AI / MACHINE LEARNING

AI for Customer Service Market worth $47.82 Billion by 2030 – Exclusive Report by MarketsandMarkets™

AI adoption in customer service is increasingly focused on implementing proactive solutions that allow businesses to anticipate customer needs and address potential issues before they escalate. This shift from reactive to proactive service fosters trust and loyalty, as highlighted by Genesys, where 72% of customer experience leaders believe AI will enable all proactive service outreach in the future.

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he AI for Customer Service Market is expected to reach USD 12.06 billion by 2024 from USD 47.82 billion in 2030, at a CAGR of 25.8% during 2024–2030, according to new research report by MarketsandMarkets™

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320 – Tables
70 – Figures
350 – Pages

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Scope of the Report

AI adoption in customer service is increasingly focused on implementing proactive solutions that allow businesses to anticipate customer needs and address potential issues before they escalate. This shift from reactive to proactive service fosters trust and loyalty, as highlighted by Genesys, where 72% of customer experience leaders believe AI will enable all proactive service outreach in the future. By leveraging predictive analytics, companies can analyze historical data to forecast customer behavior, facilitating timely interventions. This approach not only resolves issues before they arise but also strengthens customer relationships, leading to increased retention and loyalty. As businesses prioritize customer experience, the demand for AI-driven proactive solutions is expected to grow significantly in the coming years.

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Boosting Efficiency and Customer Satisfaction Through Intelligent Routing

AI adoption in customer service is driven by intelligent routing, which optimizes efficiency and customer satisfaction. By utilizing advanced algorithms and data analytics, this technology ensures inquiries are directed to the most suitable agent, reducing wait times and improving match accuracy. According to NICE, AI-driven routing minimizes average handle time (AHT) while boosting customer satisfaction (CSAT) scores. For example, a leading healthcare provider achieved an 8% reduction in AHT and a 5% increase in CSAT. Additionally, Dialzara notes that intelligent routing automates routine tasks, allowing agents to focus on more complex issues. The integration of natural language processing (NLP) and predictive analytics further enhances personalization, improving customer experiences and loyalty. As companies seek a competitive edge, intelligent routing is a key driver of AI adoption in customer service.

In customer service delivery mode, self-service segment is to lead the market during the forecast period.”

The self-service delivery mode is increasingly leading the AI for customer service market as consumers demand faster, more efficient support. Recent studies by Alltius indicate that 81% of customers prefer resolving issues through self-service options rather than interacting with live agents, reflecting a significant shift in consumer behavior. AI technologies, such as chatbots and virtual assistants, are at the reason of this transformation, as they provide immediate assistance and personalized experiences 24/7. Salesforce reports that 61% of customers use self-service channels for simple queries, indicating a significant shift in consumer behavior towards self-sufficiency. These channels alleviate the burden on customer service agents, allowing them to focus on more complex issues. Moreover, Atlassian emphasizes that effective self-service systems require a well-structured knowledge base and user-friendly interfaces. By integrating various support tools into a cohesive platform, organizations can enhance customer satisfaction while reducing operational costs.

By technology, the other AI segment will contribute the higher market share during the forecast period

Other AI technologies such as Natural Language Processing (NLP), Deep Learning, and Robotic Process Automation (RPA), dominate the market due to their versatility and transformative capabilities across customer service or support. NLP facilitates sentiment analysis, chatbots, and voice assistants, allowing businesses to provide personalized interactions. For instance, IBM Watson leverages NLP to power virtual agents that enhance customer engagement. Deep learning improves predictive analytics for better decision-making and proactive support, as seen in Google Cloud AI’s offerings. RPA automates repetitive tasks like ticket management and data entry, streamlining workflows; UiPath excels in this area with its automation solutions. Together, these technologies significantly boost efficiency and customer satisfaction while reducing costs.

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By region, North America will lead the AI for customer service market during the forecast period.

North America leads in AI for customer service, driven by the United States and Canada’s advanced technological infrastructure and widespread adoption of AI solutions. The U.S. boasts a strong technological infrastructure, with a high density of tech companies and startups such as Netomi, Intercom driving innovation in customer service solutions. The increasing emphasis on enhancing customer experiences drives businesses to adopt AI technologies that provide real-time insights and personalized interactions. Moreover, the growing consumer preference for digital engagement channels further accelerates the integration of AI in customer service strategies.

In Canada, firms like NICE and kore.ai are leading the charge in AI for customer service, focusing on enhancing self-service capabilities and automating routine inquiries. The Canadian market prioritizes improving customer satisfaction through efficient service delivery. Ada is also notable for its innovative approach to customer engagement, utilizing AI-driven solutions to facilitate seamless interactions across various channels. The emphasis on generative AI technologies allows businesses to provide more intuitive support, ensuring quick resolutions and fostering customer loyalty.

Top Key Companies in AI for Customer Service Market

Some major players in the AI for customer service Market include Microsoft (US), IBM (US), Google (US), AWS (US), Salesforce (US), Atlassian (Australia), ServiceNow (US), SAP (Germany), Zendesk (US), Sprinklr (US), OpenAI (US), Aisera (US), UiPath (US), HubSpot (US), NICE (Israel), Intercom (US),Qualtrics (US), Freshworks (US), LivePerson (US), HelpShift (US), Yellow.ai (US), Cogito (US), SmartAction (US), Talkdesk (US), Five9 (US), RingCentral (US), Nextiva (US), Kore.ai (US), Dynamic Yield (US), Jio Haptik (India), Oracle (US), Afiniti (Bermuda), Kommunicate (US), Help Scout (US), Gorgias (US), Atera (Israel), Ada (US), Kustomer (US), Levity (Germany), Cognigy (Germany), Engageware (US), Netomi (US), Level AI (US), Sybill AI (US), OneAI (US), Brainfish (Australia), SentiSum (England), Balto (US), Tovie AI (UK), Guru (US), Tidio (US), Quiq (US), Aircall (US), OneReach.ai (US), Cresta (US), Deepdesk (Netherlands), Front (US), Fullview (Denmark), Crescendo AI (US), Gridspace (US).

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