New York, June 08, 2023 (GLOBE NEWSWIRE) -- According to MarketResearch.biz, the Generative AI in customer Service market size is projected to surpass around USD 2,103.0 million by 2032, and it is poised to reach a registered CAGR of 24.2% from 2023 to 2032.
Generative AI in customer service is the technology that uses machine learning algorithms for generating responses & engage in conversations with customers. This technology can help businesses to automate routine tasks like answering frequently asked questions or processing simple requests, freeing up human agents to handle more complex customer issues.
Generative AI can also be trained to understand customer preferences and made responses accordingly, leading to more personalized and satisfying interactions. Additionally, generative AI can learn and adapt over time which allows it to continuously improve its performance & accuracy. With generative AI, businesses can provide 24/7 support to customers, improve efficiency & reduce costs, and ultimately, enhance the overall customer experience.
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Key Takeaway:
- Based on application, in 2022, the generative AI in customer service market was dominated by the chatbot segment owing to their ability to provide quick & efficient customer service at low cost.
- By industry, in 2022, the healthcare industry segment dominated the largest market share in an industry segment.
- By deployment, in 2022, the cloud-based segment dominated the largest market share in the deployment segment.
- In 2022, North America dominated the market with the highest revenue share of 46.5%.
- Asia-Pacific is expected to have the highest CAGR among all regions, owing to heavy investments in AI research & development.
Factors affecting the growth of Generative AI in Customer Service industry
There are several factors that can have an impact on the growth of the generative AI in customer service industry includes:
- Growth of the e-commerce industry: The growth of the e-commerce industry and the rise of online transactions have led to a surge in customer inquiries which is making it difficult for businesses to manage customer service with human agents alone. This has led to the need for automation with generative AI being a usable solution.
- Increasing advancements in natural language processing: the increasing advancements in natural language processing (NLP) technology have improved the accuracy & effectiveness of generative AI in customer service. With better NLP technology, AI can better understand customer queries and provide more relevant & accurate responses.
- A large amount of customer data: the availability of large amounts of customer data has enabled businesses to train AI models to better understand customer needs & preferences. This has led to more effective and personalized interactions between customers and AI-powered customer service systems.
- Low implementing cost: the decreasing costs of implementing & maintaining AI systems have made it more affordable for businesses of all sizes to adopt generative AI in their customer service operations.
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Top Trends in Generative AI in Customer Service Market
The latest trends for generative AI in the consumer services market include fraud detection, image & video generation, conversational AI, personalization, virtual assistants, and gaming. Companies use generative AI to personalize customer experiences by creating personalized content & recommendations. Conversational AI systems automate routine tasks like answering frequently asked questions. Virtual assistants help customers with their shopping experiences. The use of AI to generate high-quality images & videos for marketing and advertising purposes is another trend. Fraud detection is a trend where AI is used to detect fraudulent activities & prevent them before they occur. In the gaming industry, generative AI is used to create more realistic environments & characters and also to generate game content.
Market Growth
The demand for generative AI in customer service is being driven by several factors which include the increasing need for personalized & efficient customer service experiences, the growth of e-commerce & online transactions, and the availability of large amounts of customer data that can be leveraged to train AI models. Furthermore, the COVID-19 pandemic has accelerated the adoption of generative AI in customer service as many businesses have shifted to remote work environments and found ways to continue providing support to customers. This has led to a greater need for automation and AI-powered customer service solutions. The generative AI in the customer service market is expected to see growth across various industries which includes retail, healthcare, finance, and telecommunications.
Regional Analysis
North America is accounted as the most dominant market in the global generative AI in customer service market with a market share of 46.5%, during the forecasted period. North America is the leader in AI research & development for many years. It continues to lead the market when it comes to generative AI. There are established AI companies & research institutions in these regions that are developing cutting-edge generative AI technologies. These industries include healthcare, finance, entertainment, and entertainment.
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Scope of the Report
| Report Attribute | Details |
| Market Value (2022) | USD 254.2 Mn |
| Market Size (2032) | USD 2,103.0 Mn |
| CAGR (from 2023 to 2032) | 24.2% |
| North America Revenue Share | 46.5% |
| Historic Period | 2016 to 2022 |
| Base Year | 2022 |
| Forecast Year | 2023 to 2032 |
Market Drivers
There are many drivers behind the adoption of generative AI in the consumer services market. One main driver is the growing demand for personalized customer experience. Today's consumers expect companies to offer them customized content & recommendations. Generative AI can help companies meet these demands by creating personalized experiences for each customer. Another driver is the demand for automation & efficiency in customer service. Generative AI automates routine tasks like answering frequently asked questions, allowing customer service representatives to focus more on complex issues. This can result in improved efficiency & cost savings for businesses. The increasing volume of data from customers is also driving the adoption and use of generative AI. Companies are using generative AI for analyzing the data and gain insights into customer behaviour. The increasing competition in the consumer services sector is also driving companies to invest in generative AI. By utilizing this technology, companies can improve their customer service abilities & differentiate themselves from competitors.
Market Restraints
There are few restraints to the adoption of generative AI in the consumer services market. The lack of privacy regulations can cause companies to be concerned about how they are using customer data for training their generative AI models. Many consumers may be hesitating to share their data with companies that use generative AI. This can limit the effectiveness of the technology in improving customer experience. The cost & complexity of implementing generative AI technology can also make it difficult for small companies to adopt it. There may also be resistance from employees, who fear that generative AI technology will replace their job. This could lead to conflicts with management. There may also be cultural or social barriers to the adoption of generative AI. Some customers may prefer human interaction to automated systems. Other than these restraints, many companies continue to invest in generative AI to improve their customer service and gain a competitive advantage in the market.
Market Opportunities
There are many opportunities for generative AI in the consumer services market. One big opportunity is the ability to customize the customer experience. This can lead to increased satisfaction & loyalty. By using generative AI, companies can create personalized content & recommendations for individual clients by improving engagement and overall satisfaction. Additionally, generative AI also can be used for automating routine tasks like answering frequently asked questions. This allows customer service representatives to focus their attention on more complex tasks. This can result in increased efficiency & cost savings for businesses. Fraud detection is another area where generative AI could be used. It can analyze patterns of data to identify fraudulent activities & prevent them before they occur. Finally, generative artificial intelligence can be used to create realistic images and videos to help companies better showcase their products & services.
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Report Segmentation of the Generative AI in Customer Service Market
Application Insight
The chatbot segment will be the most lucrative within the global generative AI market for customer services with a revenue share of 42.7% and a projected CAGR of 24.6% over the forecast period. Owing to this they can provide fast & efficient service at low cost. They are very effective at automating routine tasks like answering frequently asked questions. This allows customer service representatives to concentrate on more complex tasks. Chabot's can operate 24/7, providing customers with round-the-clock support & reducing the response time which leads to improved customer satisfaction.
Industry Insight
The healthcare industry segment dominates the type segment of the generative AI market in customer services with a revenue share of 43.8% and a CAGR of 24.2%. Growing demand for better patient care and outcomes. Medical imaging analysis is one of the main areas where generative AI in healthcare is being used. Using generative AI to help physicians diagnose and identify medical conditions more accurately and efficiently is a way to use the growing volume of medical imaging data.
Deployment Insight
The cloud-based segment dominates the deployment segment of generative AI for customer services with a market value of 45.7% and a CAGR of 24.4%. Cloud-based solutions are scalable, allowing companies to easily adjust resources to match changes in demand. Additional hardware or infrastructure is not required. These solutions are also more flexible & accessible as customers & employees can access them from anywhere they have an internet connection. Cloud-based solutions are usually more cost-effective than on premise solutions as they don't require large initial investments or ongoing costs.
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Market Segmentation
Based on Application
- Chatbot
- Virtual Assistants
- Personalized Recommendation’s
- Sentiment Analysis
Based on Industry
- Healthcare
- Retail
- Finance
- Telecommunications
Based on Deployment
- Cloud-based
- On-premise
- Hybrid
Key Regions
- North America
-
- The US
- Canada
- Mexico
- Western Europe
- Germany
- France
- The UK
- Spain
- Italy
- Portugal
- Ireland
- Austria
- Switzerland
- Benelux
- Nordic
- Rest of Western Europe
- Eastern Europe
- Russia
- Poland
- The Czech Republic
- Greece
- Rest of Eastern Europe
- APAC
- China
- Japan
- South Korea
- India
- Australia & New Zealand
- Indonesia
- Malaysia
- Philippines
- Singapore
- Thailand
- Vietnam
- Rest of APAC
- Latin America
- Brazil
- Colombia
- Chile
- Argentina
- Costa Rica
- Rest of Latin America
- Middle East & Africa
- Algeria
- Egypt
- Israel
- Kuwait
- Nigeria
- Saudi Arabia
- South Africa
- Turkey
- United Arab Emirates
- Rest of MEA
Competitive Landscape
The market for generative AI in customer service is still evolving & expanding rapidly with the large number of players competing for market share. The market for generative AI in customer service is highly competitive, with a large number of players offering a range of AI-powered solutions. The key players in this market are those who have developed strong AI capabilities & have a track record of delivering high-quality customer service solutions.
Key Market Players:
Listed below are some of the most important generative AI in customer service industry players.
- Microsoft Corporation
- IBM Corporation
- Amazon Inc.
- Google Inc.
- Oracle Corporation
- Haptic Technology
- Other Key Players
Recent Developments of the Generative AI in Customer Service Market
- In September 2021, Adobe announced a new feature for Photoshop, called "Neural Filters," which uses generative AI to apply complex adjustments to images.
- In June 2021, NVIDIA unveiled its new generative AI model, called DALL-E 2, which can generate highly realistic images from textual descriptions.
- In May 2021, OpenAI announced the release of its new language model, GPT-3, which has 175 billion parameters, making it the largest language model to date
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- Generative AI in Customer Service Market size is expected to be worth around USD 2,103.0 Mn by 2032 from USD 254.2 Mn in 2022, growing at a CAGR of 24.20% during the forecast period from 2023 to 2032.
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