Enterprise AI Analysis
The new era of Artificial Intelligence in consumption: theoretical framing, review and research agenda
This paper explores the transformative impact of Artificial Intelligence (AI) on consumer behavior, analyzing 561 publications from Web of Science and Scopus. It highlights how AI reshapes brand-consumer dynamics, enhances customer service through personalized interactions and AI-powered tools like chatbots and virtual assistants, and influences consumer decision-making across diverse industries. The study proposes a conceptual model of AI's influence across industries, consumer needs, and experience optimization, and outlines future research pathways.
Executive Impact at a Glance
AI significantly reshapes brand-consumer dynamics, enabling businesses to analyze extensive datasets, discern patterns, and customize experiences. Consumers increasingly prefer AI-driven solutions due to their perceived objectivity and personalized interactions. AI-powered tools enhance customer service and engagement. The research identifies critical themes for future study, including long-term effects, consumer loyalty, trust, psychological impacts, and ethical considerations.
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Publications Analyzed
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Recent Publication Growth (2021-2024)
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Peak Citations (2021)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Influence across Industries
Addressing Consumer Needs
Optimizing Consumer Experience
Influence across Industries
This dimension explores how AI is integrated into customer-facing services, consumer preferences for AI-driven solutions, and the challenges and opportunities of AI in various industries like tourism, financial services, and healthcare.
83%
of consumers prefer AI-generated tourism plans despite occasional errors due to perceived objectivity and personalization.
| Aspect | Opportunities | Challenges |
|---|---|---|
| Interactions |
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| Trust & Privacy |
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| Emotional Aspects |
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| Adoption Barriers |
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AI in Financial Services
Problem: Traditional credit scoring and banking applications are often inefficient and prone to human bias.
Solution: AI is leveraged for credit scoring and banking applications to analyze extensive datasets and discern patterns.
Result: Research shows improved efficiency and reduced bias, though challenges related to emotional interactions and privacy remain a focus for further study. AI offers significant potential for enhancing customer satisfaction and providing personalized financial advice.
Addressing Consumer Needs
This dimension focuses on the complementary relationship between AI and human managers, consumers' readiness to embrace AI, and the impact of AI on consumer behavior and brand engagement, including anthropomorphism and responses to AI service failures.
AI Adoption and Consumer Readiness
AI complements human managers (not replaces)
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Consumers open to novel AI experiences
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AI provides broad range of customized options
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Less negative feedback for AI failures
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Anthropomorphism influences positive experiences
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Voice assistants influence low-involvement purchases
75%
of consumers expect AI not only to provide a service but to do so in a way that feels personalized and intuitive.
| Aspect | Positive Effects | Challenges/Considerations |
|---|---|---|
| Engagement |
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| Adoption |
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| Trust |
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| Effectiveness |
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Optimizing Consumer Experience
This dimension highlights the optimization of consumer experience through AI-powered solutions in retail, adaptive service recovery strategies, and the significance of AI in voice-enabled applications and biometric payment systems, emphasizing personalization and trust.
AI in Retail Environments
Problem: Optimizing customer experience in both online and physical retail requires advanced personalization and efficient service.
Solution: AI-powered retail solutions enhance personalization, influence purchase decisions, and integrate adaptive service recovery strategies.
Result: Consumers' optimism positively affects AI perceptions, leading to increased willingness to purchase, especially in luxury segments. AI mitigates in-store service influence on online platforms, enabling customized solutions and improved user engagement through chatbots and voice assistants.
AI's Role in Adaptive Service Recovery
Identify service failure type (informational vs. emotional)
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Tailor AI recovery strategy (anthropomorphism for emotional, informational for factual)
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AI-powered chatbots streamline customer journey
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Provide immediate responses and product info
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Enhance user engagement
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Facilitate purchasing process
45%
increase in customer satisfaction when AI chatbots offer tailored solutions based on diverse data and consumer knowledge.
Calculate Your Potential AI ROI
Estimate the time and cost savings your enterprise could achieve by integrating AI solutions based on this research.
Your AI Implementation Roadmap
A strategic phased approach to integrate AI into your enterprise, maximizing impact and minimizing disruption.
Phase 1: Assessment & Strategy
Conduct a comprehensive audit of current customer interaction points and identify AI integration opportunities. Define clear KPIs for success and select pilot projects.
Duration: 2-4 Weeks
Phase 2: Pilot Program Development
Develop and deploy AI-powered chatbots or virtual assistants for specific customer service functions. Gather initial user feedback and fine-tune algorithms.
Duration: 4-8 Weeks
Phase 3: Expanded Integration & Training
Roll out AI solutions to broader customer segments and integrate with existing CRM systems. Train human staff to collaborate effectively with AI, focusing on handling complex cases.
Duration: 8-12 Weeks
Phase 4: Continuous Optimization & Scaling
Implement continuous learning loops for AI systems based on ongoing customer data. Regularly evaluate performance against KPIs and explore new AI applications.
Duration: Ongoing
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