Artificial intelligence to help enhance payments was ***** as likely to be an option for younger respondents than it was for their older counterparts in 2024. This is according to a survey held in 14 different countries across North America, Europe, and Latin America. The source observed in 2023 already that most respondents - regardless of age - were not yet comfortable with the idea of AI in digital payments. This revealed itself, especially, in the reply from ** percent of the respondents that they would perhaps use artificial intelligence in two years' time when it had become more established. In 2024, the source did not ask how many people actively used AI during their payments journey. Examples of AI in day-to-day digital payments for consumers The source lists three specific use cases of artificial intelligence in consumer-driven payments: Smart wallets, AI-powered checkouts, and chatbots. One example includes Amazon's Just Walk Out (JWO) in its Amazon Go shops in the United States. The technology uses machine learning to identify what customers picked off the shelves and then bill them automatically. This solution aims at the innovation consumers hope to see most in shopping, especially online: A seamless payments experience. Payment providers had a similar impression, in that they observed a demand among their clients for real-time payments. More so than for lower payment processing costs or cross-border payment solutions. The source adds certain payment solutions might already be using AI in the background, but that consumers are simply not aware of them. AI pros and cons for financial services The finance industry is expected to make heavy use of artificial intelligence's capabilities for years to come. AI's ability to monitor trends and improve data analytics, especially, is popular among financial service providers. Another popular use is that AI can help process large quantities of data. This is especially useful for larger investment-style banks. There are concerns, though. Data issues and growing concerns about keeping talent on board to help out with issues or data sciences ranked as the top AI concerns in 2024.

During a survey carried out in January 2023 in the United States, ** percent of responding consumers expressed a lack of understanding of how artificial intelligence (AI) and machine learning (ML) technologies worked. However, ** percent of respondents said that they believed that AI and ML had potential to impact customer experience (CX) and ** percent stated they would interact with AI more frequently if it made their CX with a brand more seamless, consistent, and convenient.

During a March 2024 survey among adult consumers in the United States, approximately ** percent said they supported brands using artificial intelligence (AI) to create ads or content. The same share of respondents supported AI-powered product and service design. Consumer attitudes toward brands using AI According to the same study, over ** percent of adults preferred companies that utilized AI to design their products and services over those that did not. A similar share of the interviewees favored brands that used AI in their customer experience (CX) endeavors. However, only slightly more than ********* expressed the willingness to pay more for items designed with the help of AI. Support to AI-powered ads by gender and generation The March 2024 survey also revealed that U.S. men favored AI-supported brands more than women. About ********** of male respondents supported companies using AI to design products and services, while little more than **** of female interviewees approved of it. Millennials were more supportive of AI-reliant ads than any other adult generational group in the U.S.: ** percent of the responding members of Generation Y expressed approval of the practice, while the share among Gen Zers stood at ** percent.

According to Cognitive Market Research, the global Artificial Intelligence in Marketing Market size is USD 12.7 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 23.8% from 2024 to 2031.

Market Dynamics of Artificial Intelligence in Marketing Market

Key Drivers for Artificial Intelligence in Marketing Market



  Increasing demand for predictive analysis - AI can predict consumer behavior, such as purchasing habits and churn rates. This enables marketers to anticipate customer requirements and preferences, allowing them to solve concerns and provide relevant solutions ahead of time. AI allows marketers to provide highly tailored information and offers to individual customers based on their interests, purchasing history, and behavior. Personalization improves consumer engagement, contentment, and loyalty, resulting in more conversions and revenue. As a result, the market is growing due to increased demand for personalization and predictive analytics.


  Rapid adoption of artificial intelligence in the healthcare Application




Key Restraints for Artificial Intelligence in Marketing Market



  Cost and data privacy issues


  Maintaining data privacy and security concerns

Introduction of the Artificial Intelligence in Marketing Market

Artificial intelligence (AI) in marketing is the incorporation of advanced algorithms and machine learning techniques into various marketing processes and tactics. This cutting-edge technology lets businesses to use data-driven insights, automate repetitive operations, and provide personalized experiences to their target audience, resulting in higher customer engagement, efficiency, and ROI. AI's applicability in marketing is diverse, ranging from monitoring consumer behavior and predicting trends to optimizing ad campaigns and improving customer service. The growing usage of artificial intelligence and machine learning to provide social networking platform acceptance, tailored consumer experiences, and the growth of e-commerce are the main drivers driving the market's development.

As of March 2024, around ** percent of adults surveyed in the United States said they preferred brands that used artificial intelligence (AI) to design products and services over ones that did not. Approximately ** percent reported favoring brands that used AI in their customer experience, while around ** percent said they were willing to pay more for products and services designed with AI.

According to Cognitive Market Research, the global Customer Intelligence Platform Market was USD 2021.1 million in 2024 and expand at a compound annual growth rate (CAGR) of 24.9 % from 2024 to 2031. Market Dynamics of Customer Intelligence Platform Market

Key Drivers for Customer Intelligence Platform Market



  Increased adoption of advanced analytics and artificial intelligence - The growing usage of sophisticated analytics and artificial intelligence (AI) is one of the primary drivers of the customer intelligence platform market. The term "advanced analytics" refers to the use of sophisticated methods and equipment to analyze large amounts of data and provide relevant insights. Artificial intelligence (AI) is the development of intelligent computers capable of doing activities that have historically needed human intelligence, such as natural language processing, machine learning, and predictive analytics. Customer intelligence systems collect and analyze data from a variety of sources, including social media, customer interactions, and transaction history, employing novel analytics and artificial intelligence technology. Using these technologies allows businesses to have a deeper understanding of their customers' preferences and behavior patterns. This allows firms to create customer-relevant, data-driven marketing strategies and decisions.


  Need to get a comprehensive view of consumer data.




Key Restraints for Customer Intelligence Platform Market



  Lack of Skilled Professionals Limits Market Growth


  Lack of data quality and challenges in data integration hamper the market growth



Required to abide by data privacy legislation and defend against customer information hamper the market

Customer intelligence platforms consolidate first-party customer data from diverse channels and sources into a single customer view. Under the General Data Protection Regulation (GDPR) and other data privacy legislation, marketers are required to get marketing consent from consumers. Customer data is very susceptible to breaches and cyberattacks. Therefore, it becomes essential for a customer intelligence platform to comprehend the principal challenges relating to data management, including customer information protection as sensitive data and marketing consent of consumers. An ideal customer intelligence platform must be supported by a data model based on consent; it facilitates storing information of customer journey and consent to marketing and delivers customers transparency as well as control over the way their data gets utilized. If the customer has opted out of permission for use of their data, then the customer intelligence platform should add them to a direct mail suppression list and make sure that it will not get any unwanted marketing material through any other medium. In those nations with weak or no regulations regarding customer data privacy, customer intelligence platform solutions are applied on existing data privacy situations or even in expectation of the regulations that may emerge within the near future. It might cause problems when such new legislation is enacted surrounding customer data privacy. Therefore, the necessity of privacy of customer information and adherence to data privacy regulations is central to the acceptance of customer intelligence platforms.

Opportunities for Customer Intelligence Platform

Rising the use of Customer Intelligence Platforms to Track Market Changes

The ever-changing nature of consumer behavior and market dynamics has resulted in a rapid increase in the use of customer intelligence platforms. Companies are now more aware of the importance of remaining agile and responsive to ensure a competitive advantage. Customer intelligence platforms allow organizations to aggregate real-time information from various touchpoints like websites, social media, mobile applications, and customer service interactions—into a single view, enabling them to gain deeper insights into evolving trends and changing customer preferences. Through the use of advanced analytics and AI-based tools, such platforms enable businesses to identify shifts in purchasing behavior, sentiment in the market, and campaign effectiveness well before they happen. This enables businesses to adjust strategies, tailor customer experiences, and make better-informed decisions with data-driven accuracy. For insta...

Snapshot img { margin: 10px !important; } Artificial Intelligence (AI) In Retail Sector Market Size 2025-2029

The artificial intelligence (AI) in retail sector market size is forecast to increase by USD 51.9 billion, at a CAGR of 40.3% between 2024 and 2029.

The global artificial intelligence (AI) market in retail sector is shaped by a significant rise in investments and dedicated research into AI startups. This funding empowers the development of advanced systems for ai and machine learning in business, particularly enhancing ai for sales. The increased application of AI in e-commerce is a primary trend, where tools like ai agents in ecommerce are transforming the online shopping experience.Improving customer recommendations based on past purchases.Providing more information to the sales team and automating customer service.These advancements allow for deeper personalization and operational efficiency, leveraging predictive analytics and machine learning algorithms to refine everything from inventory control to customer interactions, which is central to applied ai in retail and e-commerce.While growth is significant, privacy issues associated with AI deployment present a notable challenge. The use of advanced data mining techniques and customer profiling, integral to generative ai in retail, raises concerns about data exploitation and individual privacy. These systems gather extensive data on buying habits and online behavior, which, while useful for creating personalized experiences, must be managed with transparency and strong governance. This concern impacts the deployment of technologies such as voice and facial recognition, requiring a careful balance between leveraging powerful predictive ai in retail and maintaining consumer trust, a critical factor for the sustainable integration of AI across the retail landscape.

What will be the Size of the Artificial Intelligence (AI) In Retail Sector Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019 - 2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe ongoing integration of ai-powered intelligent automation is fundamentally altering retail operations, with robotic process automation (RPA) becoming a key component for enhancing supply chain optimization and enabling more precise automated inventory management. The application of deep-learning neural networks and predictive analytics allows for more accurate demand forecasting, moving beyond static models to embrace real-time problem-solving. This evolution in ai and machine learning in business is critical for improving efficiencies in supply chain planning and logistics, forming the backbone of modern, agile retail frameworks. The continuous refinement of these systems underscores a market-wide shift toward data-driven operational excellence.On the customer-facing front, conversational commerce systems and ai-driven customer services are redefining engagement, central to the growth of generative ai in customer services. Core technologies such as natural language processing (NLP) and computer vision are the engines behind advanced visual search engines and increasingly sophisticated chatbots. This strategic push toward personalization at scale is a defining characteristic of applied ai in retail and e-commerce. However, its implementation must be carefully balanced with ethical considerations surrounding data exploitation and customer profiling to ensure long-term consumer trust and sustainable integration into the digital shopping journey.

How is this Artificial Intelligence (AI) In Retail Sector Industry segmented?

The artificial intelligence (AI) in retail sector industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2025-2029, as well as historical data from 2019 - 2023 for the following segments. ApplicationSales and marketingIn-storePPPLogistics managementTechnologyMachine learningComputer visionNatural language processingDeploymentCloud-basedOn-premisesGeographyNorth AmericaUSCanadaMexicoAPACChinaJapanIndiaSouth KoreaAustraliaIndonesiaEuropeUKGermanyFranceItalySpainThe NetherlandsMiddle East and AfricaUAESouth AfricaEgyptSouth AmericaBrazilArgentinaChileRest of World (ROW)

By Application Insights

The sales and marketing segment is estimated to witness significant growth during the forecast period.The sales and marketing segment leverages artificial intelligence to optimize customer interactions and drive revenue. AI-based chatbots and virtual assistants are increasingly integrated into customer relationship management strategies to provide personalized engagement and predict consumer behavior. Through data analytics, companies can boost business relationships and tailor marketing efforts. This segment accounts for over 50% of the market, reflecting its critical role i

Artificial Intelligence In Marketing Market size was valued at USD 21.27 Billion in 2023 and is projected to reach USD 138.5 Billion by 2031, growing at a CAGR of 29.11% during the forecast period 2024-2031.

Global Artificial Intelligence In Marketing Market Drivers

The market drivers for the Artificial Intelligence In Marketing Market can be influenced by various factors. These may include:

Growing Use of AI and Machine Learning: As these technologies progress and become more widely available, marketers are using them more and more to improve their marketing strategies, target customers more precisely, customise content, and run more effective campaigns.

Demand for Personalised Customer Experiences: In today's world, customers anticipate receiving personalised treatment at every touchpoint. Marketing professionals can now send more individualised and pertinent messages to customers by using artificial intelligence (AI) to analyse massive volumes of data and understand consumer behaviour, preferences, and intent. Predictive analytics is becoming more and more important since it allows marketers to forecast consumer behaviour, spot patterns, and foresee future needs. It is powered by artificial intelligence. This skill is essential for creating winning marketing plans and optimising return on investment.

Rise of Chatbots and Virtual Assistants: With their ability to offer immediate customer service, tailored recommendations, and support throughout the customer journey, chatbots and virtual assistants driven by artificial intelligence are quickly becoming essential components of marketing plans.

Developments in Natural Language Processing (NLP): NLP tools let marketers decipher and evaluate unstructured data from sources including support tickets, social media, and consumer reviews. This feature is extremely helpful for sentiment analysis, social listening, and deriving conclusions from textual information.

Emphasis on Marketing Automation: AI-powered marketing automation systems automate time-consuming processes like lead scoring, email marketing, and campaign administration, freeing up marketers to concentrate on high-value endeavours like ideation and strategy formation.

Need for Improved Customer Engagement: AI gives marketers the ability to interact with clients in real-time over a variety of channels, providing tailored offers, recommendations, and content according to each person's tastes and actions.

E-commerce is growing at an exponential rate, which has increased demand for AI-driven marketing solutions that may assist companies in attracting, converting, and keeping customers in the fiercely competitive online market. The emergence of AI-powered analytics tools: With the help of these sophisticated tools, marketers can now obtain a deeper understanding of customer behaviour, market trends, and campaign performance. This allows them to optimise their marketing strategies and make data-driven decisions.

Greater Emphasis on ROI and Cost Efficiency: Marketers are under pressure to show the return on investment (ROI) of their campaigns and to minimise expenses in a more cutthroat commercial climate. AI assists marketers in more efficiently allocating resources, focusing on the proper target market, and boosting campaign effectiveness.

Snapshot img

Artificial Intelligence in Social Media Market Size 2024-2028

The artificial intelligence (AI) in social media market size is forecast to increase by USD 5.57 billion at a CAGR of 27.82% between 2023 and 2028.

Artificial Intelligence is revolutionizing the social media market by enabling advanced data analysis and personalized user experiences. The growing demand for data integration and visual analytics is a significant market growth factor, as businesses seek to gain insights from vast amounts of social media data.
Additionally, the increasing use of social media for advertising has created a need for AI-powered solutions to effectively target and engage consumers. However, the lack of a skilled workforce for the development of AI algorithms poses a challenge for market growth. Despite this, the potential benefits of AI in social media, including improved customer engagement and enhanced marketing capabilities, are driving innovation and investment in this area.

Artificial Intelligence in Social Media Market Analysis

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How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD Billion' for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments.

Application

  Predictive risk management
  Consumer experience management
  Sales and marketing


End-user

  Large Enterprise
  SMEs


Geography

  North America

    US


  Europe

    Germany
    UK


  APAC

    China
    India


  Middle East and Africa



  South America

By Application Insights

The predictive risk management segment is estimated to witness significant growth during the forecast period. Artificial Intelligence (AI) is revolutionizing the social media market, particularly in areas of advertising, data security, and user experience. Machine learning programs are used for content recommendation, fraud detection, and predictive risk assessment, enabling large enterprises to optimize their sales and marketing efforts and enhance customer experience management. AI technology is also employed for content creation, curation, and personalization, catering to user behavior, preferences, and sentiments. Sentiment analysis, chatbots, and automated moderation are essential tools for governments and businesses to ensure the ethical use of consumer data for targeted advertising campaigns. AI-enabled smartphones and Real-Time Operating Systems provide real-time information, daily news, and live updates, enhancing user satisfaction and engagement.

Furthermore, AI experts anticipate the growing role of virtual assistants, deep learning, and predictive modeling in the advertising industry, further transforming the social media sector.

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The predictive risk management segment was valued at USD 290.00 million in 2018 and showed a gradual increase during the forecast period.

Will Social Media landscape make North America the largest contributor to the Artificial Intelligence (AI) in Social Media Market?-

North America is estimated to contribute 41% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

For more insights on the market share of various regions Request Free Sample

The social media landscape in North America is witnessing significant growth due to the increasing adoption of advanced technologies such as cognitive computing, image recognition, and artificial intelligence (AI) by various industries, including retail, manufacturing, and healthcare. The region's high internet penetration and the millennial generation's preference for social media networking make it an attractive market for brands that are conscious about their image and customer demographics. Advanced analytics derived from unstructured data, metadata, comments, vlogs, podcasts, video sharing sites, and photo sharing sites are crucial for marketing campaigns and public reviews. Telecom organizations are leveraging LongTerm Evolution (LTE) and AdvancedLTE to enhance their social media presence and engage with customers effectively. System failure and security concerns have led to the increased use of AI technologies for social listening and customer engagement. The growth of the market is further fueled by global conferences, product launches, and product exhibitions, where organizations use AI to host and promote events.

Our researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

Market Dynamics

Artificial Intellig

According to Cognitive Market Research, the global Artificial Intelligence Software System Market size was XX million by 2033, whereas its compound annual growth rate (CAGR) was XX% from 2025 to 2033. North America held the largest share of the global Artificial Intelligence Software System market around XX% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of XX% from 2025 to 2033. Asia Pacific held a market share of around XX% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of XX% from 2025 to 2033. Europe accounted for a share of over XX% of the global market size of USD XX million. The Latin American market is around XX% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of XX% from 2025 to 2033. Middle East and Africa held the major market of around XX% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of XX% from 2025 to 2033.

Market Dynamics of the Artificial Intelligence Software System Market Key Drivers of the Artificial Intelligence Software System Market

Rising investment in AI start-ups will drive the growth of Artificial Intelligence Software System market

The future growth of the artificial intelligence (AI) software sector is expected to be fuelled by the increasing investments in AI startups. Companies that specialize in developing and implementing artificial intelligence (AI) solutions to solve specific problems or meet consumer demands are referred to as AI startups. Because of the increasing demand for AI solutions in industries, as well as their scalability and affordability, investments in AI firms are growing. Through promoting marketing and sales efforts, investment in AI startups will enable AI companies to increase their market share and encourage usage of software solutions. For instance, Frame is developing one of the top customer success platforms through offering top-ranked artificial intelligence software around a strong solutions framework with the goal of addressing many customer issues. https://explodingtopics.com/blog/ai-startups By constructing "The Voice of the Customer engine", teams would be able to use Frame to identify trends among customers, recognize customer retention or acquisition patterns, and convert qualitative feedback into quantitative information for leadership. For instance, on November 26, 2024, Meesho rolled out a multilingual Gen AI-powered chatbot intended to manage shoppers' inquiries. https://www.thehindu.com/sci-tech/technology/meesho-launches-multilingual-gen-ai-powered-chatbot-to-handle-shoppers-queries/article68913793.ece This chatbot provides customized, human-like support in various languages such as Hindi and English. It is designed to work effectively even on low-end smartphones and in noisy conditions, so it is available to users across a broad spectrum. The chatbot already processes around 60,000 calls per day and has a resolution rate of 95%, which greatly lowers the requirement for human intervention. Therefore, rising investment in AI start-ups will drive the growth of artificial intelligence software system market.

Restraint of the Artificial Intelligence Software System Market

Ethical concerns regarding AI use may hamper the artificial intelligence software system market growth

AI ethics issues include fairness, bias, privacy, accountability, transparency, and possible societal effects, requiring thoughtful consideration to make AI development and application positive and responsible. AI systems can inherit and magnify biases in the training data, resulting in discriminatory results. Biases may occur due to the data, algorithms, or implementation of the models. This can lead to discriminatory or unfair treatment of groups or individuals based on such factors as socioeconomic status, gender, or race. AI systems tend to need access to a lot of data, including sensitive personal data, with attendant privacy implications. For instance, UNESCO's 193 Member States voted on the Recommendation on the Ethics of Artificial Intelligence in November 2021 and adopted it as the first worldwide standard-setting document ...

Artificial Intelligence (AI) Processor Market Outlook

According to our latest research, the global Artificial Intelligence (AI) Processor market size reached USD 18.7 billion in 2024 and is expected to expand at a robust CAGR of 22.4% from 2025 to 2033. By the end of this forecast period, the market is projected to attain a value of USD 119.7 billion by 2033. This significant growth is primarily driven by the rising adoption of AI technologies across diverse sectors, including consumer electronics, automotive, healthcare, and data centers, as organizations increasingly seek advanced computational capabilities to support complex AI workloads.

One of the primary growth factors propelling the AI processor market is the exponential increase in data generation and the subsequent need for high-performance computing. As businesses and consumers generate vast amounts of data daily, the demand for processors capable of executing advanced AI algorithms in real time has soared. AI processors, including CPUs, GPUs, ASICs, and FPGAs, are specifically designed to handle such intensive tasks, enabling faster data processing, improved decision-making, and efficient automation. The proliferation of AI-powered applications, such as voice assistants, image recognition, and autonomous vehicles, further accelerates the demand for these specialized processors.

Another critical driver for the Artificial Intelligence Processor market is the rapid evolution of AI technologies, particularly deep learning and machine learning. These technologies require immense computational power, which traditional processors often fail to deliver efficiently. As a result, the industry has witnessed a surge in investments aimed at developing next-generation AI processors optimized for specific workloads. Advanced manufacturing nodes, architectural innovations, and the integration of AI accelerators into consumer devices are not only enhancing processor performance but also reducing power consumption, making AI solutions more accessible and cost-effective for a broader range of applications.

Additionally, the integration of AI processors in edge computing devices is revolutionizing the market landscape. Edge AI enables data processing to occur closer to the source, minimizing latency and bandwidth usage while ensuring data privacy and security. This trend is particularly prominent in sectors such as healthcare, automotive, and consumer electronics, where real-time decision-making is critical. The increasing deployment of AI at the edge, combined with advancements in 5G connectivity, is expected to unlock new opportunities for AI processor vendors and drive market growth over the coming years.

From a regional perspective, North America currently dominates the AI processor market, attributed to its strong technological infrastructure, high concentration of leading AI companies, and substantial investments in research and development. Asia Pacific, however, is poised for the fastest growth, supported by the rapid digital transformation in countries like China, Japan, and South Korea. The region benefits from a burgeoning consumer electronics industry, government initiatives to foster AI innovation, and a growing ecosystem of semiconductor manufacturers. Europe and other regions are also witnessing increased adoption of AI processors, driven by advancements in automotive technologies, smart manufacturing, and healthcare digitalization.

Processor Type Analysis

The AI processor market by processor type is segmented into CPU, GPU, ASIC, FPGA, and others, each playing a pivotal role in enabling AI workloads. Central Processing Units (CPUs) have traditionally been the backbone of computing, offering versatility and compatibility with a wide range of applications. However, as AI workloads have become more complex and data-intensive, the limitations of CPUs in terms of parallel processing capabilities have become apparent. While CPUs continue to be essential for general-purpose processing and control logic, their role in AI is increa

AI in Market Research Market Outlook

According to our latest research, the AI in Market Research market size reached USD 3.16 billion in 2024, with a robust compound annual growth rate (CAGR) of 21.8%. This remarkable momentum is fueled by the increasing adoption of artificial intelligence across diverse industries seeking data-driven insights and automation in research processes. By 2033, the global market is forecasted to reach USD 23.87 billion, underscoring the transformative impact of AI-powered technologies in redefining how organizations conduct market research, analyze consumer behavior, and make strategic decisions. The growth trajectory is shaped by the convergence of big data analytics, enhanced natural language processing, and the demand for real-time actionable intelligence.

One of the most significant growth factors propelling the AI in Market Research market is the exponential increase in data volume and complexity generated by digital transformation across industries. Organizations are inundated with structured and unstructured data from multiple channels, including social media, e-commerce platforms, and customer interactions. Traditional market research methods are often inadequate to process and analyze such vast datasets efficiently. AI technologies, particularly machine learning and natural language processing, enable businesses to sift through massive data pools, extract meaningful patterns, and generate actionable insights at unprecedented speed and accuracy. The ability to automate repetitive tasks, such as survey analysis and sentiment detection, further enhances efficiency and reduces human error, making AI an indispensable tool for modern market research.

Another key driver is the growing emphasis on personalized consumer experiences and competitive differentiation. As businesses strive to understand rapidly evolving customer preferences and market dynamics, AI-powered market research tools offer granular insights into consumer sentiment, purchasing behavior, and emerging trends. These tools leverage advanced algorithms to identify micro-segments, predict demand fluctuations, and optimize product offerings. The integration of AI with predictive analytics and real-time data processing empowers organizations to make informed decisions faster than ever before. Furthermore, AI's ability to continuously learn and adapt from new data ensures that market research remains relevant and forward-looking, providing a sustainable competitive edge in crowded marketplaces.

The democratization of AI-driven market research solutions is also fueling market expansion. Previously, sophisticated analytics and research tools were accessible primarily to large enterprises with significant resources. Today, cloud-based AI platforms and scalable service models are making advanced market research capabilities available to small and medium enterprises (SMEs) as well. This widespread accessibility is driving adoption across industries such as retail, BFSI, healthcare, and media, where agile decision-making and customer-centricity are critical. The proliferation of easy-to-use AI-powered dashboards and visualization tools further lowers the entry barrier, enabling organizations of all sizes to harness the power of AI for strategic growth and innovation.

From a regional perspective, North America continues to dominate the AI in Market Research market, accounting for the largest share in 2024, driven by the presence of leading technology providers, high digital maturity, and robust investment in AI research and development. Europe follows closely, with significant adoption in sectors like retail, finance, and healthcare, supported by favorable regulatory frameworks and a strong focus on data privacy. The Asia Pacific region is witnessing the fastest growth, propelled by rapid digitalization, increasing smartphone penetration, and a burgeoning startup ecosystem. Latin America and the Middle East & Africa are also emerging as promising markets, as organizations in these regions recognize the value of AI-driven insights in navigating complex market environments and enhancing competitiveness.

Component Analysis

The AI in Market Research market is segmented by component into software and services, each playing a pivotal role in driving adoption and value creation. The software segment, which includes AI platforms, data analytics tools, and machine learning algorithms, dominates the market due to its ability to automate complex analytical tasks, streamli

During a 2024 global survey, over **** (or ** percent) of responding consumers chose the lack of a human being to connect with as a concern around brands using artificial intelligence (AI), up from **** percent of the respondents a year earlier. Approximately ** percent mentioned job losses, while ** percent cited the misuse of their personal data.

Context

Artificial Intelligence (AI) is transforming the way people engage with e-commerce platforms. From personalized product recommendations and chatbots to dynamic pricing and ethical AI considerations, consumers are increasingly exposed to AI-driven features when shopping online. While these innovations enhance convenience and personalization, they also raise questions about trust, data privacy, and fairness.

This dataset was created through a structured survey designed to capture consumer experiences and perceptions of AI in e-commerce. It consists of 102 anonymized responses, primarily from students and young professionals, reflecting opinions on how AI influences their online shopping behavior.

Content

The dataset contains 102 entries and 20 columns, including:

• Demographics: Age group, gender, education, occupation.
• Shopping Behavior: Frequency of online shopping, awareness of AI tools.
• AI Interaction: Use of chatbots, recommendation engines, voice assistants, etc.
• Perceptions: Levels of trust, satisfaction, accuracy, and fairness.
• Concerns: Privacy issues, bias in recommendations, manipulative pricing.
• Attitudes: Views on transparency, ethics, and regulation in AI use.

Possible Uses

This dataset can be applied in multiple domains, including:

• Exploratory Data Analysis (EDA): Understanding consumer behavior toward AI.
• Statistical Testing: Hypothesis testing with categorical data (e.g., chi-square).
• Clustering/Segmentation: Grouping consumers based on trust or satisfaction.
• Predictive Modeling: Building models to predict consumer trust in AI features.
• Education & Practice: A small yet diverse dataset for teaching survey analysis, visualization, and machine learning basics.

Limitations

• Sample size: With 102 responses, results are not fully generalizable.
• Demographic bias: Majority of respondents are students/young professionals.
• Self-reported data: Responses may carry bias or subjectivity.

Acknowledgment

This dataset was collected as part of an academic project on “The Influence of AI in E-Commerce.” Special thanks to all survey participants for their contributions.

We used convenience sampling, and the data were collected from 2024-02-08 to 2024-10-29 using the CAWI technique on a group of students from three universities in Poland (in Toruń, Szczecin and Warsaw) and their relatives. We used our own questionnaire elaborated on an adjusted Schepman and Rodway scale model, i.e. The General Attitudes Towards Artificial Intelligence Scale (GAAIS), adapted to the context of our research. The questions in the research questionnaire were structured according to the TAM model and divided into spheres: perceived usefulness of AI solutions, ease of use of AI solutions, attitudes towards AI solutions, intentions regarding the use of AI in the future and actual use of AI. Our research sample consisted of 371 respondents.

Customer Experience AI Market Outlook

According to our latest research, the global Customer Experience AI market size reached USD 8.7 billion in 2024, exhibiting robust adoption across industries. The market is projected to expand at a CAGR of 19.6% from 2025 to 2033, resulting in a forecasted market value of USD 41.2 billion by 2033. This growth trajectory is fueled primarily by increasing digital transformation initiatives, the rising demand for hyper-personalized customer interactions, and the proliferation of omnichannel engagement platforms. As organizations worldwide continue to recognize the critical role of artificial intelligence in transforming customer touchpoints, the Customer Experience AI market is poised for sustained expansion and innovation over the forecast period.

One of the most significant growth factors driving the Customer Experience AI market is the escalating focus on delivering seamless, personalized, and responsive customer journeys. Organizations across sectors such as retail, BFSI, healthcare, and telecommunications are leveraging AI-powered solutions to gain actionable insights from vast datasets, automate repetitive processes, and anticipate customer needs in real time. The integration of advanced AI technologies, including natural language processing (NLP), sentiment analysis, and predictive analytics, enables enterprises to tailor their services, resolve queries faster, and drive higher customer satisfaction scores. Furthermore, the rise of omnichannel communication has necessitated the adoption of AI-driven tools that can ensure consistent experiences across digital, mobile, and physical channels, further bolstering market growth.

Another key factor propelling the Customer Experience AI market is the surge in investment in AI-enabled automation and analytics platforms. Businesses are increasingly deploying AI to automate customer support through chatbots and virtual assistants, reduce response times, and provide round-the-clock service. These technologies not only enhance operational efficiency but also free up human agents to focus on complex, high-value interactions. Additionally, AI-driven analytics empower organizations to derive deep insights into customer behavior, preferences, and pain points, enabling data-driven decision-making and proactive engagement strategies. The proliferation of cloud-based AI solutions has further democratized access, allowing enterprises of all sizes to harness the power of AI without significant upfront infrastructure investments.

The growing emphasis on compliance, data privacy, and ethical AI practices is also shaping the evolution of the Customer Experience AI market. As regulatory frameworks such as GDPR and CCPA become more stringent, organizations are prioritizing secure and transparent AI deployments to maintain customer trust. This has led to increased demand for explainable AI solutions and robust data governance frameworks that ensure responsible use of customer data. Moreover, the advent of AI-powered personalization engines is enabling brands to deliver contextually relevant content and offers, fostering deeper customer loyalty and lifetime value. Collectively, these factors are accelerating the adoption of AI technologies across customer-facing functions, setting the stage for sustained market expansion.

From a regional perspective, North America continues to dominate the Customer Experience AI market, accounting for the largest revenue share in 2024. The region's leadership is underpinned by the presence of major technology providers, early adoption of digital transformation strategies, and a mature ecosystem of AI startups and enterprises. However, Asia Pacific is emerging as the fastest-growing market, driven by rapid digitalization, increasing internet penetration, and rising investments in AI infrastructure, particularly in countries such as China, India, and Japan. Europe is also witnessing significant uptake, fueled by strong regulatory frameworks and a focus on customer-centric innovation. Meanwhile, Latin America and the Middle East & Africa are gradually embracing AI-driven customer experience solutions, supported by expanding e-commerce and financial services sectors.

Component Analysis

The Customer Experience AI market is broadly segmented by component into software, hardware, and services, each playing a crucial role in the deployment and adoption of AI-driven customer experience solutions. Software remains the dominant segment, accounting for a signi

In the course of consumer behavior, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behavior when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce (E-commerce) has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behavior, courses to understand consumer satisfaction. From the perspective of E-commerce companies, this study proposes to use artificial intelligence (AI) image recognition technology to recognize and analyze consumer facial expressions. First, it analyzes the way of human–computer interaction (HCI) in the context of E-commerce and obtains consumer satisfaction with the product through HCI technology. Then, a deep neural network (DNN) is used to predict the psychological behavior and consumer psychology of consumers to realize personalized product recommendations. In the course education of consumer behavior, it helps to understand consumer satisfaction and make a reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behavior rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This study provides a reference for consumer psychological behavior analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behavior education in the context of E-commerce.

The Generative AI Marketsize was valued at USD 43.87 USD Billion in 2023 and is projected to reach USD 453.28 USD Billion by 2032, exhibiting a CAGR of 39.6 % during the forecast period. Recent developments include: June 2023: Salesforce launched two generative artificial intelligence (AI) products for commerce experience and customized consumers –Commerce GPT and Marketing GPT. The Marketing GPT model leverages data from Salesforce's real-time data cloud platform to generate more innovative audience segments, personalized emails, and marketing strategies., June 2023: Accenture and Microsoft are teaming up to help companies primarily transform their businesses by harnessing the power of generative AI accelerated by the cloud. It helps customers find the right way to build and extend technology in their business responsibly., May 2023: SAP SE partnered with Microsoft to help customers solve their fundamental business challenges with the latest enterprise-ready innovations. This integration will enable new experiences to improve how businesses attract, retain and qualify their employees. , April 2023: Amazon Web Services, Inc. launched a global generative AI accelerator for startups. The company’s Generative AI Accelerator offers access to impactful AI tools and models, machine learning stack optimization, customized go-to-market strategies, and more., March 2023: Adobe and NVIDIA have partnered to join the growth of generative AI and additional advanced creative workflows. Adobe and NVIDIA will innovate advanced AI models with new generations aiming at tight integration into the applications that significant developers and marketers use. . Key drivers for this market are: Growing Necessity to Create a Virtual World in the Metaverse to Drive the Market. Potential restraints include: Risks Related to Data Breaches and Sensitive Information to Hinder Market Growth . Notable trends are: Rising Awareness about Conversational AI to Transform the Market Outlook .