In this age of rapid technological advancement, chatbots are one product taking the market by storm. Their applications are easily understood by businesses across industries. If implemented properly, chatbots can have huge impacts on a company’s ROI. An AI chatbot can help increase innovation across the board, while enabling firms to adopt agile and lean process methodologies. Unfortunately, chatbots come with a lot of baggage that has swayed popular opinion on their purpose and efficiency. Here are some common myths that plague the public image of chatbots.
1. Chatbots will Replace Humans Completely
This is predicated by the notion that chatbots are designed to work more efficiently than humans are capable of. A conversational chatbot has efficiencies built in, giving it greater access to more computing capabilities. On the other hand, human workers are still needed to handle complicated queries that require context. These encoded conversations are fed back into the system to make chatbots more intelligent. This means the symbiotic relationship between chatbots and humans will continue to exist for the foreseeable future. Chatbots are not designed to make humans irrelevant. They are only designed to augment what humans can do, to ensure that humans are only working on tasks that explicitly demand their attention and expertise. When customers have access to chatbots, they can get quality customer service at a fraction of the resources it would take for businesses to hire sufficient service representatives.
This increased demand for skilled human workers incentivizes those who go beyond menial and repetitive tasks, instead of sharpening their skills. It’s a win-win situation for both the employer and the employee. The employee learns invaluable skills while exercising them in tasks that actually demand his/her attention, while the employer can use chatbots to perform menial and repetitive tasks.
Leaders in Finance in companies like Wells Fargo, JPMorgan Chase, Bank of America, Capital One, American Express, HSBC, and others have all integrated chatbots to handle incoming customer queries. The Muthoot Group has also integrated a homegrown chatbot called MATTU & MITTU, which will provide customized query resolution services. If the query can’t be handled by the AI, it transfers to a real human agent.
HDFC’s chatbot Eva is another success story, handling more than 5 million queries garnering more than 1,000,000 unique users. It also holds an 85% accuracy rate at this point.
*“The chatbot engaged with bank customers through content. It feeds off data from website and mobile interfaces and provides answers to queries like interest rates, product details, fees and charges for various products, application processes, branch codes etc. We are taking this to the next level and are testing it for basic payment related transactions like bill payments, ticket bookings, etc.” *- Nitin Chugh, Country Head — Digital Banking, HDFC Bank in an interview with Economic Times.
2. Chatbots Have Peaked in Potential
There is significant scope in chat assistant technologies. With greater advancement in NLP and AI, there is increased scope in chatbots potential. A few skeptics are on the fence about the power of the technology owing to its simplified UI and ease of integration. However, as more research is incorporated into core chatbot technologies, there will be more focused conversations that can be done at scale.
In fact, scientists from Facebook and Stanford have been working on a chatbot technology that continually learns from its mistakes. This has taken the conversation from passive learning to active, wherein decisions can be made rapidly.
*“When the conversation appears to be going well, the user’s responses become new training examples to imitate. [And] when the agent believes it has made a mistake, it asks for feedback; learning to predict the feedback that will be given improves the chatbot’s dialogue abilities further … These new examples improve the agent’s dialogue abilities while using only natural responses from the user that do not require special structure, accompanying numerical feedback, or additional human intervention in order to be used.” *- Braden Hancock, Lead Researcher [Learning from Dialogue after Deployment: Feed Yourself, Chatbot]
While the global chatbot market is growing at 34% CAGR, there is enough potential for a self-learning chatbot to emerge as a new standard. The scope is also dependant on the type of applications which are possible. Chatbots aren’t only useful for customer query handling and information. They’re also used for virtual assistant roles and improving patient engagement.
Clinical Psychologist Alison Darcy developed Woebot, which helped over 50,000 patients within the first week of launch about topics ranging from depression to anxiety. It accomplished what few human psychologists could — scalable engagement. It’s estimated to have upwards of two million conversations a week via Facebook Messenger.
*” CBT is a readily translatable treatment for digital therapies, because it’s really structured, it’s based on data, it’s time limited and evidence-based. The big realization lightbulb moment — one of the big ones for us — was that actually, some people don’t want to talk to a human. That’s kind of the value proposition of Woebot is that he’s very much a robot.” *- Dr. Ali Darcy, CEO, Woebot.
3. Chatbot Technology is Complicated
This is one of the easiest myths to dispel. With the rise in software integrations and cloud computing, Chatbots are some of the easiest-to-execute software packages a business can install. They come in a variety of formats, with many chatbots being executed through the existing platform of the web presence. They can be scaled up as needed and can have multiple human agents to be assigned to a single case. Added to that, Chatbots provide more information on a single dashboard than any alternative. They’re also capable of self-learning and have quality engineers working on making chatbots better. Chatbots are also easy-to-use, making it ROI friendly to install at scale. As the use of AI and ML become ubiquitous, the power of chatbots rises. They become increasingly sophisticated and require lesser maintenance and updates.
The core technology keeps evolving without much input needed from end users. As technology becomes smarter about collecting data, chatbots will need more resources. These resources can be supplied by chatbot developers. If you’re a CXO or an IT manager who wants to integrate chatbots, it helps to connect with experts in the domain.