Future of Conversational AI

Conversational AI is inherently becoming a regular part of our lives. Every industry is using artificial intelligence to smoothen customer conversations and better the lives of their agents. As AI becomes more realistic, we are approaching a bright future where machines will complement our employees and curate the ultimate experience for the end-user.

Conversational AI is the technology that allows computers or smart devices to communicate with humans and perform tasks. It uses NLU and NLP to decode the semantics of human languages and understand the intent and emotion of the speaker. Basically, speaking bots have notched up things a bit in our lives and everywhere else.

We are all familiar with mainstream conversational AI solutions like Siri or Alexa that help us in our day-to-day lives. In the corporate world, there are similar solutions that help businesses to perform regular tasks with minimal to no error. There are three kinds of roles that conversational AI plays in any organization:

1. Customer-facing assistance.
2. Employee and/or agent assistance
3. Workforce Management

While conversational AI can play a major role, it is often seen as a complicated technology for various reasons. One of the primary reasons is privacy concerns and the second reason is lack of personnel. The privacy concerns around AI-driven solution is legitimate yet not a roadblock. Modern customers expect complete transparency on how their data is being utilized for the benefit of better service. Clearing this fog of doubt will allow people to embrace and accept AI for better purposes.

Now, the secondary issue is, there is a distinct lack of personnel who can work with Artificial Intelligence and Machine Learning. The field is a growing discipline and lacks an abundance of manpower. Hence, certain companies are skeptical about completely investing in AI, beyond just chatbots.

Once we overcome these issues, we will understand better how conversational AI doesn’t just mean AI. It means simplifying complex human tasks and getting it done within a flick of an eye or may I say, just by mere utterance!.

The Future of Conversational AI

Every day we witness better use cases of Artificial Intelligence. In fact, its adoption was accelerated due to complications faced thanks to the covid-19 pandemic. AI is no longer limited to just NLP-based bots. It has become more sophisticated, intelligent, and contextual. Now, conversational AI is leveraged to create an immersive experience that not only resolves customer issues but also spoils them for choice. The demand for such solutions is definitely on the rise, as businesses race to fulfill customer expectations while also reducing operational costs per customer.

1. Mass Adoption of Conversational AI:

As the covid-19 pandemic froze many operations, there was a surge in the usage of conversational AI. Many people were laid off due to operational discontinuity and loss of money. On the other hand, many couldn’t travel to work due to social distancing and other government-led protocols. All in all, it led to a distinct need for chatbots and virtual assistants.

This accelerated adoption led to people recognizing the potential of AI. People witnessed how it can fulfill many requirements without draining resources. Brands are going to continue to adopt AI and offer more valuable customer service in the coming years. Multilingual language capabilities and switching between languages are also a priority for the brands if they are operating from multi-geography or the region has speakers of different languages.

2. Contextual Awareness:

Context is key for conversational AI bots. It is important to know the context during the conversation.

For example, the caller says - Please book my flight from Amsterdam to Brussels for 19th June. Once the bot confirms the availability and the callers ask, what documents will be required?

The bot should understand the context that is related to flight reservation and responds accordingly. So while the conversation is on, the bot knows that it is related to flight reservations and not hotel reservations. And as soon as the caller moves to a hotel reservation it stores the context and responds accordingly.

Emotional intelligence is an asset when it comes to serving customers. The only way machines can develop emotional intelligence is by being contextually aware. In fact, thanks to newer machine learning models, conversational AIs are becoming aware of customer intent, sentiments, and other emotions. It allows them to reply more aptly and collect relevant information. In the coming years, AI can be self-aware enough to offer positive responses and even create a friendly atmosphere. These bots can learn for years and recall historical data, customer emotional history during each interaction, and other sentiment-driven data. Through this information, it can accurately decide how to respond to the customer and create a safe environment.

3. AI-Driven Advisory In Every Industry:

While we all take a lot of pride in our job roles, we always need assistance. We do forget things, make errors, and even have shortcomings. Soon enough though, these issues can be reduced with AI Coaches. According to a Gartner study, around 70% of employees will take help from AI to perform their job better. In fact, in certain countries, doctors are asked to have an AI advisor who will offer a second opinion on every patient case. It only goes to show how AI can offer a superior and error-free opinion as it can run through historical data without breaking a sweat. AI coaches will enable employees to reduce errors in their daily work. It will also improve their decision-making as the AI can consider multiple factors at once, unlike humans.

4. Monetizing Across Multiple Touch-points:

Conversation with AI assistants is no longer limited to a singular platform. Earlier, we only got to experience AI either only on mobile or website. But now, conversational AI can be integrated across platforms and create an omnichannel ecosystem. In other words, customers will no longer repeat their information shared on one channel. Agents will have complete hover-vision across channels and create an individualized experience for each customer. This can be paired with sentiment mapping and keyword discovery across customer conversations to better the experience for the customers.

Conclusion:

Conversational AI is important to make communication seamless. As brands expand and grow, personal touch tends to get lost. Today the customer is more vigilant and aware, hence, it is advised to nurture them. Thanks to AI, most of these can be done without shedding extra resources. AI is a landmark solution for enterprises that deal with sensitive data such as finance and healthcare. It can help in resource management and customer satisfaction. With conversational AI, the possibilities are immense, and now is the perfect time to invest and explore.