Python, C#, among others to integrate and deploy full-featured bots. Users can choose Slash commands to implement specific actions in bot.
- Powered by Google’s machine learning, Dialogflow is a framework for building text and voice-based conversational interfaces for applications. It can be used to connect on Google Assistant, Amazon Alexa, Messenger, Slack, among others.
Future of BaaS
Over the years, messaging platforms have created an immense potential for bots. Apart from just carrying out primary chat services, chatbots’ role may soon diversify, and its usage may extend to personal assistant, entertainment, travel agent, news, advertising, and promotion. Intelligent chatbots would continue to grow in the coming years. Some of the trends that can be expected of BaaS are:
- Bots will be more open and universal. This will allow users to instantaneously find and chat with a company’s bot, not dependent on which messaging is being used.
- Bots will become more accessible with a minimum complexity factor. This means that even non-developers will be able to build and operate a bot.
- The bots will become language-agnostic. Currently, most bots use English as a medium for query solving. However, with the advancement in NLP technology, this is expected to include a larger pool of languages. One step towards making these bots’ universal’ would be to have a This would require developing a generalised framework to allow anyone to operate a bot.
- Intertwined with better sentiment analysis capabilities, chatbots can be trained to be more human-like. Apart from providing an effective response, chatbots in future will be able to cater to a delightful customer experience by responding to customer emotions accurately.
- In the future, chatbots will become multimodal. A multimodal chatbot will be able to interact with the customer using both images and texts.
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I am a journalist with a postgraduate degree in computer network engineering. When not reading or writing, one can find me doodling away to my heart’s content.