Travel: The Agentic Commerce Shift: AI-Powered Holiday Shopping 2025

What is the Agentic Commerce Trend? Delegation is the New Discovery

• The rise of AI as a primary shopping assistant represents a fundamental shift toward agentic commerce. This trend is defined by consumers, particularly younger generations, outsourcing decision-making and research tasks to sophisticated AI platforms like large language models (LLMs). These AI tools move beyond simple search results to actively generate product ideas, compare value propositions, and even provide direct purchase links. This behavior transforms the shopping journey from passive browsing into a highly efficient, targeted, and assisted experience. The trend accelerates a move away from traditional search engines and influencer-led discovery toward trusted, personalized digital agents.

• It redefines consumer efficiency and value perception. For busy, value-conscious shoppers, AI serves as an indispensable "sidekick" that cuts through the noise of the crowded holiday retail landscape. By automating tasks like comparing prices and vetting the true worth of a "deal," AI helps consumers feel more confident and less fatigued by the annual shopping stress. This focus on maximizing value and minimizing effort is especially appealing in an economically uncertain environment where every dollar spent must be justified. It underscores a demand for smart, manageable choices rather than total luxury splurging.

• The trend highlights a generational split in technology adoption for commerce. Adoption rates are significantly higher among digital natives: 56% of Gen Z and 50% of Millennials plan to use AI for holiday shopping, far outpacing older demographics. This disparity indicates that comfort with LLMs and digital tools is the primary driver of the trend's growth. For younger consumers, AI integration is simply an expected baseline feature of the modern shopping ecosystem, blending seamlessly into their daily digital lives. This generational preference forces brands to rapidly develop a robust "Answer Engine Optimization" (AEO) strategy.

Why it is the topic trending: The Economic and Digital Crunch

• Economic Pressure and the Hunt for Value. With persistent inflation and geopolitical instability leading to tariff concerns, consumers are highly motivated to find the absolute best value for their money this holiday season. AI excels at complex, rapid data comparison, allowing shoppers to ensure a product's price point is genuinely the lowest and that a promotional offer is truly superior to year-round deals. This tactical use of technology transforms a typically stressful financial time into a manageable analytical challenge for the consumer. Consequently, the use of AI is directly tied to the desire for smart spending rather than total budget reduction.

• The Overload of Digital Retail and Decision Fatigue. The modern retail environment offers a near-infinite choice of products across countless online and social platforms, leading to severe shopper exhaustion and anxiety. As noted, over half of consumers report that using AI reduces the stress and fatigue associated with holiday purchasing. AI acts as a sophisticated filter, curating gift ideas and generating hyper-personalized recommendations that bypass the endless scrolling and targeted advertising bombardment. This focus on stress reduction positions AI as a wellness tool for the digital consumer.

• Rapid Maturation of Generative AI Technology. The recent leap in the capability and accessibility of large language models (LLMs) has made them practical for complex tasks like creative brainstorming and multi-step comparison, which are key to holiday gifting. Previously, AI in shopping was limited to basic chatbots or simple recommendation engines; now, consumers are using platforms like ChatGPT to prompt, "What can I get my 50-year-old aunt who loves knitting and birds?" and receiving nuanced, actionable gift ideas. This immediate utility makes AI an obvious and trusted starting point for the shopping journey.

Overview: AI: The New 56% Conversion Catalyst

The 2025 holiday shopping season marks the definitive entry of Artificial Intelligence into the mainstream consumer decision funnel, moving it from a niche tool to a critical component of retail navigation. Approximately one-third of all consumers plan to leverage AI, predominantly Gen Z (56%) and Millennials (50%), viewing it as a secret weapon against economic uncertainty and shopping fatigue. The primary use cases are tactical and strategic: brainstorming gift ideas, finding the lowest available prices, and verifying the true value of promotional deals. This adoption is underpinned by a rising level of trust, with many Gen Z users trusting AI recommendations as much as, or more than, those from friends and family. However, this transformative trend is tempered by consumer caution regarding data privacy (25%) and the potential for scams (19%), signaling that while adoption is swift, the demand for transparency and human-in-the-loop support remains paramount. Retailers must acknowledge that the future of commerce is "agentic," where AI manages the complexity and the brand must earn the trust of the AI and the end-user simultaneously.

Detailed findings: Gen Z's Secret Weapon: AI for Tactical Value

• Generational adoption is driving market penetration. Gen Z (56%) and Millennials (50%) are the core users of shopping AI, demonstrating a significant preference for tech-assisted purchasing. This high rate of use among peak-spending-power groups ensures that AI will quickly become a foundational layer of the digital retail experience. The trend among these demographics highlights that AI is not a fleeting trend but an embedded utility expected to transform shopping within three years, according to 81% of Gen Z respondents.

• AI is used for strategic, high-value tasks. Consumers are primarily leveraging AI to perform tasks that maximize efficiency and financial benefit: brainstorming gift ideas (39%), finding the lowest prices (37%), and checking deal value (30%). These findings indicate that AI is being used not for convenience alone, but as a strategic tool to optimize budget allocation and ensure a high return on effort during the busy season. Retailers need to ensure their pricing data is accurately represented within these AI models to remain visible.

• Trust and anxiety reduction are key psychological benefits. Beyond the practical features, consumers cite that AI reduces the overall stress and fatigue associated with the overwhelming holiday shopping process. This emotional benefit—making a complex task feel simpler and more controlled—is a powerful driver of continued adoption. Furthermore, the fact that a majority of Gen Z now trusts AI for gifting advice as much as, or more than, human sources signals a profound shift in consumer reliance on algorithmic authority.

• Skepticism remains a crucial constraint for mass adoption. Despite the embrace of AI's utility, significant portions of the consumer base still harbor serious concerns, specifically revolving around data privacy (25%), the risk of scams (19%), and the lack of human interaction (19%). These reservations act as a necessary guardrail, reminding brands that while efficiency is critical, trust, security, and the ability to access human support during resolution remain non-negotiable expectations. Any successful AI strategy must incorporate transparent data handling protocols and clear human fallback options.

Key success factors of The Trend: Frictionless Utility and Human Trust

• Seamless Integration into the Purchase Path. The most successful AI tools integrate fluidly into existing consumer digital habits, whether that is starting on a search-like LLM platform or within a retailer's own application ecosystem. The integration must be frictionless, allowing the user to jump from an AI-generated idea to a verified product link with minimal clicks or friction points. Any platform that requires extensive setup, new accounts, or redundant data entry will see significantly lower adoption rates.

• Demonstrable Value and Deal Validation. Success hinges on the AI’s ability to prove its superiority over manual research, primarily by consistently delivering better prices or more creative, high-impact gift recommendations. When an AI tool can unequivocally confirm that a deal is "truly worthwhile" or find a product link the consumer couldn't locate through simple search, it solidifies its value proposition. This requires real-time access to accurate pricing and inventory data across multiple ecosystems.

• Transparency and Trust Protocols. To counter the inherent consumer concerns about data privacy and scams, leading platforms must prioritize transparency in how data is used and how recommendations are generated. Success is built on clearly articulating the source of the recommendation, demonstrating robust security measures, and providing immediate access to human customer service for complex issues or errors. Maintaining the "human touch" at the point of friction is essential for long-term loyalty.

Key Takeaway: The Core Imperative: Optimize for the Algorithmic Gatekeeper

The 2025 holiday season confirms the shift to Agentic Commerce, where AI transitions from being a passive data source to an active, trusted agent that curates the shopping experience. This trend is overwhelmingly driven by Gen Z and Millennials seeking to reduce the cognitive load of holiday shopping while maximizing value amid economic pressures. For brands, the imperative is clear: optimize for AI platforms (AEO), prioritize data transparency, and integrate human-assisted resolution to balance technological efficiency with essential consumer trust.

Core trend: Algorithmic Ascent: Beyond Search to Orchestration

The core trend is the Algorithmic Ascent of Commerce, marking the moment when consumers willingly delegate complex research and gift-finding tasks to generative AI, moving digital discovery beyond traditional search or social media influence. This delegation signifies a desire for hyper-efficiency, personalized curation, and a reduction in decision fatigue, fundamentally restructuring the top of the retail funnel.

Description of the trend: The Seamless, Intelligence-Led Path to Purchase

This trend describes a structural change in consumer behavior where large language models (LLMs) and specialized AI tools are used to orchestrate the initial stages of the purchase journey. The AI acts as a smart, personalized filter, synthesizing product data, price histories, and gift context to deliver optimized results (e.g., "the perfect gift idea + the lowest verified price + a direct link to purchase"). This contrasts sharply with legacy e-commerce, which relied on the consumer doing most of the heavy lifting. The result is a highly streamlined, intelligence-led path to conversion, driven by the younger demographic's demand for utility and instant gratification.

Key Characteristics of the trend: Value Verification and Generational Divide

• Delegated Discovery & Curation: Consumers are offloading the mental burden of brainstorming and sifting through overwhelming options to AI agents. These agents are expected to not only present options but also to filter them based on nuanced, complex prompts that integrate budget, recipient interest, and current availability. This outsourcing of cognitive effort is a primary driver for the trend's stress-reducing benefit.

• Value Verification over Simple Pricing: The use of AI goes beyond simple price comparison; it includes checking whether a deal is труly worthwhile compared to historical pricing or competitive offers. This indicates a sophisticated, tactical shopper who uses AI to validate the integrity of promotional claims, prioritizing demonstrable financial prudence over impulsive buying. This characteristic reflects an overall cautious spending mindset in the face of rising costs.

• High Generational Concentration: The rapid adoption rate is disproportionately concentrated among Gen Z and Millennials, creating a clear technological divide in shopping behavior between digital natives and older cohorts. This segment-specific penetration means that AI-driven commerce strategies are now essential for engaging the market's most influential and future-defining consumer groups. Their high confidence in AI for personal advice underscores their comfort with algorithmic authority.

Market and Cultural Signals Supporting the Trend: Digital Fatigue and LLM Normalization

• Decline in Search and Social Effectiveness for Curation: As traditional search results become increasingly saturated with advertising and social media feeds are cluttered with non-contextual content, AI offers a clean, direct, and non-commercialized (in appearance) route to product discovery. Consumers are fatigued by the pay-to-play nature of conventional digital advertising, viewing AI as an unbiased, objective assistant, even though brand data inputs remain critical. This cultural shift reflects a desire for authenticity and utility.

• Embedding of LLMs into Daily Life: The daily use of LLMs (such as ChatGPT or Perplexity) for general knowledge, work tasks, and creative output has normalized the interaction with generative AI for millions of consumers. This familiarity lowers the barrier to entry for using the same tools for commerce-related tasks. The convenience of using a single, familiar conversational interface for both information and transaction makes AI a natural extension of the digital toolkit.

• The Continued Economic Prudence Post-Inflation: The prevailing culture of "smart spending," driven by ongoing concerns about tariffs and cost of living, validates any tool that guarantees financial optimization. The cultural narrative focuses on intentional, necessary, and high-value purchases, contrasting with past eras of impulse consumerism. AI perfectly aligns with this mindset by promoting a highly calculated, risk-averse, and resource-efficient shopping process.

What is consumer motivation: Trade Stress for Simplicity

• The Primary Motivation is Stress Reduction and Efficiency. The holiday shopping season is notorious for creating time pressure and emotional stress, which AI directly addresses by reducing the mental effort required to find the "perfect" gift. By automating the research, comparison, and verification phases, AI acts as a sophisticated organizational buffer. This efficiency is highly valued by Millennials balancing career and family obligations and by Gen Z navigating budget constraints.

• Motivation for Financial Prudence (Value-Seeking). In an era defined by economic caution, consumers are motivated to use AI to ensure they are getting the maximum possible value for every purchase. The drive is not merely to find the lowest price, but to feel certain that they have strategically outsmarted the sales cycle and avoided paying full price. This tactical motivation transforms the chore of budgeting into a game of optimization led by their AI sidekick.

• A Desire for Hyper-Personalized Gifting. Consumers are motivated by the difficulty of finding truly unique and thoughtful gifts for people who seemingly already have everything. AI is used as a creative muse, synthesizing deep contextual information about the recipient to generate non-obvious, highly tailored recommendations that feel personal. This addresses the emotional motivation of giving a meaningful gift, which is harder to achieve through generic search queries.

What is motivation beyond the trend: Bypassing the Marketing Façade

• Demand for Algorithmic Authority and Trust. Beyond the surface-level efficiency, consumers are motivated by a growing trust in algorithmic objectivity compared to potentially biased human recommendations or heavily optimized search results. For a generation raised on data and personalization, a high-performing algorithm carries more weight than a social media influencer paid for a promotion. This reflects a deeper, cynical motivation to bypass perceived marketing facades.

• The 'Always-On' Commerce Identity. The motivation extends to incorporating shopping into a seamless, perpetual digital existence rather than scheduling it as a discrete, periodic activity. With 48% of consumers maintaining a 'perpetual shopping list,' AI tools facilitate this "shopping as a state of mind" by making product discovery and price tracking an ongoing, integrated background process. This motivates consumers to use tools that blur the line between content, communication, and transaction.

• A Preference for Agentic Control. Consumers are motivated by the desire to use advanced technology to gain control over their environment and decisions. Using AI to manage complex retail variables—tariffs, price fluctuations, inventory—gives them a sense of empowerment and mastery over market volatility. This is a behavioral motivation rooted in digital literacy and the expectation that technology should serve to simplify and enhance personal agency.

Description of consumers: The Omnichannel, Value-Driven Digital Native

• Digital Natives Leading the Charge (Gen Z & Millennials): The core consumer is overwhelmingly represented by Gen Z (ages 18-28) and Millennials (ages 29-44), demonstrating high digital fluency and an expectation that technology should seamlessly integrate with all aspects of life. Their lifestyle is mobile-first, socially-influenced, and defined by a constant seeking of efficiency and personalized experiences. They are comfortable with sharing data in exchange for superior utility.

• Income Bracket (Varies, but value-focused): While specific income data is not detailed in the public snippet, this group spans from early-career Gen Z facing budget tightening to established Millennials with peak earning power and high fixed expenses. Regardless of income, the collective lifestyle is value-driven, where AI is a tool to stretch discretionary dollars and prioritize intentional spending over impulse luxury. Lower-income segments use AI for essential budget adherence, while higher-income segments use it for time efficiency.

• Lifestyle (Omnichannel, Skeptical, and Intentional): Their lifestyle is defined by blending online and in-store experiences (28% prefer a fully blended experience), high reliance on social media for inspiration, and a skeptical stance toward traditional advertising. They are intentional shoppers who budget smartly, use BNPL options, and prioritize sustainable or ethical factors (34% of Gen Z). They demand speed, simplicity, and personalized interactions.

Consumer Detailed Summary: The 18−44 Cohort: Demanding Efficiency and Trust

• Who are them? The AI-powered shopper is predominantly the digitally native consumer, comprised of Gen Z and Millennials. These are individuals who grew up with the internet, social media, and algorithmic recommendations, making them naturally inclined to delegate complex decisions to sophisticated platforms. Their purchasing power is rapidly increasing, and they are setting the future standards for e-commerce interaction.

• What is their age? The primary age cohort is between approximately 18 and 44 years old. This range covers the youngest shoppers just entering the workforce (Gen Z) up to established family builders (Millennials) who are actively seeking ways to reduce the time spent on necessary tasks like holiday shopping. Their life stage demands high utility and maximum efficiency.

• What is their gender? While gender data is not explicitly provided in the core survey findings, digital usage trends often show balanced adoption across genders, with slight variations based on product category. Both male and female consumers within these cohorts are highly active online and equally value tools that promise convenience and deal-finding efficiency. In the context of gifting, AI is likely used equally by both genders to manage the complex logistics and creative demands of giving.

• What is their income? The income levels are broad, ranging from lower-to-middle income for Gen Z to middle-to-high income for established Millennials. Crucially, regardless of absolute income, this group exhibits a shared value-conscious mindset driven by macroeconomic uncertainty. AI adoption is a mechanism for both budget maximization in tighter situations and for reducing the friction of finding unique luxury or high-end items quickly in wealthier segments.

• What is their lifestyle? Their lifestyle is characterized by being hyper-connected, omnichannel, and seeking a life-work-digital balance. They integrate shopping into their daily digital flow ("always-on" commerce), prioritize flexible payment options like BNPL, and are highly influenced by authenticity and user-generated content (UGC). They demand that retail experiences be frictionless, fast, and emotionally intelligent.

How the Trend Is Changing Consumer Behavior: From Passive Searching to Prompt-Driven Buying

• Shift from Searching to Prompting for Discovery: Consumers are moving away from traditional keyword-based searching (e.g., "best gifts for dad") to natural language prompting in LLMs (e.g., "Generate 10 affordable, sustainable gift ideas for a father who loves hiking and coffee, linking to products under 50"). This changes the expectation from receiving a list of links to receiving a curated, executable recommendation. It fundamentally alters the role of the brand's digital presence from SEO to AEO (Answer Engine Optimization).

• Increased Confidence in Tactical Spending Decisions: The use of AI for deal verification (30%) means consumers are becoming more confident and decisive, relying less on instinct or simple promotional headlines. This changes behavior by accelerating the buying process once a recommendation is validated by the AI. It fosters a mindset of "if the AI approves it, it's a smart buy," leading to faster conversion rates for trusted products.

• Elevation of Emotional Utility (Stress Reduction) as a Purchase Driver: Beyond price and convenience, the behavioral outcome of reduced stress and fatigue is now a key factor in tool adoption. Consumers are subconsciously prioritizing platforms and retailers that offer AI integration because it makes the experience of shopping more pleasant, not just the outcome. This psychological benefit drives platform loyalty that simple discounts cannot replicate.

Implications of trend Across the Ecosystem: From AEO to Blended Customer Service

• For Consumers: AI creates a less stressful, more efficient, and financially optimized shopping journey. Consumers gain a personalized "super-assistant" that filters noise, validates deals, and provides customized gift ideas, ultimately saving them time and money. However, they must remain vigilant about data privacy and the potential for AI-driven scams, which are the main risks associated with this delegation.

• For Brands and CPGs: Brands must urgently shift their digital marketing strategy from traditional SEO to AEO (Answer Engine Optimization). Their product data, inventory status, and pricing must be flawlessly available and structured for ingestion by LLMs, as the AI becomes the gatekeeper of visibility and recommendation. Furthermore, brands must invest in transparent data use policies and ensure their value proposition is clear enough to be accurately summarized by an external agent.

• For Retailers: The retail sector needs to prioritize frictionless omnichannel experiences and integrate AI into their customer service and logistics. Retailers must leverage AI not just for external recommendations, but internally to manage inventory and pricing, ensuring the information given to consumers is accurate and minimizing friction points like high shipping costs (44% frustration point). The store's digital front door must be optimized for speed, simplicity, and human-in-the-loop support when issues arise.

Strategic Forecast: The Race to the "Trust Layer"

• Hyper-Personalized Gifting via Generative Agents will become standard in Q4 2026. Within the next year, basic AI assistants will evolve into advanced generative agents capable of handling multi-step tasks like drafting a personalized gift message, arranging delivery, and finding complementary items automatically. This shift means that retailers will compete primarily on the quality and seamless integration of their proprietary AI services.

• The Regulatory and Trust Framework will Evolve Rapidly in 2026. Given the consumer concerns over data privacy (25%) and scams (19%), there will be increasing pressure on regulatory bodies to define clear guidelines for AI in commerce, forcing platforms to provide auditable transparency on how product data is prioritized and how personal data is utilized to generate recommendations. Trust badges will likely emerge for "AI-Verified Deals."

• AI Integration will Become the Baseline Expectation for Customer Service Resolution. While consumers demand a human touch for problem resolution (96% prefer human intervention), AI will become the indispensable first layer for instant diagnosis and routing of complex issues. Retailers who successfully blend AI speed with human empathy at the moment of truth will capture market share.

Areas of innovation (implied by trend): Blending Finance, Trust, and Generative Gifting

• "Trust Layer" Protocol for Algorithmic Transparency. Innovation is required in developing technology that transparently validates an AI's source data and its recommendation logic, potentially providing a "Trust Score" nextable to product suggestions. This will directly address consumer skepticism and concerns about bias or scams by making the AI's decision-making process auditable and visible to the end-user.

• Generative Gifting Ecosystems (GGES). This involves creating platforms where AI can access and synthesize complex, multi-source data—such as a recipient’s publicly available wish lists, social media interests, and past purchase history—to generate truly inspired, non-obvious gift solutions. This requires secure, permission-based data aggregation and high-fidelity LLM outputs tailored for emotional resonance.

• Frictionless Financial Health Tools Integrated with Commerce AI. Future innovation will blend shopping AI with personal finance management (PFM) tools, allowing users to seamlessly check their spending against their budget or BNPL commitments during the shopping process. This integration aligns the AI assistant with the consumer's deep-seated motivation for intentional and managed spending.

Summary of Trends: The New Commerce Mandate

• Core Consumer Trend: The Delegation Economy Consumers are moving toward a delegation economy where mental fatigue is reduced by outsourcing complex, data-heavy tasks like deal vetting and creative brainstorming to AI. This shift is driven by a desire for both efficiency and emotional relief during a high-pressure season.

• Core Social Trend: Trusting the Machine A growing segment of digital-native consumers now places equal or greater trust in algorithmic recommendations compared to traditional human sources (friends, family, influencers). This signals a profound cultural shift where verified data output is prioritized over subjective personal opinion, particularly in financially sensitive decisions.

• Core Strategy: AEO (Answer Engine Optimization) Supremacy For brands, the winning strategy centers on optimizing product data for AI platforms, recognizing that the AI has become the primary gatekeeper and curator of the retail funnel. Visibility now means ensuring rich, accurate, and easily structured data is ingested by the LLMs consumers use.

• Core Industry Trend: The Blended Service Model The retail industry is converging on a blended service model that leverages AI for speed and scale while reserving human capital for moments of high-friction or emotional complexity (e.g., returns, disputes). Successful retailers will be those who can seamlessly pivot from AI-driven automation to empathetic human support.

• Core Consumer Motivation: Relief from Cognitive Overload The fundamental driver of AI adoption is the need for relief from the cognitive overload imposed by endless choice and economic uncertainty. AI serves a deep psychological need for control and simplification in a chaotic market.

• Trend Implications: The Agentic Future of the Purchase Funnel The trend implies a complete remapping of the purchase funnel, where the initial "Inspiration/Discovery" phase is now managed by an AI agent, shifting the brand mandate from advertising to data excellence and service integration. Brands must now compete to be the preferred recommendation of the consumer's AI assistant.

Final Thought (summary): AI as the Ultimate Value & Stress Filter

The 2025 holiday shopping season serves as the definitive inflection point for "Agentic Commerce." The data confirms that AI is not a supplement to shopping; it is rapidly becoming the structural foundation for the younger generations' retail journey, a powerful tool used to achieve both financial prudence and emotional ease. The most successful brands and retailers will be those that prioritize building trust directly into their AI ecosystem, ensuring transparency, security, and a clear path to human intervention. The future of commerce is one where the machine handles the complexity, allowing the consumer to focus on the meaning of the gift, not the struggle of finding it.

Source: https://www.retaildive.com/news/consumers-ai-shopping-tools-holidays-retail/801800/