Conversational AI Use Cases in 2024
Businesses across various sectors are leveraging the power of conversational AI to enhance customer experiences, automate tasks, and drive innovation. From banking and insurance to government services and fintech, conversational AI is transforming the way organizations interact with their customers and deliver value.
41% of tech leaders believe companies will fall behind if they don't adopt conversational AI capabilities.
In this blog post, we will explore the key use cases of Conversational AI in the banking, fintech, insurance, and government sectors. We will also delve into the factors to consider when deciding whether to build or buy a Conversational AI solution.
Conversational AI in banking
Conversational AI (CAI) is revolutionizing the banking industry, enabling financial institutions to deliver exceptional customer experiences, automate tasks, and drive innovation.
One key application of Conversational AI in banking is the implementation of self-serve AI assistants within banking apps and products. These AI assistants provide customers with 24/7 support for routine banking tasks such as checking account balances, adjusting credit limits, transferring funds, and paying bills. By removing the need for in-person visits or phone calls, Conversational AI enhances customer satisfaction and convenience, offering a seamless banking experience anytime, anywhere.
Another significant use case of Conversational AI in banking is its ability to analyze vast amounts of customer data, transaction history, and behavioral patterns. Advanced Conversational AI platforms, like Alltius, leverage this data to create comprehensive customer profiles and identify relevant cross-selling opportunities. These AI platforms can proactively suggest personalized banking products and services to sales professionals during customer interactions. This guarantees that customers receive tailored solutions that meet their unique financial needs and preferences.
Conversational AI also plays a crucial role in enhancing the quality of banking services. By analyzing customer conversations, Conversational AI can identify areas where the bank can improve its offerings and customer support. This data-driven approach enables banks to continuously refine their services, provided they meet the evolving needs and expectations of their customers.
Furthermore, Conversational AI serves as a powerful tool in detecting and preventing fraud within the banking sector. By analyzing customer transactions in real-time, Conversational AI can identify suspicious activities and flag potential fraudulent attempts. This proactive approach safeguards customers' financial assets and preserves the integrity of the banking system.
Case in point
Conversational AI in insurance
Many insurance companies take 42 hours or more to respond to sales leads, and nearly half never respond at all. Over a third of companies only reply to customer queries within an hour, leaving many customers frustrated with long wait times.
This makes Conversational AI a powerful tool that can be used to improve customer experience in the insurance industry. Conversational AI assistants can be used on both the customer end and the support agent end.
Self-served AI assistants in the insurance industry can help companies:
- help customers with a variety of tasks, such as filing claims, getting policy information, and making payments without relying on human help.
- provide personalized recommendations to customers, such as suggesting the best policy for their needs or helping them find a local insurance agent.
For customer support agents, these AI assistants can help them close tickets at a faster rate with
- Pre-defined answers for frequently-asked questions.
- Immediate root-cause analysis of customer queries and finding correct answer from multiple insurance-related documentation.
- Canned responses for legal questions.
In addition to customer service, sales agents can also use conversational AI assistants to find the exact plan that suits the customer's needs. Advanced tools like Alltius can even create a tailored pitch for sales agents to pitch the plan to the customer on-call within seconds.
Conversational AI in government
In the realm of governance, conversational AI can empower governments to enhance citizen service delivery and transform the public sector. This innovative technology holds immense potential to revolutionize the way governments interact with citizens, optimize service provision, and drive meaningful improvements in various domains.
One of the key advantages of conversational AI lies in its ability to automate routine tasks. It can handle repetitive query resolution for citizens, thus freeing up valuable human resources. This enhances operational efficiency and also leads to significant cost savings.
Conversational AI platforms like Alltius can be used by government institutions for knowledge management. It can act as a powerful enterprise search platform to extract information from multiple documents with one query within seconds.
In case you’re looking to explore AI in your company, try Alltius. Alltius is a platform created as a result of decades of research at Carnegie Mellon and Wharton. Alltius is a gen AI assistant platform that can 3X sales and slash support costs by 50% within weeks of implementation.
We’ve helped companies reduce their customer support costs by $50k per month. In case you’re interested:
- Request a demo
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- See the ROI from Alltius
- Explore the platform
Conversational AI in fintech
The AI fintech market will reach $44.08 billion in 2024 and grow at a CAGR of 2.91% to reach $50.87 billion by 2029.
Fintech products are highly personalized and multifaceted. The buyer journey can often be lengthy and complex. Conversational AI can play a huge role in providing information at all stages of the buyer journey and accelerating the buying journey.
For lead generation, AI assistants can engage with potential customers, answer their questions, and guide them through the sales process. They can also help customers find the information they need, compare multiple plans, and take account of actions without human intervention.
In the case of sales, conversational AI can be used to automate repetitive tasks, reducing the workload on human employees. It can help sales agents understand customer needs and preferences. It can also help agents identify best way to effectively cross-sell and upsell relevant financial products, increasing conversion rate and revenue!
Conversational AI can also be used to detect and prevent fraud in fintech. By analyzing transaction data, AI algorithms can identify suspicious patterns that may indicate fraudulent activity. This can help fintech companies protect their customers from financial loss and reduce the risk of fraud-related losses.
Case in Point
How long does it take to develop conversational AI?
You're interested in exploring conversational AI for your use cases, but how long until you can see the output?
The development time of a conversational AI solution depends on several factors, including the following:
- The number of languages the AI needs to support. - The more languages the AI needs to support, the longer it will take to develop. This is because the AI needs to be trained on data in each language, and the amount of training data available for each language may vary.
- The amount of training data available. - The more training data available, the better the AI will perform. However, collecting and cleaning training data can be a time-consuming process.
- The complexity of the desired interactions.- The more complex the desired interactions, the longer it will take to develop the AI.
- Build or Buy - If you need a solution quickly and are willing to pay a higher price, then buying a pre-built solution may be a better option. However, if you have the time and resources to develop your own solution, then building a conversational AI custom solution may be a better choice.
What’s next for conversational AI?
As the technology improves, more and more avenues to use conversational AI shall emerge. As of now, conversational AI is a perfect fit for textual medium for customer service and sales. It can help your employees perform better and become efficient at their jobs. Conversational AI isn’t yet developed to completely replace their human counterparts.
In this blog post, we’ve discussed some ways conversational AI can be used by modern businesses. As conversational AI grows, Alltius will keep finding new ways to implement generative AI to help customer success, customer support and sales team become better at their tasks.
FAQs
What is an example of a conversational bot?
An example of a conversational bot is Alltius AI assistant, which can engage in natural language conversations, answer questions, and perform tasks based on user input for customers, sales and support teams.
What is the basic conversational AI?
Basic conversational AI involves programming machines to understand and respond to natural language input from users, typically using techniques such as natural language processing (NLP) and machine learning algorithms.
Where can we use conversational AI?
Conversational AI can be used in various applications such as customer service chatbots, virtual assistants in mobile devices, smart home devices, and even in healthcare for patient engagement and support.
What is an example of AI in communication?
An example of AI in communication is chatbots integrated into messaging platforms like Facebook Messenger or Slack, where they assist users with inquiries, schedule appointments, or provide information, all through conversational interactions.
What is the difference between chatbot and conversational AI?
While a chatbot typically refers to a program designed to respond to user inputs in a conversational manner, conversational AI encompasses a broader spectrum of technologies and techniques used to enable machines to engage in natural language conversations, including but not limited to chatbots.
What is the difference between AI and conversational AI?
AI refers to the broader field of creating intelligent machines capable of performing tasks that typically require human intelligence, whereas conversational AI specifically focuses on enabling machines to engage in natural language conversations with users, understanding context and intent to provide meaningful responses.
Read more:
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- How to build conversational AI?
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