• CogniCor

We live in an era in which every aspect of our life is touched by artificial intelligence. From sales to service and support, conversational AI is fast becoming the platform of choice for interaction.

Like many business areas, conversational AI is transforming IT help desk in a powerful way by moving beyond solving mundane issues such as password reset. Today, enterprises are able to personalise the IT support experience and anticipate what may occur in the future.

But, success would depend on a clearly defined scope of use cases. This article sheds light on where conversational AI can be applied from our experience and discusses how it helps IT support become more efficient.

Effortless Self-service

Conversational AI makes self-help a more accessible and an appealing experience. It empowers users with accurate and instant information round the clock. Repetitive tasks such as password reset and printer configuration can be easily solved with the help of interactive assistants. These assistants use AI to understand the query and proactively fetch the solution from the knowledge base, creating space for help desk professionals to focus on tier 2 and tier 3 support.

Seamless Switch to Live Agent

The need for expert help during the course of a conversation can never be negated. If the solution offered by the Interactive Assistant is unsatisfactory, a user might feel the need to interact with a human agent. To accomplish this, forcing a user to switch to a new channel can damper the experience.

Access to expert help can be made a seamless experience by automatically switching to a live agent from the same window. Even more, AI technologies can be used to analyse user sentiment and proactively bring expert help into the conversation.

Automate Service Requests

Most of the routine service requests could be brought under the ambit of conversational AI by creating automated workflows. Consider one of the most common service requests - password reset. Just by conversing with the bot, an automated mail with the password reset link could be sent to the user for resetting the password. This would help the IT Support providers in addressing other problems like delays in processing service requests.

Better Manage Incident Requests

Acknowledging the problem is key. Instead of raising a ticket and waiting for a response, conversational AI lets the user know that the problem is acknowledged diligently. By connecting to existing systems, an Interactive Assistant can help a user create an incident ticket by conversing in natural language or pre-fill the form for the user. In addition, users can easily check the status of tickets and make updates within the chat window.

Higher Turnaround Time

Often, IT help desks receive high volume of requests that is more than what they can manage. Conversational AI can automatically categorize and prioritize tickets making it easier for help desk agents to act promptly.

Increase Time-to-Respond

IT help desk agents work with huge databases and documents. To answer a query, they sift through hordes of documents which can be tiresome. Interactive Assistants make information discoverable by offering a conversational UI that can quickly find relevant content and answer the query.

Manage Training and Knowledge Gap

With organization pulling the cost reduction lever, IT support desks are now being forced to do more with less. With a high churn rate, training new resources is no longer efficient. Conversational AI can keep the learning curve to a minimum. For example, while managing service requests, new agents don’t need to learn the entire process. Instead, they can just converse with the interactive assistant and get the response.

AI is a journey, not a destination. Careful planning and execution is required to make conversational AI commonplace in the enterprise.

Conversational AI has been making waves across industries. From lead generation, customer on-boarding, customer and agent support, the benefits could be generating new revenue or reducing cost. Infosys research, based on a survey of more than 1,000 business and IT leaders, found that 73 percent of respondents agreed that their AI deployments have already transformed the way they do business.

As an enterprise, you have probably established an innovation team or AI lab and may be your initial project has gone live. What do you do next?

AI is a journey, not a destination. Careful planning and execution is required to make conversational AI commonplace in the enterprise. After all, every AI deployment and use-case is different.

From our deployment experience, below are a few ways to move forward after launching a virtual assistant.

1. Set the Team, Process and Optimise

While most conversational AI vendors talk about technology jargon like Machine Learning, NLP and Cognitive, it is important to cut through the noise. Establish a dedicated team to understand the vendor landscape, ask the tough questions, dig deep into the bot’s capabilities and finally, create a process to fine tune and optimise the bot.

A robust bot is one that continuously learns from interactions, improves accuracy and speed of its responses. AI continuously evolves but it's not magic. Gather actionable insights from the performance of your conversational AI and improve your bot.

2. Conversational Experience Beyond Automation

Many organisations use conversational AI to automate simple tasks and answer simple questions. But new advancements in machine learning and AI can now make the bot truly intelligent.

Transition from a simple FAQ chatbot to a more intelligent Conversational AI capable of handling complex decisions such as product recommendations based on user profile and respond to predictive scenarios.

3. Be Proactive

Integrate with existing systems and leverage data to personalise interactions in real-time. Be proactive rather than reactive. Engage with customers on their preferred touchpoint and personalise the interaction. Remember their preferences, analyse their sentiment and proactively transfer to a live agent.

4. Expand to New Channels and Languages

Is your bot deployed across customer touch points? Website need not be the only interface for your bot. Analyse the most frequently used customer touch points and provide an omni-channel experience across touch points such as Text, Facebook Messenger, etc.

Global organisations can cater to customer across borders. Organisations leverage CogniCor’s multi-language understanding pipeline to deploy multi-lingual bots.

5. Scale

Success from one use-case should be experienced in another. The bot should easily be able to extend its capabilities and enable organisations to easily add additional products or services. Using CogniCor, one of the leading insurance providers experienced tremendous success in selling automotive insurance policies. The firm has now extended its capabilities to health insurance.

6. Deploy Across Customer Journeys

Merely having conversations with customers has no impact. Conversational AI can be a boon when used across journeys. Map a journey and leverage flexibility of the bot to cater to customers/users across their journey. Some of the leading financial institutions in Asia and US have deployed CogniCor’s virtual assistant for mortgages, insurance and wealth management related use cases. The bot was built to carry a conversation on either topic and seamlessly engage with customers.

Just like the e-commerce shopping experience, customers want instant, personalised and simplified information anytime anywhere from all industries and, more so from insurance. The traditional insurance industry has been resilient for a long time but digitisation and disintermediation has forced insurers to rethink the way they want to interact with customers.

Virtual Assistants offer insurers a quick and easy way to serve customers and insurance agents anytime anywhere. Through virtual assistants, insurers can support insurance agents and customers by providing instant product information and allowing customers to quickly purchase insurance and redeem coverage at any time.

So far, most chatbots have been focusing on automating the claims process but now the focus is moving towards streamlining the end-to-end process and guiding customers using chatbots. AI-powered virtual assistants leverage NLP and deep learning to understand the underlying context and generate personalised human-like response. Here are twelve ways AI-powered virtual assistants transform the insurance industry, sooner rather later.

  1. Reduce customer confusion — According to a recent survey, 72 percent of consumers agree that insurance companies use confusing jargon. Chatbots can help reduce this confusion by simplifying insurance terms, explaining complex coverage and walking customers through the process step-by-step.

  2. Automate query management process without human intervention — Chatbots can collect information about the customer and the issue in real time and, process data to quickly solve the query.

  3. Improve lead generation & sales — Use chatbot as a channel to nurture leads and sell insurance. Using the CogniCor platform, a leading global insurance provider sells 2000+ automotive insurance policies on a monthly basis and the entire process starting from product discovery, premium calculation and the actual buying process is handled by the virtual assistant without any human in the loop.

  4. Support insurance agents — While interacting with customers, scouting for specific information on insurance policies on an enterprise portal is inefficient. Instead insurance agents can ask the virtual assistant questions and get responses quickly and, convert customers in real time.

  5. Underwriting recommendation — Evaluating risk profile is a long drawn and tedious process. Typically insurance agents collect information and go to the underwriter for approval. Chatbots can streamline the underwriting process and quickly assess risk of applicants.

  6. Streamline claims processing — With the use of AI, chatbots can automate claim processing without any human intervention thereby eliminating repetitive tasks, speeding up the claims process and decreasing cost per claim.

  7. Drive down premium costs — By analysing customer behaviour, chatbots can assess risk and drive down premium costs for low risk customers and penalise high risk customers.

  8. Product Recommendation — By analysing user profile, chatbots can offer personalised insurance products and customise coverage. In addition, chatbots can also embed cultural nuances to personalise customer interaction.

  9. Enable Product comparison — Customers can easily compare insurance products within the chatbot and make informed decisions.

  10. Explore What-if Scenarios — Customers can reason hypothetical scenarios and apply relevant policies to the situation

  11. Seamless handoff to live agent — When the chatbot comes across a complex query, it can seamlessly transfer the chat to a live insurance agent in such a way that the live agent can pick up where the chatbot left off.

  12. Reduce handling time — Using machine learning, AI-powered chatbots can analyse past claims and predict which incoming claims will be time-consuming such as fraud or litigation, and flag them for proactive human intervention.

What’s next?

With the proliferation of AI and virtual assistants, insurance companies have a tremendous opportunity to reshape claims, distribution, underwriting, pricing and streamline customer experience. Customers expect brands to be omnipresent across multiple channels including mobile, Facebook messenger and eventually voice as well. Insurance chatbots need to be integrated across all the channels and make insurance ubiquitous.

Originally published in Medium