市场调查报告书
商品编码
1466390
客服中心人工智慧市场:按元件、应用程式、部署、组织、产业划分 - 2024-2030 年全球预测Call Center AI Market by Component (Services, Software), Application (Agent Performance Management, Appointment Scheduling, Journey Orchestration), Deployment, Organization, Vertical - Global Forecast 2024-2030 |
※ 本网页内容可能与最新版本有所差异。详细情况请与我们联繫。
预计2023年客服中心人工智慧市场规模为24亿美元,2024年预估达29亿美元,2030年将达98.5亿美元,复合年增长率为22.34%。
客服中心人工智慧,也称为客服中心人工智慧,充当自动化系统,旨在简化客户交互,同时提高效率和生产力。这项先进的技术使用机器学习演算法和自然语言处理来理解、解释和回应客户的询问,提供 24/7 虚拟援助。客服中心人工智慧软体可自动执行呼叫路由、资料收集和日常客户查询等任务,减少人工参与,使员工能够专注于更复杂和定性的任务。人工智慧和机器学习技术的进步、数位化的提高以及客户服务业务对成本效益的需求正在加速对客服中心人工智慧的需求。然而,资料隐私问题、技术故障和故障的风险以及实施和维护人工智慧解决方案的成本正在阻碍其普及。开拓公司透过先进的预测分析来解决隐私问题,以实现更准确的资料预测,支援人工智慧的培训模组可提高代理绩效,类人对话人工智慧可提高客户参与。方案。随着该领域的积极研发,客服中心AI市场可望成为未来利润丰厚的投资领域。
主要市场统计 | |
---|---|
基准年[2023] | 24亿美元 |
预测年份 [2024] | 29亿美元 |
预测年份 [2030] | 98.5亿美元 |
复合年增长率(%) | 22.34% |
组件 开发高效能客服中心人工智慧软体以改善客户体验
服务包括客服中心人工智慧实施和营运的专业服务和支援服务。专业服务包括咨询、系统整合、客製化和培训,帮助企业有效实施人工智慧解决方案。支援服务包括维护技术支援和持续协助,以确保客服中心AI的顺利运作。客服中心人工智慧领域的第二个组成部分是软体,包括自动回应、简化呼叫流程和提供客户分析的解决方案。许多公司更喜欢提供丰富的人工智慧实施并确保根据其要求轻鬆整合和客製化的软体解决方案。客服中心人工智慧软体解决方案可实现自动化、销售服务、即时资料分析、客户关係管理以及与客服中心应用程式的整合。呼叫路由和互动语音回覆系统(IVR) 系统、预测分析软体和情绪分析工具是客服中心人工智慧的一些关键工具。
部署:云端客服中心人工智慧提供扩充性、成本效益和易于更新
客服中心人工智慧的云端部署是许多公司选择的可存取、可扩展且经济高效的解决方案。云端部署通常最适合工作负载波动的企业或需要自动线上更新人工智慧软体的企业。它也适合希望降低硬体、软体和内部 IT 人员成本的企业。重视对其解决方案和资料进行细粒度控制的公司更喜欢本地部署客服中心人工智慧。这些解决方案特别适合拥有大量 IT 资源和监管要求的大型企业,以将资料保存在自己的基础架构内。
快速普及人工智慧来优化应用客服中心的座席效能
人工智慧可以透过提供即时回馈和绩效指标来帮助监控和提高座席绩效。人工智慧用于衡量代理的有效性和效率,以确保无缝的客户服务。人工智慧透过优化客服人员时间和提高客户满意度来帮助有效安排预约。借助人工智慧系统,绘製和简化客户旅程变得更加顺畅,确保与客户的个人化联繫。预测呼叫路由采用人工智慧根据资料分析有目的地路由客户呼叫。市场相关人员正在将客户情绪和偏好纳入其路由演算法中,以提供更好的服务。客服中心的人工智慧使用情绪分析来确定客户对产品和服务的态度。领先的供应商正在使用人工智慧来分析词彙、音调和语气,以更好地了解客户的气质。借助工作流程自动化和智慧调度,人工智慧技术将机器学习整合到平台中,优化劳动力管理并释放劳动力的全部潜力。
分区:客服中心AI在银行、金融、保险等领域广泛应用
BFSI 领域继续需要增强人工智慧,以改善客户交互,例如帐户查询和提供有关金融产品的资讯。医疗保健领域的人工智慧支援临床决策和患者检查,并为预约安排和图表管理提供协助。在媒体和娱乐领域,人工智慧有助于个人化和推荐内容。演算法分析用户偏好和观看习惯并提供个人化内容,从而提高用户参与度。从库存管理到个人化购物体验,人工智慧正在为零售和电子商务提供帮助。人工智慧演算法还根据需求、竞争等因素调整产品价格,以扩大盈利。在通讯业,人工智慧可以帮助通讯业者维护网路健康并改善客户服务。人工智慧监控网路效能,识别问题并预测不间断服务的维护,这些品质可以有利于客服中心代理提供更好的服务。旅游和酒店业中的人工智慧可改善客户预订体验并优化业务效率。人工智慧将追踪您的旅行行程,发送更新并提供有关当地景点的资讯。
区域洞察
在美洲,客服中心人工智慧被广泛采用,主要是在美国和加拿大,这是为最终用户提供多样化解决方案的主要技术提供者的所在地。随着这些技术提高生产力,电子商务平台、电信业者和金融服务正在实现积极成长。在日本、韩国和新加坡等技术先进国家,人工智慧正在整合到客服中心中,以提供多语言支援和即时客户协助。在印度和菲律宾等新兴经济体,人工智慧新兴企业在客服中心人工智慧市场不断涌现。亚洲也是客服中心的重要外包地点,越来越多地采用人工智慧解决方案来处理日益增加的客户互动。欧洲注重资料保护和客户隐私,精心实施了客服中心人工智慧,以确保 GDPR 合规性。在德国、法国和英国等国家,人工智慧聊天机器人和语音助理越来越受欢迎,并保证 24/7 客户支援。在东欧,医疗保健和通讯业的采用正在取得进展,重点是对现有员工进行人工智慧技术培训,以确保无缝过渡。
FPNV定位矩阵
FPNV定位矩阵对于评估客服中心 AI市场至关重要。我们检视与业务策略和产品满意度相关的关键指标,以对供应商进行全面评估。这种深入的分析使用户能够根据自己的要求做出明智的决策。根据评估,供应商被分为四个成功程度不同的像限:前沿(F)、探路者(P)、利基(N)和重要(V)。
市场占有率分析
市场占有率分析是一个综合工具,可以对客服中心人工智慧市场中供应商的现状进行深入而深入的研究。全面比较和分析供应商在整体收益、基本客群和其他关键指标方面的贡献,以便更好地了解公司的绩效及其在争夺市场占有率时面临的挑战。此外,该分析还提供了对该行业竞争特征的宝贵见解,包括在研究基准年观察到的累积、分散主导地位和合併特征等因素。这种详细程度的提高使供应商能够做出更明智的决策并制定有效的策略,从而在市场上获得竞争优势。
1. 市场渗透率:提供有关主要企业所服务的市场的全面资讯。
2. 市场开拓:我们深入研究利润丰厚的新兴市场,并分析其在成熟细分市场的渗透率。
3. 市场多元化:提供有关新产品发布、开拓地区、最新发展和投资的详细资讯。
4. 竞争评估和情报:对主要企业的市场占有率、策略、产品、认证、监管状况、专利状况和製造能力进行全面评估。
5. 产品开发与创新:提供对未来技术、研发活动和突破性产品开发的见解。
1.客服中心AI市场的市场规模与预测为何?
2.客服中心人工智慧市场预测期间需要考虑投资的产品、细分市场、应用程式和领域有哪些?
3.客服中心AI市场的技术趋势和法规结构是什么?
4.客服中心AI市场主要厂商的市场占有率如何?
5.进入客服中心AI市场合适的型态和策略手段是什么?
[184 Pages Report] The Call Center AI Market size was estimated at USD 2.40 billion in 2023 and expected to reach USD 2.90 billion in 2024, at a CAGR 22.34% to reach USD 9.85 billion by 2030.
Call center AI, also known as artificial intelligence in call centers, functions as an automated system designed to streamline customer interactions while enhancing efficiency and productivity. This sophisticated technology utilizes machine learning algorithms and natural language processing to understand, interpret, and respond to customer inquiries, providing 24/7 virtual assistance. Automating tasks such as call routing, data collection, and routine customer queries with call center AI software reduces human involvement, allowing staff to focus on more complex and qualitative tasks. Advancements in AI and machine learning technologies, the push towards digitization, and the need for cost-effectiveness in customer service operations have accelerated the demand for call center AI. However, data privacy issues, the risk of technology failure or glitches, and the cost of implementing and maintaining AI solutions have impeded their widespread adoption. Market players are developing advanced predictive analytics for more accurate demand forecasting, AI-enabled training modules for enhancing agent performance, human-like conversational AI for better customer engagement, and secure data handling solutions that address privacy concerns. Rigorous research and development in these areas is expected to make the call center AI market a lucrative area for investment in the future.
KEY MARKET STATISTICS | |
---|---|
Base Year [2023] | USD 2.40 billion |
Estimated Year [2024] | USD 2.90 billion |
Forecast Year [2030] | USD 9.85 billion |
CAGR (%) | 22.34% |
Component: Development of high-performing call center AI software to provide enhanced customer experience
Services include professional and support services related to call center AI implementation and operation. Professional services cover consulting, system integration, customization, and training to help businesses implement AI solutions effectively. Support services encompass maintenance technical support and ongoing assistance to ensure the smooth operation of call center AI. Software, the second component of the Call Center AI field, entails solutions that automate responses, streamline call flows, and offer customer analytics. Many businesses prefer software solutions that provide high-functioning AI implementations, ensuring ease of integration and customization according to their requirements. Call center AI software solutions enable automation, sell service, real-time data analysis, and integration with customer relationship management and contact center applications. Call routing and interactive voice response (IVR) systems, predictive analytics software, and sentiment analysis tools are some of the major call center AI tools utilized.
Deployment: Increased scalability, cost-effectiveness, and ease of updates offered by on-cloud call center AI
On-cloud deployment of call center AI has emerged as a preferred choice for many businesses as this model facilitates accessible, scalable, and cost-effective solutions. On-cloud deployment is generally ideal for businesses with fluctuating workloads and those that need online and automated updates to their AI software. It is also suitable for organizations seeking to cut down on hardware, software, and in-house IT staffing costs. On-premises deployment of call center AI is preferred by businesses emphasizing granular control over their solution and data. These solutions are particularly suitable for larger organizations with significant IT resources and regulatory requirements to keep data within their own infrastructure.
Application: Exponential adoption of AI for optimizing agent performance in call centers
AI can assist in monitoring and improving agent performance by providing real-time feedback and performance metrics. AI is used to measure the effectiveness and efficiency of agents to ensure seamless customer service. AI aids in scheduling appointments effectively by optimizing agents' time and improving customer satisfaction. Mapping and streamlining customer journeys are made smoother by AI systems, ensuring personalized connections with customers. Predictive call routing employs AI to route customer calls purposefully based on data analysis. Market players are incorporating customer emotions and preferences into routing algorithms to offer improved services. AI in call centers uses sentiment analysis to determine customers' attitudes toward products or services. Major providers use AI to analyze words, pitch, and tone to understand customer temperament better. Through workflow automation and intelligent scheduling, AI technologies optimize workforce management by integrating machine learning into its platform to maximize workforce potential.
Vertical: Extensive usability of call center AI in banking, finance, and insurance sectors
The BFSI sector continually requires AI enhancements to improve customer interactions by offering assistance with account inquiries and information on financial products. AI in healthcare aids in clinical decision-making and patient consultations while offering help with appointment scheduling and medical records management. In media and entertainment, AI assists with content personalization and recommendation as the algorithms analyze user preferences and viewing habits to offer personalized content, improving user engagement. From inventory management to personalized shopping experiences, AI proves instrumental in the retail & eCommerce sector. AI algorithms also adjust product pricing based on demand, competition, and other factors to expand profitability. AI assists telecom operators in maintaining the network's health and improving customer service in the telecommunications industry. AI monitors network performance, identifies issues, and predicts maintenance for uninterrupted service, and these qualities can benefit the call center agent to provide better services. AI in travel and hospitality enhances customer booking experiences and optimizes operational efficiency. AI complies with travel itineraries, sends updates, and provides information on local attractions.
Regional Insights
In the Americas, call center AI has been widely adopted, mainly in the U.S. and Canada, being home to major technology providers offering diverse solutions for end-users. E-commerce platforms, telecommunication companies, and financial services have shown positive growth and productivity enhancements due to these technologies. Predominantly in technologically advanced countries like Japan, South Korea, and Singapore, AI has been integrated into call centers, providing multilingual support and real-time customer assistance. In developing economies of India, the Philippines, and others, AI startups are emerging in the call center AI market. Asia is also a significant outsourcing hub for call centers, and the adoption of AI solutions is on the rise to handle the increasing volume of customer interactions. Europe's emphasis on data protection and customer privacy has cautiously implemented call center AI, ensuring GDPR compliance. AI-powered chatbots and voice assistants have gained popularity in nations such as Germany, France, and the UK, guaranteeing 24/7 customer support. In Eastern Europe, markets are catching up with the adoption across healthcare and telecom industries, focusing on training the existing workforce about AI technologies to ensure a seamless transition.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the Call Center AI Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
Market Share Analysis
The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Call Center AI Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.
Key Company Profiles
The report delves into recent significant developments in the Call Center AI Market, highlighting leading vendors and their innovative profiles. These include Artificial Solutions, Avaya Holdings Corp., Cognigy GmbH, Conversica, Inc., Cresta Intelligence, Inc., Dialpad, Inc., Five9, Inc. by Zoom Video Communications, Inc., Gemshelf Inc., Google, LLC by Alphabet, Inc., Inbenta Technologies Inc., Infinitus Systems, Inc., International Business Machines Corporation, Jio Haptik Technologies Limited, Kore.ai, Inc., Level AI, LivePerson, Inc., Microsoft Corporation, Nextiva, Inc., Oracle Corporation, Parloa GmbH, PolyAI Limited, Pypestream Inc., Replicant Solutions, Inc., RingCentral, Inc., Rulai, Inc., SAP SE, Skit USA, Inc., Talkdesk, Uniphore Technologies Inc., and Zendesk, Inc..
Market Segmentation & Coverage
1. Market Penetration: It presents comprehensive information on the market provided by key players.
2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
1. What is the market size and forecast of the Call Center AI Market?
2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Call Center AI Market?
3. What are the technology trends and regulatory frameworks in the Call Center AI Market?
4. What is the market share of the leading vendors in the Call Center AI Market?
5. Which modes and strategic moves are suitable for entering the Call Center AI Market?