Chatbots continue to be a hot topic among media, end-users and vendor communities. This is no surprise, as chatbot technology - which uses artificial intelligence (AI) to mimic human conversations - is beginning to mature and offer more sophisticated solutions. This is primarily because of improved, AI-enabled language capabilities.
As a result, more organisations are investing in chatbot development and deployment. In the 2019 Gartner CIO Survey, CIOs identified chatbots as the main AI-based application used in their enterprises.
Van Baker, VP Analyst at Gartner.
“There has been a more than 160% increase in client interest around implementing chatbots and associated technologies in 2018 from previous years,” says Van Baker, VP Analyst at Gartner.
“This increase has been driven by customer service, knowledge management and user support.”
Chatbots and the modern workforce
Thanks to their ability to use natural language processing to map spoken or written input to an intent, chatbots are rapidly entering the workplace.
“The tools and software being used today need to simulate this behavioural trend and supplement faster, better and more efficient collaboration in the workplace,” says Baker.
By 2022, 70% of white-collar workers will interact with conversational platforms on a daily basis. This expected growth is on par with the increase of millennials in the workplace. Because chatbots cater to millennials’ demand for instant, digital connections that keep them up to date at all times, millennials will likely have a large impact on how well and how quickly organisations adopt the technology.
Best practices for chatbot development
The proliferation of enterprise chatbots comes with some challenges. The market is crowded with more than 2,000 vendors, many of which are ill-equipped to deliver and maintain chatbots.
To ensure your chatbot solution is an effective one for all stakeholders, implement governance policies and apply these best practices as part of an overall conversational platform strategy.
Avoid chatbot solutions that perform poorly or overlap. Many vendors are unable to deliver enterprise-grade chatbot solutions. Screen vendors carefully, avoid providers that cater to single-use cases and ensure those chatbot guidelines are defined.
Reduce the risk of failure by sourcing chatbots from external providers. You should only attempt to create your own chatbots if you have the right data science and machine learning assets. If not, look to third-party providers that specialise in data preparation or providers that build and host chatbots.
Secure funding and monitoring resources for ongoing model maintenance. Chatbots require ongoing operational assets that can periodically evaluate the performance of the model and add domain-specific expertise. Devote resources to model management on an ongoing basis and ensure you have access to all of the required data management skills.
Prepare for the day when users expect voice-enabled chatbots. Although few chatbots support voice-enabled features today, demand for such features is increasing, as they provide a natural way to interact with conversational technologies. Be prepared to meet this demand by specifying voice support in your solutions.
Incorporate tone, emotion, personality and other soft features. Soft features are critical to the success of chatbots, although most solutions don’t include them. Ensure the chatbots you deploy reflect the values of your company and your brand, and that the tone of your chatbot is pleasant. The latter increases the tolerance for mistakes or additional questions.
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