By: Joel Nathan M and Vinoth S

The novel coronavirus pandemic has had a lasting impact that will take years to overcome. Apart from people, the pandemic also affected multiple sectors. Amongst these, the healthcare sector had an adverse effect, while the pandemic also exposed its deep underlying problems that needed immediate action.

As the years have gone by, technology has witnessed rapid progress. From the days of talking through a device to talking to a device – the technological advancement is immense. Conversational AI is at the forefront of technology enablement that has made this happen. What is conversational AI? In simple words, it translates to the human-like interaction between humans and computers. Conversational AI uses a set of technologies like Natural Language Processing (NLP), Machine Learning (ML), etc. to process large volumes of data to recognize speech and text input to translate their meanings across various languages, thus imitating human interactions.

Conversational AI process:

Conversational AI already has a significant influence on healthcare. Even before the pandemic, Gartner, in July 2019, stated that “By 2025, customer service organizations that embed AI in their multichannel customer engagement platform will elevate operational efficiency by 25%. During the pandemic, Gartner, in February 2020, predicted that, “By 2022, 70% of customer service interactions will involve emerging technologies such as machine learning (ML) applications and chatbots.” The forefront of customer service organization is healthcare, and ensuring proper customer satisfaction by attaining optimal operational efficiency to provide better customer service is of primary importance.

Conversational AI is a pivotal aspect of digital transformation in the healthcare industry. Consumers these days are not only authoritative, but also demanding in their healthcare journey as they expect immediate and high-quality care. In this era of the Internet, consumers demand accurate information to make educated, smart, and cost-effective decisions. Also, as this industry is shifting its focus to a consumer-centric approach, healthcare industries are forced to find ways to provide high-quality experience while bringing down their costs. One such door where opportunity awaits is traditional call centers, as 50-70% of calls are related to health benefits and the industry is slapped with higher costs in searching for more granular data per call. The cost averages around $5-15 per call. Service industries try to lower their costs without impacting their service efficiency. According to Forbes, out of 60% of millennials who have used chatbots, 70% of them have reported positive experiences and nearly half of them who have not used it say they are interested in using them.

Conversational AI only gives appropriate information to customers, but can also anticipate follow-on questions to provide a better customer experience.

Conversational AI solution includes intelligent chatbots, virtual agents, and voice assistants. Chatbots are one of the frequent use cases of AI in enterprises and according to Forbes, in the next two to five years, the adoption of AI-powered chatbots will be twice of what we see now. Current versions of chatbots are trained to answer simple queries, which follow a pattern. However, with the power of AI, chatbots can efficiently handle more complex queries with a personal touch. Conversational AI can leverage the combination of NLP, machine learning, and other advanced technologies to address complex patient journeys and provide the best health care, but a rudiment chatbot only leverages the power of NLP, which depends on algorithms and linguistic rules to understand the question and choose an appropriate response. (Fig 1)

• According to Markets and Markets, by 2026, global conversational AI including chatbots, virtual agents, and voice assistants is projected to be USD 18.4 billion and growing at a CAGR of 21.8% during this period.
• According to the article, ’Chatbots will appeal to modern workers’ published by Gartner in July 2019, “70% of white-collar workers will be interacting with conversational platforms by 2022.”

The following are a few applications that are changing healthcare worldwide:

• Scheduling Appointment
• Access to Information
• Assessing symptoms

With conversational AI, chatbots can retrieve the required information from the patient and find a suitable slot by booking the required physician’s appointment, all in just a conversation. AI assistants are also used to answer customer queries immediately. Where to get the next vaccination? How long to undergo medication? Answers to such queries can be got by dropping a mail or calling the hospital/doctor, which mostly goes unanswered. However, with AI, the information is readily available, and the responses are triggered based on the keywords in the questions raised. Conversational AI is also used to understand the symptoms of patients by asking relevant questions and directing them to the healthcare provider based on the symptoms. The applications of conversational AI in healthcare have impacted the operational efficiency of the system positively. However, when COVID-19 spread across the world, people were left stranded without beds in hospitals, medicines, etc.

Communication is key during a pandemic. When the pandemic broke, false information spread like wildfire, creating chaos in India. The Government of India, in its already existing platform, deployed conversational AI with the help of a service provider to ensure better user engagement and communicate the right information about the outbreak. The World Health Organization (WHO) also used AI to find answers to users’ questions, accessed through WhatsApp and Facebook Messenger.

While conversational AI was useful during the pandemic, as more such applications are implemented in the field of healthcare, there is no doubt that we will witness an increase in its relevancy and accuracy. Successful adoption requires a fine balance between empathy and machine learning. In the next few years, we can expect conversational AI in:

• Serving as 24×7 caretakers
• Notifying relevant agency in case of an emergency
• Helping in early diagnosis
• Managing chronic conditions and mental health issues
• Identifying symptoms proactively and cross-check them with the medical history
• Providing timely medical advice.

Building a futuristic healthcare solution requires a thought beyond technology for better adoption. Only then, will we be able to unlock the true potential of conversational AI.

References:

• Conversational AI Market Size, Share and Global Market Forecast to 2026 | MarketsandMarkets
• Chatbots Will Appeal To Modern Workers (gartner.com)
• What’s New In Gartner’s Hype Cycle For AI, 2020 (forbes.com)
• The future of conversational AI | Deloitte Insights
• Conversation AI- healthcare
• https://www.gartner.com/smarterwithgartner/top-cx-trends-for-cios-to-watch
• How Chatbots Feed Into Millennials’ Need For Instant Gratification (forbes.com)
• Conversational AI vs. Chatbots—What’s the Difference? – CSG (csgi.com)