The increase of chatbots in the modern workplace requires IT leaders to create conversational platform strategies that ensure effective solutions for customers, employees, and key partners.
AI-powered chatbots continue to be a hot topic among end-users and vendor communities. It is no surprise that chatbot technology is beginning to mature to offer more sophisticated solutions. Gartner has predicted that by 2022, over 70% of white-collar workers, on a daily basis, will interact with conversational platforms.
Due to this, more organizations are investing in chatbot deployment and development. The 2019 Gartner CIO Survey also mentions that CIOs think that chatbots are one of the significant AI-based application used in enterprises.
Enterprise interest in around implementing chatbots has increased by over 160% from 2018. This increase is driven by knowledge management, customer service, and user support. This growth is on the same level at which millennials are entering the workplace. Chatbots can cater to millennials’ demand for instant and digital connections that allow them to be up-to-date at all times. The millennials will likely have a significant impact on how quickly and efficiently the organizations adopt the technology.
The ability of chatbots to use natural language processing (NLP) to map written and spoken input has led to it rapidly entering the workplace. Experts believe that the tools and software that are being used need to simulate the behavioral trend and supplement better, faster, and more efficient collaboration in the workplace.
But, the proliferation of enterprise chatbots does come with some challenges. Currently, the market is crowded with over 2,000 vendors, and many of these are ill-equipped to maintain and deliver chatbots. CIOs need to ensure that the chatbot solution that they chose is effective for all stakeholders and implement governance policies.
While implementing a chatbot solution for the enterprise, experts suggest avoiding providers that cater to single-use cases. The most ideal is to attempt and create in-house chatbots if the right data science and ML assets are available. If not that, approaching the third-party providers that specialize in data preparation to build and host chatbots must be partnered with.
To take the strategy long ahead, it is suggested to secure monitoring and funding resources for ongoing model maintenance. Chatbots also require ongoing operational assets that are needed for periodical evaluation of the performance of the model and also to add domain-specific expertise. CIOs must ensure that resources are devoted to model management on an ongoing basis and access available for data management.
In the next five years, it is predicted that voice-enabled chatbots will become a norm. Although some chatbots do support voice-enabled features, the demand for such features is only increasing, as they provide natural ways to interact with the conversational technologies. Enterprises are suggested to be prepared for meeting this demand by already specifying voice support in their solutions.
Above all, the chatbots are expected to have human emotions and it is necessary to incorporate tone, personality, and other soft features that are critical to the success of chatbots. Enterprises must ensure the chatbots they deploy reflect the values of the company and the brand.
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