글로벌 소매업 분야 인공지능 시장 – 2023-2030

Global Artificial Intelligence In Retail Market - 2023-2030

상품코드ICT7002
발행기관DataM Intelligence
발행일2023.10.11
페이지 수197 Pages
포맷PDF + EXCEL
커버리지Global

6,525,00011,775,000

보고서 요약(국문)

개요
전 세계 소매 부문 인공지능(AI) 시장은 2022년 55억 달러 규모에 달했으며, 2023년부터 2030년까지 연평균 34.2%의 성장률을 기록하며 2030년에는 554억 달러에 이를 것으로 예상됩니다.
AI는 소매업체가 제품 추천, 고객 서비스용 챗봇, 가상 체험 등 개인화된 쇼핑 경험을 제공할 수 있도록 지원하여 고객 만족도와 충성도를 향상시킵니다. AI 기반 시스템은 공급망 관리, 재고 관리, 수요 예측을 최적화하여 비용 절감과 운영 효율성 증대로 이어집니다. 소매업체는 AI를 활용하여 방대한 데이터를 분석하고 고객 행동, 시장 동향, 경쟁사 정보에 ​​대한 통찰력을 얻을 수 있습니다.
예를 들어, 아마존은 2023년 9월 25일 AI 스타트업 앤트로픽(Anthropic)에 40억 달러를 투자하여 생성형 AI 모델을 개발하는 파트너십을 체결했습니다. 이 파트너십은 특히 소비자 대상 기기 및 서비스 분야에서 AI에 대한 아마존의 집중적인 투자와 맥락을 같이합니다. 초기에 이번 협력은 아마존의 클라우드 서비스와 마이크로칩을 활용한 앤트로픽의 생성형 AI 모델 개발을 지원할 것입니다. 이러한 모델은 아마존 웹 서비스(AWS)의 아마존 베드록(Bedrock) 플랫폼을 통해 이용 가능합니다.
아시아 태평양 지역은 전 세계 소매 인공지능 시장의 3/5 이상을 차지하며 빠르게 성장하는 지역 중 하나입니다. 이 지역은 인구가 많고 지속적으로 증가하고 있으며, 도시화가 빠르게 진행됨에 따라 소비자 기반이 확대되고 소매 서비스에 대한 수요가 증가하고 있습니다. 이러한 수요를 효율적으로 충족하기 위한 AI 기반 솔루션에 대한 필요성이 커지고 있습니다. 아시아 태평양 지역은 정형 및 비정형 데이터를 포함하여 방대한 양의 데이터를 생성합니다. AI는 데이터를 기반으로 발전하며, 아시아 태평양 지역의 소매업체들은 AI를 활용하여 고객 행동, 선호도 및 시장 동향을 분석하고 데이터 기반 의사 결정을 내립니다.
동향
전자상거래 산업에서의 AI 도입
AI 알고리즘은 고객 데이터를 분석하여 개인화된 제품 추천과 쇼핑 경험을 제공함으로써 고객 만족도를 높이고 매출을 증대시킵니다. AI 기반 챗봇과 가상 비서는 연중무휴 24시간 고객 지원을 제공하여 응답 시간을 단축하고 고객 참여도를 향상시킵니다. AI는 수요 패턴을 예측하고 과잉 재고 및 재고 부족 상황을 줄이며 재고 유지 비용을 최소화함으로써 소매업체가 재고를 최적화하도록 돕습니다.
예를 들어, BigCommerce는 2023년 7월 31일 Google Cloud와의 파트너십을 통해 자사 전자상거래 플랫폼에 새로운 AI 기반 기능을 출시했습니다. 이러한 AI 도구는 대기업 판매자가 운영 효율성을 개선하고 고객 경험을 향상시키며 매출을 증대하는 데 도움이 될 것입니다. 주요 AI 기능에는 AI 기반 제품 설명, 고도로 개인화된 온라인 스토어, 비즈니스 성과에 대한 심층적인 통찰력을 얻을 수 있는 AI 기반 데이터 분석 등이 포함됩니다.
고객 경험을 개선하는 AI 기반 챗봇 사용 증가가 시장 성장을 견인합니다.
챗봇은 고객 문의에 빠르고 즉각적인 답변을 제공하여 대기 시간을 줄이고 전반적인 고객 경험을 개선할 수 있으며, 대량의 고객 문의를 동시에 처리할 수 있어 고객 상호 작용 빈도가 높은 기업에 적합합니다. 챗봇은 모든 고객에게 일관된 답변과 정보를 제공하여 모든 고객이 동일한 수준의 서비스를 받을 수 있도록 보장합니다. 고급 챗봇은 고객 데이터를 활용하여 상호 작용을 개인화하고 맞춤형 추천 및 솔루션을 제공할 수 있습니다.

예를 들어, 스키 및 스포츠 용품 브랜드인 Evo는 2023년 7월 12일, 연휴 시즌을 맞아 ChatGPT 기반의 고객 서비스 챗봇을 출시할 예정입니다. 이 AI 기반 챗봇은 간단한 고객 서비스 문의를 처리할 수 있으며, 바쁜 겨울 시즌 동안 추가 상담원 채용 필요성을 줄여줄 수 있습니다. Evo는 일반적으로 이 기간 동안 고객 서비스 직원을 두 배로 늘립니다.
AI 기반 협업으로 소매 경험이 혁신적으로 변화하고 있습니다.
협업을 통해 소매업체는 자사의 데이터와 AI 기업의 데이터 분석 전문 지식을 결합하여 고객 행동, 선호도 및 트렌드에 대한 심층적인 통찰력을 얻고, 더 나은 비즈니스 의사 결정을 내릴 수 있습니다. AI 기반 소매 협업은 고도로 개인화된 쇼핑 경험을 가능하게 합니다. 소매업체는 AI 기업과 협력하여 개별 고객 프로필과 과거 상호 작용을 기반으로 제품을 추천하는 추천 엔진을 개발할 수 있습니다.

예를 들어, 2022년 4월 6일 유니레버는 소매 마케팅 플랫폼인 퍼치(Perch)와 제휴하여 워싱턴 DC 지역의 자이언트 푸드(Giant Food) 슈퍼마켓에 인터랙티브 매장 내 제품 참여 플랫폼을 출시했습니다. 이 플랫폼은 쇼핑객이 제품과 상호 작용하면 해당 제품에 대한 비디오와 정보를 자동으로 제공하는 디지털 스크린을 특징으로 하며, QR 코드, 추가 앱 또는 화면 터치 없이 모든 기능을 사용할 수 있습니다.
데이터 프라이버시 및 부정확한 데이터
AI는 개인화 및 인사이트 도출을 위해 방대한 양의 고객 데이터에 의존합니다. 그러나 데이터 프라이버시와 소매업체가 민감한 고객 정보를 처리하고 보호하는 방식에 대한 우려가 커지고 있습니다. GDPR과 같은 데이터 보호 규정을 준수하는 것은 필수적이지만 어려운 과제입니다. 인프라, 소프트웨어 및 직원 교육을 포함한 AI 기술 구현은 소매업체, 특히 소규모 기업에게 비용 부담이 클 수 있습니다. AI 도입에 필요한 초기 투자는 장벽이 될 수 있습니다.
AI 시스템은 고품질 데이터에 의존합니다. 부정확하거나 불완전한 데이터는 잘못된 예측 및 추천으로 이어질 수 있습니다. 소매 조직 내 다양한 ​​소스의 데이터를 통합하는 것 또한 복잡할 수 있습니다. AI 시스템을 개발하고 유지 관리하려면 숙련된 데이터 과학자, 머신러닝 엔지니어 및 AI 전문가가 필요하지만, AI 전문 인력이 부족하여 소매업체가 AI 팀을 구축하고 관리하는 데 어려움을 겪고 있습니다.
세분화 분석
전 세계 소매 부문 인공지능 시장은 제공 서비스, 기능, 배포 유형, 애플리케이션, 기술 및 지역별로 세분화됩니다.
고객 서비스 제공이 시장 성장을 촉진
AI를 통해 소매업체는 방대한 고객 데이터를 분석하여 개인화된 쇼핑 경험을 제공할 수 있습니다. 이러한 개인화에는 제품 추천, 타겟 마케팅 및 맞춤형 프로모션이 포함되며, 이는 전반적인 쇼핑 경험을 향상시키고 매출 증대로 이어집니다. AI는 수요 예측을 통해 재고 수준을 최적화하고 과잉 재고 및 재고 부족 상황을 줄이며 공급망 효율성을 개선하여 비용 절감을 가져오고 고객이 원하는 시점에 제품을 제공할 수 있도록 합니다.
예를 들어, 아마존은 2022년 11월 10일, 제품 포장 전 개별 제품을 처리하여 주문 처리 프로세스를 개선하도록 설계된 지능형 로봇 시스템인 스패로우(Sparrow)를 출시했습니다. 아마존은 지난 10년 동안 운영의 다양한 측면을 자동화하기 위해 로봇 공학 및 첨단 기술에 대규모 투자를 해왔습니다. 스패로우는 아마존의 방대한 재고 내 개별 제품 관리에 있어 중요한 진전을 의미합니다.
지리적 침투
개인 맞춤형 추천으로 고객 참여도 향상 및 시장 성장 촉진
북미는 전 세계 소매 인공지능 시장을 주도하고 있으며, 이 지역의 소매업체들은 고객 쇼핑 경험 개선을 위해 AI 활용을 확대하고 있습니다. AI 기반 챗봇, 가상 쇼핑 도우미, 개인 맞춤형 추천은 고객 참여도와 만족도를 높입니다. 북미 소비자들은 개인 맞춤형 경험을 기대하며, AI는 소매업체가 방대한 고객 데이터를 분석하여 맞춤형 제품 추천, 마케팅 메시지, 가격 전략을 제공하는 데 도움을 줍니다.
예를 들어, 2023년 8월 16일 허니웰이 실시한 설문조사에 따르면, 소매업체의 약 60%가 향후 1년 내에 오프라인 매장과 온라인 모두에서 쇼핑 경험을 향상시키기 위해 인공지능, 머신러닝, 컴퓨터 비전 기술을 도입할 계획이라고 밝혔습니다. 전 세계 1,000명의 소매업체 임원을 대상으로 한 이 설문조사에서 응답자의 48%는 AI, 머신러닝, 컴퓨터 비전(CV)이 향후 3~5년 내에 소매 산업에 상당한 영향을 미칠 것이라고 생각하는 것으로 나타났습니다.

경쟁 환경
시장의 주요 글로벌 기업으로는 Amazon.com, Inc., IBM Corporation, Intel Corporation, Google LLC, Salesforce.com, Inc., SAP SE, Talkdesk, Inc., Microsoft Corporation, Nvidia Corporation 및 Oracle Corporation이 있습니다.
COVID-19 영향 분석
봉쇄 조치와 사회적 거리두기로 인해 온라인 쇼핑이 급증했습니다. 소매업체들은 온라인 쇼핑 경험을 향상시키고 웹사이트 트래픽 증가를 관리하기 위해 AI 기반 추천 엔진, 챗봇 및 가상 쇼핑 도우미를 활용했습니다. COVID-19는 전 세계 공급망을 교란시켰습니다. AI 기반 예측 분석은 소매업체들이 공급망 차질을 예측하고 관리하고, 재고 수준을 최적화하고, 고객이 필요로 하는 시기와 장소에 제품을 제공하는 데 필수적인 요소가 되었습니다.
팬데믹으로 인해 수요와 공급에 변동이 발생했습니다. AI는 실시간으로 가격 전략을 조정하는 데 사용되어 소매업체들이 과잉 재고를 방지하고 수익성을 유지하는 데 도움이 되었습니다. 소매업체들은 고객과 매장 직원 간의 물리적 접촉을 최소화하기 위해 셀프 계산대 키오스크 및 비접촉식 결제 옵션과 같은 AI 기반 기술을 도입했습니다. 예측 불가능한 팬데믹 상황으로 인해 수요 예측이 더욱 어려워졌습니다. AI 모델은 소비자 행동 및 선호도의 급격한 변화를 반영하도록 조정되었습니다.
AI 분석은 소매업체가 팬데믹 기간 동안 변화하는 고객 행동을 이해하는 데 도움이 되었고, 이 정보는 마케팅 캠페인을 맞춤화하고, 제품 구성을 최적화하고, 고객 참여를 강화하는 데 사용되었습니다. 열화상 카메라 및 얼굴 인식 시스템과 같은 AI 기반 솔루션은 매장과 유통 센터에서 건강 및 안전 프로토콜을 시행하는 데 활용되었습니다.
AI 영향
AI 기반 추천 시스템은 고객 데이터를 분석하여 개인화된 제품 추천을 제공함으로써 쇼핑 경험을 향상시키고 고객의 구매 가능성을 높입니다. AI 알고리즘은 수요를 예측하여 재고 수준을 최적화하고 과잉 재고 및 품절을 줄여 비용 절감과 고객 만족도 향상을 가져올 수 있습니다.
소매업체는 AI 기반 챗봇과 가상 비서를 사용하여 실시간 고객 지원을 제공하고, 문의에 답변하고, 제품 검색을 지원함으로써 고객 서비스 담당자의 업무 부담을 줄입니다. AI는 시장 상황, 경쟁사 가격 및 고객 행동을 분석하여 제품 가격을 실시간으로 조정함으로써 최대 수익성을 달성할 수 있습니다. 또한 AI 기반 비디오 분석 및 이미지 인식 시스템은 시장 성장을 촉진합니다. 예를 들어, 2023년 9월 13일 아마존은 생성형 인공지능(AI)을 활용하여 판매자의 상품 등록 및 관리 프로세스를 개선했다고 발표했습니다. 이러한 AI 기능은 상품 제목, 설명 및 상품 정보 생성 과정을 간소화하여 판매자가 상품 목록을 더 빠르고 쉽게 만들고 풍부하게 만들 수 있도록 지원합니다. 이러한 접근 방식은 상품 등록 프로세스를 간소화하고 수동 데이터 입력의 필요성을 줄이며 고객에게 더욱 포괄적이고 일관성 있으며 매력적인 상품 정보를 제공합니다.
러시아-우크라이나 전쟁의 영향
이 분쟁은 특히 기술 부문에서 공급망 관리를 교란했습니다. 반도체 및 하드웨어와 같은 많은 AI 관련 부품은 전 세계 여러 곳에서 제조됩니다. 공급망 차질은 AI 기술의 부족이나 비용 증가로 이어져 소매업에서의 AI 도입에 영향을 미칠 수 있습니다. 지정학적 갈등은 경제적 불확실성을 야기하여 소비자 행동에 영향을 미칠 수 있습니다. 소매업체는 불확실한 시기에 AI 관련 투자를 포함한 투자에 더욱 신중해질 수 있습니다.

러시아-우크라이나 전쟁의 영향
이 분쟁은 특히 기술 부문에서 공급망 관리를 교란했습니다. 지정학적 긴장의 파급 효과는 세계 경제에 영향을 미쳐 환율 변동, 무역 제한, 소비자 지출 패턴 변화 등을 초래할 수 있으며, 이러한 요인들은 소매업에서 AI 도입 속도와 규모에 영향을 미칠 수 있습니다. 소매업체들은 고객 데이터 분석, 개인화, 사이버 보안을 위해 AI에 의존하고 있습니다. 지정학적 긴장은 데이터 보안 및 개인정보 보호에 대한 우려를 증대시켜 소매업체들이 AI 전략과 데이터 처리 방식을 재평가하도록 유도할 수 있습니다.
제공 서비스별
• 서비스
• 솔루션
기능별
• 운영 중심
• 고객 중심
배포 유형별
• 클라우드
• 온프레미스
기술별
• 컴퓨터 비전
• 머신 러닝
• 자연어 처리
• 기타
애플리케이션별
• 예측 분석
• 매장 내 시각 모니터링 및 감시
• 고객 관계 관리
• 시장 예측
• 기타
지역별
• 북미
o 미국
o 캐나다
o 멕시코
• 유럽
o 독일
o 영국
o 프랑스
o 이탈리아
o 러시아
o 기타 유럽
• 남미
o 브라질
o 아르헨티나
o 기타 남미
• 아시아 태평양
o 중국
o 인도
o 일본
o 호주
o 기타 아시아 태평양
• 중동 및 아프리카
주요 개발 사항
• 2021년 10월, AT&T와 H2O.ai는 협력하여 데이터와 머신 러닝 엔지니어링 기술을 체계적으로 관리하고 재활용할 수 있는 AI 피처 스토어를 개발했습니다. 데이터 과학자와 개발자는 AI 모델을 만들 때 저장 및 배포에 사용되는 AI 기능과 동일한 기능을 활용합니다.
• 2023년 1월, EY는 마이크로소프트 클라우드와 클라우드 포 리테일을 활용하여 소비자의 쇼핑 경험을 향상시키는 EY 리테일 인텔리전스 솔루션을 출시했습니다. 소매 환경이 디지털 전환을 겪으면서 전통적인 소매업체는 소비자가 다양한 채널에서 최저가를 찾는 등의 문제에 직면하고 있습니다.
• 2022년 11월, AI 및 고급 분석 솔루션의 글로벌 공급업체인 프랙탈은 소비재, 제조 및 소매업을 위해 설계된 상호 연결된 AI 솔루션인 Asper.ai를 출시했습니다. Asper.ai는 수요 계획, 재고 최적화, 전략적 가격 책정 및 프로모션을 통합하는 엔드투엔드 AI 제품을 제공함으로써 이러한 부문의 AI 생태계 내 파편화를 해소하는 것을 목표로 합니다.
보고서 ​​구매 이유:

• 제품, 기능, 배포 유형, 애플리케이션, 기술 및 지역별로 세분화된 글로벌 소매 인공지능 시장을 시각화하고 주요 상업 자산 및 플레이어를 파악합니다.

• 트렌드 분석 및 공동 개발을 통해 사업 기회를 식별합니다.

• 소매 시장 전반의 모든 부문에 걸친 인공지능 관련 다양한 데이터가 담긴 엑셀 데이터시트

• 심층적인 질적 인터뷰와 연구를 바탕으로 한 종합적인 분석 결과를 담은 PDF 보고서

• 주요 기업들의 핵심 제품을 모두 포함한 제품 맵핑 자료(엑셀 파일)

글로벌 소매 시장 인공지능 보고서는 약 77개의 표, 77개의 그림, 197페이지 분량입니다.
주요 독자층 (2023년 기준)
• 제조업체/구매자
• 산업 투자자/투자은행
• 시장 조사 전문가
• 신흥 기업

보고서 요약(영어 원문)

Overview
Global Artificial Intelligence In Retail Market reached US$ 5.5 billion in 2022 and is expected to reach US$ 55.4 billion by 2030, growing with a CAGR of 34.2% during the forecast period 2023-2030.
AI enables retailers to offer personalized shopping experiences, including product recommendations, chatbots for customer service and virtual try-ons and this enhances customer satisfaction and loyalty. AI-powered systems can optimize supply chain management, inventory control and demand forecasting, which leads to cost savings and more efficient operations. Retailers can harness the power of AI to analyze huge volumes of data, gaining insights into customer behavior, market trends and competitive intelligence.
For instance, on 25 September 2023, Amazon is partnering with AI startup Anthropic in a $4 billion investment to develop generative AI models. This partnership aligns with Amazon's growing focus on AI, particularly in its consumer-facing devices and services. Initially, the collaboration will support Anthropic's work on generative AI models using Amazon's cloud services and microchips. These models will be available through Amazon Web Services' Amazon Bedrock platform.
Asia-Pacific is among the growing regions in the global artificial intelligence in retail market covering more than 3/5th of the market and the region is characterized by a large and growing population, along with increasing urbanization and this results in a higher consumer base and greater demand for retail services, driving the need for AI-powered solutions to meet these demands efficiently. The region generates vast amounts of data, both structured and unstructured. AI thrives on data and retailers in Asia-Pacific leverage AI to analyze customer behavior, preferences and market trends to make data-driven decisions.
Dynamics
Adoption of AI in E-Commerce Industry
AI algorithms analyze customer data to provide personalized product recommendations and shopping experiences and this enhances customer satisfaction and increases sales. Chatbots and virtual assistants powered by AI provide 24/7 customer support, improving response times and customer engagement. AI helps retailers optimize their inventory by predicting demand patterns, reducing overstock and understock situations and minimizing carrying costs.
For instance, on 31 July 2023, BigCommerce launched new AI-powered features on its e-commerce platform, due to its partnership with Google Cloud and these AI tools will help enterprise merchants improve operational efficiency, enhance customer experiences and boost sales. Some of the key AI features include AI-powered product descriptions, highly personalized storefronts and AI-driven data analytics to gain deeper insights into business performance.
Increasing Use of AI-Powered ChatBots that Improve Customer Experience Drives the Market
Chatbots can provide quick and instant responses to customer queries, reducing wait times and improving the overall customer experience and they can handle a large volume of customer inquiries simultaneously, making them scalable for businesses with high customer interaction rates. Chatbots provide consistent responses and information to all customers, ensuring that everyone receives the same level of service. Advanced chatbots can use customer data to personalize interactions, providing tailored recommendations and solutions.
For instance, on 12 July 2023 Ski and sporting goods brand Evo plans to launch a customer service chatbot, powered by ChatGPT, in time for the holiday season and this AI-driven chatbot can handle light-touch customer service inquiries and may reduce the brand's need to hire additional agents during the busy winter season. Evo typically doubles its customer service employees during this period.
AI-Powered Collaborations Revolutionize Retail Experiences
Collaborations allow retailers to combine their data with AI companies' expertise in data analysis and this enables retailers to gain deeper insights into customer behavior, preferences and trends, leading to more informed business decisions. AI-driven retail collaborations facilitate the creation of highly personalized shopping experiences. Retailers can partner with AI companies to develop recommendation engines that suggest products based on individual customer profiles and past interactions.
For instance, on 6 April 2022, Unilever partnered with Perch, a retail marketing platform, to launch an interactive in-store product engagement platform at Giant Food supermarkets in the Washington DC area and this platform features digital screens that automatically respond to shoppers' interactions with products by providing videos and information about those products, all without the need for QR codes, additional apps or screen touching.
Data Privacy and Inaccurate Data
AI relies on huge volumes of customer data for personalization and insights. However, there are growing concerns about data privacy and how retailers handle and protect sensitive customer information. Compliance with data protection regulations, such as GDPR, is essential but challenging. Implementing AI technologies, including infrastructure, software and staff training, can be expensive for retailers, especially smaller businesses. The initial investment required for AI adoption can be a barrier.
AI systems depend on high-quality data. Inaccurate or incomplete data can lead to erroneous predictions and recommendations. Integrating data from various sources within a retail organization can also be complex. AI requires skilled data scientists, machine learning engineers and AI specialists to develop and maintain systems and there is a shortage of professionals with AI expertise, making it challenging for retailers to build and manage AI teams.
Segment Analysis
The global artificial intelligence in retail market is segmented based on offerings, function, deployment type, application, technology and region.
Services Provided to Customers Boost the Market
AI enables retailers to analyze huge volumes of customer data to create personalized shopping experiences and this personalization includes product recommendations, targeted marketing and customized promotions, all of which enhance the overall shopping experience and drive sales. AI helps retailers optimize inventory levels by predicting demand, reducing overstock and understock situations and improving supply chain efficiency, this leads to cost savings and ensures that products are available when customers want them.
For instance, on 10 November 2022, Amazon introduced Sparrow, an intelligent robotic system designed to enhance the fulfillment process by handling individual products before they are packaged. Over the past decade, Amazon has invested heavily in robotics and advanced technology to automate various aspects of its operations. Sparrow represents a critical advancement in the handling of individual products within Amazon's vast inventory.
Geographical Penetration
Personalized Recommendation Enhance Customer Engagement Boosts the Market
North America is dominating the global artificial intelligence in retail market and retailers in the region are increasingly using AI to improve the customer shopping experience. AI-powered chatbots, virtual shopping assistants and personalized recommendations enhance customer engagement and satisfaction. North American consumers expect personalized experiences and AI helps retailers analyze vast amounts of customer data to provide tailored product recommendations, marketing messages and pricing strategies.
For instance, on 16 August 2023, a survey conducted by Honeywell revealed that around 60% of retailers plan to adopt artificial intelligence, machine learning and computer vision technologies in the next year to enhance the shopping experience, both in physical stores and online. The survey involved 1,000 retail directors globally and found that 48% of respondents believe AI, ML and Computer Vision(CV) will have a significant impact on the retail industry in the next three to five years.
Competitive Landscape
The major global players in the market include Amazon.com, Inc., IBM Corporation, Intel Corporation, Google LLC, Salesforce.com, Inc., SAP SE, Talkdesk, Inc., Microsoft Corporation, Nvidia Corporation and Oracle Corporation.
COVID-19 Impact Analysis
Lockdowns and social distancing measures in place, there was a surge in online shopping. Retailers turned to AI-powered recommendation engines, chatbots and virtual shopping assistants to enhance the online shopping experience and manage increased website traffic. COVID-19 disrupted supply chains globally. AI-powered predictive analytics became crucial for retailers to predict and manage supply chain disruptions, optimize inventory levels and ensure products were available when and where customers needed them.
The pandemic caused fluctuations in demand and supply. AI was used to adjust pricing strategies in real-time, helping retailers avoid overstocking and maintain profitability. Retailers implemented AI-driven technologies like self-checkout kiosks and touchless payment options to minimize physical contact between customers and store employees. The unpredictable nature of the pandemic made demand forecasting more challenging. AI models were adapted to account for sudden shifts in consumer behavior and preferences.
AI analytics helped retailers understand changing customer behaviors during the pandemic and this information was used to tailor marketing campaigns, optimize product offerings and enhance customer engagement. AI-powered solutions, such as thermal imaging cameras and facial recognition systems, were deployed to enforce health and safety protocols in stores and distribution centers.
AI Impact
AI-powered recommendation systems analyze customer data to provide personalized product recommendations and this enhances the shopping experience and increases the likelihood of customers making purchases. AI algorithms can optimize inventory levels by predicting demand, reducing overstock and stockouts and this results in cost savings and improved customer satisfaction.
Retailers use AI-driven chatbots and virtual assistants to provide real-time customer support, answer queries and assist with product searches and this reduces the workload on human customer service agents. AI can analyze market conditions, competitor pricing and customer behavior to adjust product prices in real-time for maximum profitability. Also, AI-powered video analytics and image recognition systems boost the market.
For instance, on 13 September 2023, According to Amazon, amazon leveraged generative artificial intelligence to enhance the product listing creation and management process for sellers and these AI capabilities simplified the process of creating product titles, descriptions and listing details, making it faster and easier for sellers to create and enrich their product listings and this approach streamlines the listing creation process, reduces the need for manual data entry and ensures that customers receive more comprehensive, consistent and engaging product information.
Russia- Ukraine War Impact
The conflict has disrupted supply chain management, especially in the technology sector. Many AI-related components, such as semiconductors and hardware, are manufactured in various parts of the world. Disruptions in the supply chain can lead to shortages or increased costs for AI technology, impacting its adoption in retail. Geopolitical conflicts can contribute to economic uncertainty, which affects consumer behavior. Retailers may become more cautious in their investments, including AI initiatives, during uncertain times.
The ripple effects of geopolitical tensions can impact the global economy, leading to fluctuations in currency exchange rates, trade restrictions and changes in consumer spending patterns and these factors can influence the pace and scale of AI adoption in retail. Retailers rely on AI for customer data analysis, personalization and cybersecurity. Geopolitical tensions can lead to increased concerns about data security and privacy, prompting retailers to reassess their AI strategies and data handling practices.
By Offerings
• Services
• Solutions
By Function
• Operation-Focused
• Customer-Facing
By Deployment Type
• Cloud
• On-Premise
By Technology
• Computer Vision
• Machine Learning
• Natural Language Processing
• Others
By Application
• Predictive Analytics
• In-Store Visual Monitoring & Surveillance
• Customer Relationship Management
• Market Forecasting
• Others
By Region
• North America
o U.S.
o Canada
o Mexico
• Europe
o Germany
o UK
o France
o Italy
o Russia
o Rest of Europe
• South America
o Brazil
o Argentina
o Rest of South America
• Asia-Pacific
o China
o India
o Japan
o Australia
o Rest of Asia-Pacific
• Middle East and Africa
Key Developments
• In October 2021, AT&T and H2O.ai collaborated together that resulted in the development of an AI feature store that allows the organization and recycle data and machine learning engineering skills. Data scientists and developers employ the same features that AI features used for storage and distribution when creating AI models.
• In January 2023, EY introduced the EY Retail Intelligence solution which leveraging the Microsoft Cloud and Cloud for Retail, that leads to enhance consumers' shopping experiences. As the retail landscape undergoes digital transformation, traditional retailers face challenges such as consumers searching for the best prices across various channels.
• In November 2022, Fractal, a global provider of AI and advanced analytics solutions, launched Asper.ai, an interconnected AI solution designed for consumer goods, manufacturing and retail. Asper.ai aims to address the fragmentation within the AI ecosystem in these sectors by offering an end-to-end AI product that unifies demand planning, inventory optimization, strategic pricing and promotion
Why Purchase the Report?
• To visualize the global artificial intelligence in retail market segmentation based on offerings, function, deployment type, application, technology and region, as well as understand key commercial assets and players.
• Identify commercial opportunities by analyzing trends and co-development.
• Excel data sheet with numerous data points of artificial intelligence in retail market-level with all segments.
• PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
• Product mapping available as excel consisting of key products of all the major players.
The global artificial intelligence in retail market report would provide approximately 77 tables, 77 figures and 197 Pages.
Target Audience 2023
• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies

상세 목차

1. Methodology and Scope
1.1. Research Methodology
1.2. Research Objective and Scope of the Report
2. Definition and Overview
3. Executive Summary
3.1. Snippet by Offerings
3.2. Snippet by Function
3.3. Snippet By Deployment Type
3.4. Snippet by Application
3.5. Snippet by Technology
3.6. Snippet by Region
4. Dynamics
4.1. Impacting Factors
4.1.1. Drivers
4.1.1.1. Adoption of AI in E-Commerce Industry
4.1.1.2. Increasing Use of AI-Powered ChatBots that Improve Customer Experience Drives the Market
4.1.1.3. AI-Powered Collaborations Revolutionize Retail Experiences
4.1.2. Restraints
4.1.2.1. Data Privacy and Inaccurate Data
4.1.3. Impact Analysis
5. Industry Analysis
5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Russia-Ukraine War Impact Analysis
5.6. DMI Opinion
6. COVID-19 Analysis
6.1. Analysis of COVID-19
6.1.1. Scenario Before COVID
6.1.2. Scenario During COVID
6.1.3. Scenario Post COVID
6.2. Pricing Dynamics Amid COVID-19
6.3. Demand-Supply Spectrum
6.4. Government Initiatives Related to the Market During Pandemic
6.5. Manufacturers Strategic Initiatives
6.6. Conclusion
7. By Offerings
7.1. Introduction
7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offerings
7.1.2. Market Attractiveness Index, By Offerings
7.2. Services *
7.2.1. Introduction
7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Solutions
8. By Function
8.1. Introduction
8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
8.1.2. Market Attractiveness Index, By Function
8.2. Operation-Focused*
8.2.1. Introduction
8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. Customer-Facing
9. By Deployment Type
9.1. Introduction
9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
9.1.2. Market Attractiveness Index, By Deployment Type
9.2. Cloud*
9.2.1. Introduction
9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
9.3. On-Premise
10. By Application
10.1. Introduction
10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
10.1.2. Market Attractiveness Index, By Application
10.2. Predictive Analytics*
10.2.1. Introduction
10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
10.3. In-Store Visual Monitoring & Surveillance
10.4. Customer Relationship Management
10.5. Market Forecasting
10.6. Others
11. By Technology
11.1. Introduction
11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
11.1.2. Market Attractiveness Index, By Technology
11.2. Computer Vision*
11.2.1. Introduction
11.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
11.3. Machine Learning
11.4. Natural Language Processing
11.5. Others
12. By Region
12.1. Introduction
12.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
12.1.2. Market Attractiveness Index, By Region
12.2. North America
12.2.1. Introduction
12.2.2. Key Region-Specific Dynamics
12.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offerings
12.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
12.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
12.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
12.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
12.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
12.2.8.1. U.S.
12.2.8.2. Canada
12.2.8.3. Mexico
12.3. Europe
12.3.1. Introduction
12.3.2. Key Region-Specific Dynamics
12.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offerings
12.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
12.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
12.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
12.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
12.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
12.3.8.1. Germany
12.3.8.2. UK
12.3.8.3. France
12.3.8.4. Italy
12.3.8.5. Russia
12.3.8.6. Rest of Europe
12.4. South America
12.4.1. Introduction
12.4.2. Key Region-Specific Dynamics
12.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offerings
12.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
12.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
12.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
12.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
12.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
12.4.8.1. Brazil
12.4.8.2. Argentina
12.4.8.3. Rest of South America
12.5. Asia-Pacific
12.5.1. Introduction
12.5.2. Key Region-Specific Dynamics
12.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offerings
12.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
12.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
12.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
12.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
12.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
12.5.8.1. China
12.5.8.2. India
12.5.8.3. Japan
12.5.8.4. Australia
12.5.8.5. Rest of Asia-Pacific
12.6. Middle East and Africa
12.6.1. Introduction
12.6.2. Key Region-Specific Dynamics
12.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offerings
12.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
12.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
12.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
12.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
13. Competitive Landscape
13.1. Competitive Scenario
13.2. Market Positioning/Share Analysis
13.3. Mergers and Acquisitions Analysis
14. Company Profiles
14.1. Amazon.com, Inc.*
14.1.1. Company Overview
14.1.2. Product Portfolio and Description
14.1.3. Financial Overview
14.1.4. Key Developments
14.2. IBM Corporation
14.3. Intel Corporation
14.4. Google LLC
14.5. Salesforce.com, Inc.
14.6. SAP SE
14.7. Talkdesk, Inc.
14.8. Microsoft Corporation
14.9. Nvidia Corporation
14.10. Oracle Corporation
LIST NOT EXHAUSTIVE
15. Appendix
15.1. About Us and Services
15.2. Contact Us

언급된 주요 기업들

Amazon.com, Inc., 4. Key Developments, IBM Corporation, Intel Corporation, Google LLC, Salesforce.com, Inc., SAP SE, Talkdesk, Inc., Microsoft Corporation, Nvidia Corporation, Oracle Corporation

표 목록 (Tables)

List of Tables

Table 1 Global Artificial Intelligence In Retail Market Value, By Offerings, 2022, 2026 & 2030 (US$ Billion)

Table 2 Global Artificial Intelligence In Retail Market Value, By Function, 2022, 2026 & 2030 (US$ Billion)

Table 3 Global Artificial Intelligence In Retail Market Value, By Deployment Type, 2022, 2026 & 2030 (US$ Billion)

Table 4 Global Artificial Intelligence In Retail Market Value, By Application, 2022, 2026 & 2030 (US$ Billion)

Table 5 Global Artificial Intelligence In Retail Market Value, By Technology, 2022, 2026 & 2030 (US$ Billion)

Table 6 Global Artificial Intelligence In Retail Market Value, By Region, 2022, 2026 & 2030 (US$ Billion)

Table 7 Global Artificial Intelligence In Retail Market Value, By Offerings, 2022, 2026 & 2030 (US$ Billion)

Table 8 Global Artificial Intelligence In Retail Market Value, By Offerings, 2021-2030 (US$ Billion)

Table 9 Global Artificial Intelligence In Retail Market Value, By Function, 2022, 2026 & 2030 (US$ Billion)

Table 10 Global Artificial Intelligence In Retail Market Value, By Function, 2021-2030 (US$ Billion)

Table 11 Global Artificial Intelligence In Retail Market Value, By Deployment Type, 2022, 2026 & 2030 (US$ Billion)

Table 12 Global Artificial Intelligence In Retail Market Value, By Deployment Type, 2021-2030 (US$ Billion)

Table 13 Global Artificial Intelligence In Retail Market Value, By Application, 2022, 2026 & 2030 (US$ Billion)

Table 14 Global Artificial Intelligence In Retail Market Value, By Application, 2021-2030 (US$ Billion)

Table 15 Global Artificial Intelligence In Retail Market Value, By Technology, 2022, 2026 & 2030 (US$ Billion)

Table 16 Global Artificial Intelligence In Retail Market Value, By Technology, 2021-2030 (US$ Billion)

Table 17 Global Artificial Intelligence In Retail Market Value, By Region, 2022, 2026 & 2030 (US$ Billion)

Table 18 Global Artificial Intelligence In Retail Market Value, By Region, 2021-2030 (US$ Billion)

Table 19 North America Artificial Intelligence In Retail Market Value, By Offerings, 2021-2030 (US$ Billion)

Table 20 North America Artificial Intelligence In Retail Market Value, By Function, 2021-2030 (US$ Billion)

Table 21 North America Artificial Intelligence In Retail Market Value, By Deployment Type, 2021-2030 (US$ Billion)

Table 22 North America Artificial Intelligence In Retail Market Value, By Application, 2021-2030 (US$ Billion)

Table 23 North America Artificial Intelligence In Retail Market Value, By Technology, 2021-2030 (US$ Billion)

Table 24 North America Artificial Intelligence In Retail Market Value, By Country, 2021-2030 (US$ Billion)

Table 25 South America Artificial Intelligence In Retail Market Value, By Offerings, 2021-2030 (US$ Billion)

Table 26 South America Artificial Intelligence In Retail Market Value, By Function, 2021-2030 (US$ Billion)

Table 27 South America Artificial Intelligence In Retail Market Value, By Deployment Type, 2021-2030 (US$ Billion)

Table 28 South America Artificial Intelligence In Retail Market Value, By Application, 2021-2030 (US$ Billion)

Table 29 South America Artificial Intelligence In Retail Market Value, By Technology, 2021-2030 (US$ Billion)

Table 30 South America Artificial Intelligence In Retail Market Value, By Country, 2021-2030 (US$ Billion)

Table 31 Europe Artificial Intelligence In Retail Market Value, By Offerings, 2021-2030 (US$ Billion)

Table 32 Europe Artificial Intelligence In Retail Market Value, By Function, 2021-2030 (US$ Billion)

Table 33 Europe Artificial Intelligence In Retail Market Value, By Deployment Type, 2021-2030 (US$ Billion)

Table 34 Europe Artificial Intelligence In Retail Market Value, By Application, 2021-2030 (US$ Billion)

Table 35 Europe Artificial Intelligence In Retail Market Value, By Technology, 2021-2030 (US$ Billion)

Table 36 Europe Artificial Intelligence In Retail Market Value, By Country, 2021-2030 (US$ Billion)

Table 37 Asia-Pacific Artificial Intelligence In Retail Market Value, By Offerings, 2021-2030 (US$ Billion)

Table 38 Asia-Pacific Artificial Intelligence In Retail Market Value, By Function, 2021-2030 (US$ Billion)

Table 39 Asia-Pacific Artificial Intelligence In Retail Market Value, By Deployment Type, 2021-2030 (US$ Billion)

Table 40 Asia-Pacific Artificial Intelligence In Retail Market Value, By Application, 2021-2030 (US$ Billion)

Table 41 Asia-Pacific Artificial Intelligence In Retail Market Value, By Technology, 2021-2030 (US$ Billion)

Table 42 Asia-Pacific Artificial Intelligence In Retail Market Value, By Country, 2021-2030 (US$ Billion)

Table 43 Middle East & Africa Artificial Intelligence In Retail Market Value, By Offerings, 2021-2030 (US$ Billion)

Table 44 Middle East & Africa Artificial Intelligence In Retail Market Value, By Function, 2021-2030 (US$ Billion)

Table 45 Middle East & Africa Artificial Intelligence In Retail Market Value, By Deployment Type, 2021-2030 (US$ Billion)

Table 46 Middle East & Africa Artificial Intelligence In Retail Market Value, By Application, 2021-2030 (US$ Billion)

Table 47 Middle East & Africa Artificial Intelligence In Retail Market Value, By Technology, 2021-2030 (US$ Billion)

Table 48 Amazon.com, Inc.: Overview

Table 49 Amazon.com, Inc.: Product Portfolio

Table 50 Amazon.com, Inc.: Key Developments

Table 51 IBM Corporation: Overview

Table 52 IBM Corporation: Product Portfolio

Table 53 IBM Corporation: Key Developments

Table 54 Intel Corporation: Overview

Table 55 Intel Corporation: Product Portfolio

Table 56 Intel Corporation: Key Developments

Table 57 Google LLC: Overview

Table 58 Google LLC: Product Portfolio

Table 59 Google LLC: Key Developments

Table 60 Salesforce.com, Inc.: Overview

Table 61 Salesforce.com, Inc.: Product Portfolio

Table 62 Salesforce.com, Inc.: Key Developments

Table 63 SAP SE: Overview

Table 64 SAP SE: Product Portfolio

Table 65 SAP SE: Key Developments

Table 66 Talkdesk, Inc.: Overview

Table 67 Talkdesk, Inc.: Product Portfolio

Table 68 Talkdesk, Inc.: Key Developments

Table 69 Microsoft Corporation: Overview

Table 70 Microsoft Corporation: Product Portfolio

Table 71 Microsoft Corporation: Key Developments

Table 72 Nvidia Corporation: Overview

Table 73 Nvidia Corporation: Product Portfolio

Table 74 Nvidia Corporation: Key Developments

Table 75 Oracle Corporation: Overview

Table 76 Oracle Corporation: Product Portfolio

Table 77 Oracle Corporation: Key Developments

그림 목록 (Figures)

List of Figures

Figure 1 Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 2 Global Artificial Intelligence In Retail Market Share, By Offerings, 2022 & 2030 (%)

Figure 3 Global Artificial Intelligence In Retail Market Share, By Function, 2022 & 2030 (%)

Figure 4 Global Artificial Intelligence In Retail Market Share, By Deployment Type, 2022 & 2030 (%)

Figure 5 Global Artificial Intelligence In Retail Market Share, By Application, 2022 & 2030 (%)

Figure 6 Global Artificial Intelligence In Retail Market Share, By Technology, 2022 & 2030 (%)

Figure 7 Global Artificial Intelligence In Retail Market Share, By Region, 2022 & 2030 (%)

Figure 8 Global Artificial Intelligence In Retail Market Y-o-Y Growth, By Offerings, 2022-2030 (%)

Figure 9 Services Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 10 Solutions Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 11 Global Artificial Intelligence In Retail Market Y-o-Y Growth, By Function, 2022-2030 (%)

Figure 12 Operation-Focused Function in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 13 Customer-Facing Function in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 14 Global Artificial Intelligence In Retail Market Y-o-Y Growth, By Deployment Type, 2022-2030 (%)

Figure 15 Cloud Deployment Type in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 16 On-Premise Deployment Type in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 17 Global Artificial Intelligence In Retail Market Y-o-Y Growth, By Application, 2022-2030 (%)

Figure 18 Predictive Analytics Application in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 19 In-Store Visual Monitoring & Surveillance Application in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 20 Customer Relationship Management Application in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 21 Market Forecasting Application in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 22 Others Application in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 23 Global Artificial Intelligence In Retail Market Y-o-Y Growth, By Technology, 2022-2030 (%)

Figure 24 Computer Vision Technology in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 25 Machine Learning Technology in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 26 Natural Language Processing Technology in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 27 Others Technology in Global Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 28 Global Artificial Intelligence In Retail Market Y-o-Y Growth, By Region, 2022-2030 (%)

Figure 29 North America Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 30 Asia-Pacific Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 31 Europe Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 32 South America Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 33 Middle East and Africa Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 34 North America Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 35 North America Artificial Intelligence In Retail Market Share, By Offerings, 2022 & 2030 (%)

Figure 36 North America Artificial Intelligence In Retail Market Share, By Function, 2022 & 2030 (%)

Figure 37 North America Artificial Intelligence In Retail Market Share, By Deployment Type, 2022 & 2030 (%)

Figure 38 North America Artificial Intelligence In Retail Market Share, By Application, 2022 & 2030 (%)

Figure 39 North America Artificial Intelligence In Retail Market Share, By Technology, 2022 & 2030 (%)

Figure 40 North America Artificial Intelligence In Retail Market Share, By Country, 2022 & 2030 (%)

Figure 41 South America Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 42 South America Artificial Intelligence In Retail Market Share, By Offerings, 2022 & 2030 (%)

Figure 43 South America Artificial Intelligence In Retail Market Share, By Function, 2022 & 2030 (%)

Figure 44 South America Artificial Intelligence In Retail Market Share, By Deployment Type, 2022 & 2030 (%)

Figure 45 South America Artificial Intelligence In Retail Market Share, By Application, 2022 & 2030 (%)

Figure 46 South America Artificial Intelligence In Retail Market Share, By Technology, 2022 & 2030 (%)

Figure 47 South America Artificial Intelligence In Retail Market Share, By Country, 2022 & 2030 (%)

Figure 48 Europe Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 49 Europe Artificial Intelligence In Retail Market Share, By Offerings, 2022 & 2030 (%)

Figure 50 Europe Artificial Intelligence In Retail Market Share, By Function, 2022 & 2030 (%)

Figure 51 Europe Artificial Intelligence In Retail Market Share, By Deployment Type, 2022 & 2030 (%)

Figure 52 Europe Artificial Intelligence In Retail Market Share, By Application, 2022 & 2030 (%)

Figure 53 Europe Artificial Intelligence In Retail Market Share, By Technology, 2022 & 2030 (%)

Figure 54 Europe Artificial Intelligence In Retail Market Share, By Country, 2022 & 2030 (%)

Figure 55 Asia-Pacific Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 56 Asia-Pacific Artificial Intelligence In Retail Market Share, By Offerings, 2022 & 2030 (%)

Figure 57 Asia-Pacific Artificial Intelligence In Retail Market Share, By Function, 2022 & 2030 (%)

Figure 58 Asia-Pacific Artificial Intelligence In Retail Market Share, By Deployment Type, 2022 & 2030 (%)

Figure 59 Asia-Pacific Artificial Intelligence In Retail Market Share, By Application, 2022 & 2030 (%)

Figure 60 Asia-Pacific Artificial Intelligence In Retail Market Share, By Technology, 2022 & 2030 (%)

Figure 61 Asia-Pacific Artificial Intelligence In Retail Market Share, By Country, 2022 & 2030 (%)

Figure 62 Middle East & Africa Artificial Intelligence In Retail Market Value, 2021-2030 (US$ Billion)

Figure 63 Middle East & Africa Artificial Intelligence In Retail Market Share, By Offerings, 2022 & 2030 (%)

Figure 64 Middle East & Africa Artificial Intelligence In Retail Market Share, By Function, 2022 & 2030 (%)

Figure 65 Middle East & Africa Artificial Intelligence In Retail Market Share, By Deployment Type, 2022 & 2030 (%)

Figure 66 Middle East & Africa Artificial Intelligence In Retail Market Share, By Application, 2022 & 2030 (%)

Figure 67 Middle East & Africa Artificial Intelligence In Retail Market Share, By Technology, 2022 & 2030 (%)

Figure 68 Amazon.com, Inc.: Financials

Figure 69 IBM Corporation: Financials

Figure 70 Intel Corporation: Financials

Figure 71 Google LLC: Financials

Figure 72 Salesforce.com, Inc.: Financials

Figure 73 SAP SE: Financials

Figure 74 Talkdesk, Inc.: Financials

Figure 75 Microsoft Corporation: Financials

Figure 76 Nvidia Corporation: Financials

Figure 77 Oracle Corporation: Financials