Chatbots are popping up more and more at companies. As primarily it was used in customer service, but the shift has also taken place in improving customer experience (CX), business efficiencies, and these are just a few to name it. Chatbots are often termed as virtual agents, digital assistants, virtual customer assistants, and conversational AI bots.
Unforgettable COVID-19
COVID-19 is working as a catalyst for 76 percent of enterprises to invest in long-term IT reforms [1]. Due to the COVID-19 situation, businesses are digitizing to safeguard staff and service consumers who are experiencing mobility issues. Artificial intelligence-powered (AI-powered) chatbot spending will reach $78 billion in 2022, a massive increase from the $24 billion forecast in 2018 [1]. Software is the fastest-growing technology category, with AI/cognitive systems accounting for 40% of the market, with a five-year compound annual growth rate (CAGR) of 43% [1]. Deep learning and machine learning applications (wide applications across all sectors) and conversational AI are the two verticals where investments are concentrated (chatbots, personal assistants, virtual agents, etc.). The United States has the greatest market in conversational AI in terms of size and growth, while Southeast Asia has the fastest CAGR [1]. With increased private equity investment in AI/machine learning, the United States will dominate the incorporation of conversational AI. Furthermore, rising government spending on AI-powered technology will hasten industry expansion. The demand for increased functionality and value is driving an explosion of investment and interest as more consumers and businesses employ chatbots.
Explosion? Why?
When it comes to quick answers, 74% of customers end up choosing AI chatbots [1]. Companies who use AI chatbots in retail have witnessed a 47 percent increase in efficiency, a 40 percent increase in inventiveness, and a 36 percent increase in helpfulness [1]. Increased need for lower AI chatbot development costs, greater customer service, and omni-channel development are all driving growth.
Roadblock?
Although the chatbot market is still in its early stages, Europe lags behind other countries because to data privacy, ethical concerns, fear of failure, and market uncertainty [1]. The language barrier is now the most significant obstacle in the way of chatbots in underdeveloped countries. It would be straightforward if all interactions were conducted in English. Other languages, on the other hand, can be far more sophisticated in terms of syntax and organization. To feel natural to customers and so improve the customer experience, chatbots must be schooled in the complexities of the language [1].
Each organization that commits to a chatbot in its business operations decides for itself the regulations regarding the development of the chatbot. Among other factors, a chatbot can handle sensitive data. So here and there may vary the extent to which the chatbot is transparent.
I personally believe that it should be clearly stated in advance what will be done with the data and in whose hands it ends up. If I would like to use a chatbot myself, the questions will refer to more informative answers that you can get within a split second via the chat. No more and no less.
Now, I am curious to what extent will you trust a chatbot with sharing data (for example, personal data) and why?
[1] Hoang, T. (2021, 17 mei). The AI Chatbot Explosion in Various Regions around the World. Discover.Bot. https://discover.bot/bot-talk/ai-chatbot-in-various-regions/
Hi Ishwar! Very interesting topic and summary on the current dilemmas related to chatbots. Indeed, they are a very effective tool when they serve as kind of a replacement of FAQ pages and are programmed to provide customer support. However, with the development of NLP, they become more and more able to “understand”, or at least process, more complicated and unexpected customer requests. Not to mention that on the other side of a chatbot is an employee inside a company who has access to all records stored by the chatbot software.
If chatbots become sophisticated enough to increase trust in customers towards them, there is a huge risk that sensitive information can be stored which otherwise shouldn’t be communicated to that specific retailer at all. One of my friends is working for a chatbot development company, and according to her, it is very shocking to see how many people don’t understand even the basics of how chatbots work and what kind of conversations they were designed to have. This lack of understanding of its working mechanism completed with the technological advancements in NLP can create very unpleasant situations if regulations don’t follow.
Your question at the end about how much people would trust a chatbot with personal data is a good one and in my opinion, the answer is more than they should. To what extent will companies using the chatbot technology be able to store and use data they acquire through their chatbots is another interesting question to be asked.