20 Key Conversational AI Use Cases in the Arab World in 2023
Among artificial intelligence technologies, conversational AI is quickly becoming the most popular. Increasingly, businesses in the Arab world are using it to manage their teams or better serve their customers while remaining competitive.
The significant impact of Conversational AI is evidenced by predictions that more than 95% of customer interactions will be handled using AI by 2025.
Additionally, it is estimated by the same year that the size of the artificial intelligence market is expected to reach USD $1.3 billion, growing at a 24% compound annual growth rate.
As this market is expanding tremendously in the Arab region, we can see conversational AI examples or use cases in a wide variety of industries and business functions such as customer service, marketing, sales or even automating internal operations.
In this article, we will explore the most popular conversational AI use cases that are found across diverse fields in many of Arab countries.
5 Conversational AI Use Cases in Customer Service
Customer service represents the most prominent areas of business where conversational AI has a substantial impact. As customers demand quick solutions and personalized help, AI-powered digital assistants are indispensable tools.
Using AI chatbots can save 2.5 billion hours of customer service, and thus help to reduce the costs of the service by $11 billion annually.
Conversational AI alternatives can be integrated into customer service processes to achieve the following:
1. Automating customer support
Implementing conversational AI platforms on a business website optimizes operational efficiency and facilitates customer interaction.
AI chatbots have proven to be effective at resolving common queries while reducing the need for human interaction. As a result, customers will have a seamless experience at each stage of the service journey.
Read more about ➡️ What Is Customer Service Automation? And Why Is It Important?
2. Enhance agent experience
AI solutions help agents do their tasks better. Customer support representatives can answer tickets much faster and maintain high-quality interactions with customers by using conversational AI interfaces.
3. Provide more self-service
By developing tools that can better leverage your knowledge base and company data, you can help customers serve themselves better.
Conversational AI applications can deliver answers to common queries or the most frequently asked questions, giving customers what they're looking for and freeing agents from handling repetitive tasks.
4. Increase customers engagement
Conversational AI platforms can help to attract leads by focusing on users who already know the company after entering its portal. Traffic from visitors to the website can result in new leads.
Interacting with chatbots when users are viewing products or services on businesses' online stores is an excellent means to engage them.
Read also ➡️ How Can Conversational AI Boost Customer Engagement in 2023?
5. Helping to collect customer feedback
Using conversational AI-powered chatbots is an effective tool for acquiring customer feedback, which is crucial for aligning products and services with customer requirements and expectations and improving business productivity.
3 Key eCommerce Chatbot Use Cases
The global e-commerce market is very large and continues to grow year over year. It is estimated to total $5.717 trillion in 2022, and projected to reach $8.148 trillion in 2026. And by 2023, it is predicted that e-commerce transactions via chatbots will reach $112 billion.
With such a massive volume of the eCommerce market, there is clearly a tremendous opportunity to utilize conversational AI for business in e-commerce via the following methods:
1. Automation of the purchasing processes
Conversational AI applications can help companies and customers automate their online purchases, create repeat orders, and resolve any problems they may experience.
2. Provide effective and attractive shopping platforms
AI chatbots can be used to be an all-in-one point of sale where consumers can complete the entire customer journey by checking out without leaving the chat window.
Chatbots can also be used for upselling and cross-selling as they can suggest products in a conversational manner with a brief explanation.
3. Streaming insightful data
Chatbots empowered by conversational AI can actually provide very insightful data for businesses as a whole. This process is carried out continuously in order to help brands learn about customer buying habits, get feedback, and help to put strategies for scaling.
Top 3 Use Cases of Conversational AI in Insurance
The insurance sector is evolving through digital transformation as it leverages artificial intelligence capabilities to enhance its processes.
According to (McKinsey), 10% to 55% of the work performed by major functions of insurance companies, including actuarial, claims, underwriting, finance, and operations, could be automated within the next decade, while 10% to 70% of tasks will change significantly in scope.
Conversational AI applications help insurance agencies make adjustments in order to overcome several challenges faced by insurers. The following are some examples:
1. The assessment of risk
Thanks to the advent of machine learning algorithms, insurance agents and underwriters can now gain access to more information and data to gauge the risk insurance companies take on.
Artificial intelligence capabilities allow insurance agents to take in greater amounts of data and assess risks more accurately.
2. The detection of fraud
Issues surrounding insurance can seem complicated and insurers face many challenges related to false claims; people often conceal information on insurance applications to get better coverage or lower premiums.
Artificial intelligence applications can help detect fraud by having accuracy parameters set on applications in order to ensure that the information being sent in is accurate and truthful.
3. Reducing the incidence of human errors
Insurance policies have a long and complex chain of intermediaries between the insured and the insurer who examine information. Manual work and human error can lead to the loss of a lot of information.
Conversational AI applications minimize human error by analyzing documents and data for users, thus reducing the possibility of making miscalculations.
Read also ➡️ How to Improve Customer Satisfaction Using Chatbots in 2023?
Top 3 Conversational AI Use Cases in Banking
Conversational artificial intelligence is increasingly used in banking and financial services to help lower operating costs, automate processes, and enhance customer service.
According to (JuniperResearch) the operational cost savings from using chatbots in banking will reach $7.3 billion globally by 2023, up from an estimated $209 million in 2019. This represents time saved for banks in 2023 of 862 million hours, equivalent to nearly half a million working years.
Due to the increase in users' preference for app-based banking, and the strong performance of early banking digital agents, chatbot integration in mobile banking applications will be the dominant channel for chatbot-driven customer communications, accounting for 79% of successful interactions in 2023.
The following are some of banking's use cases of conversational artificial intelligence:
1. Automating financial processes
Conversational AI can be used to help resolve customer queries by automating repetitive processes that take a human agent a long time to complete. It can help in account management, including checking user balances and processing transactions across all bank accounts.
2. Detecting fraud
Conversational AI applications can be employed to prevent fraud by identifying phrases or keywords that may indicate fraudulent activity using automatic speech recognition.
3. Analyzing data
Conversational AI applications can be leveraged to assess customers’ banking tendencies, using the information as a basis for creating customer-centric initiatives and goals.
Top 3 Conversational AI Use Cases in Healthcare
Nowadays, conversational AI is increasingly being adopted in healthcare. By automating tedious processes, it has considerably improved the quality of service.
The most prominent conversational AI use cases in healthcare are as follows:
1. Scheduling appointments
Chatbots can arrange appointments based on a doctor’s availability. Specifically designed AI digital agents can integrate with CRM systems such as Microsoft Dynamics or Salesforce to help staff track visits and follow-up appointments for a particular patient.
Also, Patients can be engaged in the post-treatment phase with conversational AI in healthcare.
2. Assessing symptoms
Symptom checker bots can act as the first point of contact between patients and hospitals enabling them to reach a healthcare provider via phone call, video call, telehealth, or in-person visit.
3. Escalation of emergency cases
During health crises, conversational AI platforms could be used to focus on screening patients and triaging treatment by collecting patients’ symptom data and instructing them to take proper action accordingly.
Conclusion
Conversational AI continues to progress, turning into the most popular technology nowadays, and becoming an essential element in numerous fields such as:
- Customer service
- Ecommerce
- Insurance
- Banking
- Healthcare, and others.
With time, the capabilities of conversational AI keep innovating to provide more advantages and opportunities to both businesses and customers alike.
As such, if you want your business to be competitive, conversational AI is the way to maintain your advantage.
DXwand, the leading conversational AI technologies provider in the Middle East, offers a wide range of feature-rich conversational AI tools that can help evolve your organization.
Find limitless revenue-building opportunities with every customer interaction by starting using one of our solutions that are best suited for your business.