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How AI will change the relationship between consumers and consumer goods manufacturers

September 18, 2025

How AI will change the relationship between consumers and consumer goods manufacturers

Our AI Inclination Index reveals which consumers are most open to using AI in the consumer goods purchase journey—as well as where and how they’ll use it. Knowing this, manufacturers can develop a highly nuanced and effective consumer-facing AI strategy.

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Consumer goods manufacturers have long wanted to forge a closer relationship with the customers who buy and use their products. Their recent investments in AI-based smart manufacturing technology could go a long way in helping them cut through what has historically made that difficult. Using AI-driven insights into individual preferences, shopping history and profiles, consumer goods manufacturers may soon be able to anticipate a customer’s journey before it begins. And <a href="https://manufacturingleadershipcouncil.com/survey-manufacturers-go-all-in-on-ai-35350/#:\~:text=Manufacturers%20are%20ramping%20up%20digital,KEY%20TAKEAWAYS%3A\&text=Digital%20transformation%20is%20a%20game,after%20a%20dip%20in%202024." target="_blank">with 47% of manufacturers</a> currently using generative AI tools in their manufacturing operations, those capabilities may soon change the consumer goods purchase journey as we know it. First, however, consumer goods manufacturers need to understand more about how AI will change consumer behavior. Which consumers are most (and least) inclined to use AI? Which tool would they prefer to use? Where in the purchase process would they be most comfortable using it?  And what are the implications for manufacturers’ existing business models and strategies? To answer these questions, we used data from our recent consumer AI study to develop the AI Inclination Index, which quantifies consumers’ propensity to use the technology. We found that consumers’ inclination to use AI for consumer goods purchases nearly meets or exceeds the average across industries studied. Beyond that high-level finding, we also found important distinctions in AI attitudes across the three key phases of the consumer journey (Learn, Buy and Use) and the five manufactured goods segments defined in our study:    <ul> <li>Everyday essentials (e.g., groceries, toiletries)</li> <li>Small purchases (e.g., shoes, clothing, beauty)</li> <li>Large purchases (e.g., electronics, appliances)</li> <li>Luxury goods (e.g., designer clothing and accessories)</li> <li>Unexpected needs </li> </ul> Consider these AI adoption metrics in the consumer goods purchase experience: <ul> <li>Consumers are much more apt to use AI in the Learn vs. the Use phase—but there’s more to the story. Despite consumers’ relatively lower inclination to use AI in the Use phase, manufacturers are well positioned in the post-purchase phase to leverage the AI and digital agents they’ve deployed in their recent value chain transformation efforts. By embedding AI into their products, manufacturers could cross-sell and upgrade services and capabilities to their customers and offer real-time maintenance and support. This represents a new dimension for both the consumer experience and manufacturers’ market opportunities. </li> <li>Higher-income consumers shape AI-enabled purchasing. Low- and medium-income consumers demonstrated similar interest in using AI across all five manufactured goods product categories and all phases of the purchase journey. In contrast, high-income consumers scored much higher; in the Buy phase, their scores were twice as high as their lower- and medium-income counterparts. </li> <li>Technology attitudes and AI comfort level are highly contextual. Consumers’ comfort with using both digital technologies and AI tools varies by age, income, product category and journey phase. While younger cohorts tend to be more comfortable with digital technology generally, older groups demonstrate a higher comfort level specifically with AI tools. </li> <li>Conversational AI is the tool of choice—and a key opportunity for manufacturers. Across the five product categories in our study, consumers— particularly those in the high-income cohort—most often identified conversational AI as their tool of choice. Conversational AI also provides manufacturers an immediate opportunity to deepen their relationship with customers, particularly for products that can be embedded with AI capabilities.</li> </ul> The AI Inclination Index To quantify consumers' propensity to adopt AI-driven technology features throughout the consumer journey, we developed the AI Inclination Index. The index was calculated using three measures from our New minds, new markets survey data.

AI inclination in consumer goods vs. the global average Consumers' inclination for using AI for manufactured goods nearly meets or exceeds the average across industries studied.

3550101_GMPSM-TL New minds, new markets - Industry - Retail blog

Figure 1  Base: 8,451 respondents in the US, UK, Germany and Australia  Source: Cognizant Research  With these variances across consumer groups and journey stages, it’s clear consumer goods manufacturers will need to craft a precise and nuanced AI strategy that captures the greatest areas of opportunity while avoiding low-value pursuits.  Understanding consumer use of AI, as well as the accompanying pockets of spending power, is essential for leaders in all industries. In our global study “<a href="https://www.cognizant.com/us/en/new-minds-new-markets-ai-customer-experience" target="_blank" rel="noopener noreferrer">New Minds, New Markets</a>,” we found that consumers who are enthusiastic about using AI will account for up to 55% of all purchases made across industries. This amounts to $4.4 trillion in spending in the US, $690 billion in the UK, $690 billion in Australia and $540 billion in Germany.   In this report, manufactured goods leaders will learn about where in the purchase journey consumers are most and least inclined to use AI, the AI tools they would be most apt to use and how this differs among consumers across age groups. With this information, businesses can reshape their approach to customer engagement—where and how it matters most.

About the research

This research is based on our “New minds, new markets” study, which included a survey of over 8,400 respondents in four countries and across 16 industries, extensive economic modeling and in-depth discussions with 80 consumers.

<h4> AI across the manufactured goods consumer journey</h4> Using AI to augment human capabilities and transform operations isn’t new to manufacturers. With advanced manufacturing initiatives, manufacturers have already used AI to optimize inventory and predict demand, automate quality checks and design products. Further, manufacturers’ investment in AI <a href="https://www.weforum.org/stories/2024/01/company-using-ai-transform-manufacturing-business/" target="_blank" rel="noopener noreferrer">is expected to grow 57%</a> by 2026, from a baseline of $1.1 billion in 2020 to $16.7 billion. That foundation positions manufacturers to extend the reach of their intelligence beyond suppliers and intermediaries to customers. In fact, <a href="https://manufacturingleadershipcouncil.com/survey-manufacturers-go-all-in-on-ai-35350/?stream=mlc-research" target="_blank" rel="noopener noreferrer">23% of manufacturers</a> say they’ve already deployed AI for customer-facing systems, and 70% say they will do so by the end of this year.   However, consumers’ inclination to engage with product manufacturers through AI will be highly contextual. For example, interest in using AI for essentials and small purchases is higher than the cross-industry average across the board but particularly in the Buy and Use phases. At the same time, AI inclination is much lower for larger-ticket and luxury items. Similar differences can be found based on consumer age, income and comfort level with AI, or experience with digitized shopping.

About our analysis

To understand consumer AI behaviors and attitudes at a granular level, we structured our analysis around four key pillars:

The consumer journey. We studied the specifics of AI use at each phase of the customer journey. This journey—how consumers discover, purchase and engage with products and services before and after a sale—is at the heart of the business-customer relationship.

Consumer demographics. To gain a better understanding of how consumer attitudes and behaviors differ by age group, we divided consumers into five categories: 18-24, 25-34, 35-44, 45-54, and 55+.

Consumer AI tools. We defined consumer AI use by asking about their intended use of three key tools that are prevalent in the consumer world: voice assistants, chatbots and conversational AI.

Industry-specific products. We included five consumer goods product categories in our analysis: everyday essentials, small, large, luxury and unexpected purchases.

<h5> The Learn phase: Consumers are enthusiastic about using AI to learn about everyday consumer goods</h5> <ul> <li><a>AI enthusiasm is highest when the stakes are low</a> </li> <li>Consumers 55+ lead in AI tool comfort </li> <li>AI adds a new dimension to product discovery</li> </ul> With an AI index score of 88 (out of 100), consumers of manufactured goods demonstrate a strong propensity to use AI for discovering and learning about products. As one consumer noted, “I’m keen for AI to help me in product research—for example, in helping me compare and select appliances.” AI tool comfort scores are bolstered, in part, by the dramatic uptake in consumers using generative AI over the past year. Analysis of online purchases performed by Adobe found that in that time, <a href="https://blog.adobe.com/en/publish/2025/03/17/adobe-analytics-traffic-to-us-retail-websites-from-generative-ai-sources-jumps-1200-percent" target="_blank" rel="noopener noreferrer">55% of consumers</a> used gen AI to research products. As such, the Learn phase represents a prime opportunity for manufacturers to capture attention and influence decisions. Doing so starts with understanding what consumers value about using AI in this phase and which tools they’re most apt to use. Consumer goods manufacturing AI Inclination Index: The Learn phase

Figure 2 Base: 8,451 respondents in the US, UK, Germany and Australia Source: Cognizant Research AI enthusiasm is highest when the stakes are low Of the five product categories in our study, small purchases and everyday essentials attracted the greatest interest in AI. The index scores for these two categories are five and three points, respectively, above the global average of 90. As one consumer said, “When it comes to purchases you're making for your household, even if you lost out, it wouldn't be the end of the world.” Both product categories have a healthy technology comfort score of 37, above the cross-industry average of 32 for the Learn phase. This score indicates a positive disposition toward using digital technologies, such as smartphones, to learn about small-ticket purchases such as sundries, food, clothing and toiletries. However, the opposite is true for large items or luxury goods, which scored four and seven points, respectively, below the global average. Here the stakes are higher, as these items not only are more expensive but are also less frequently purchased. As one consumer summed up, “The larger the purchase, the more concerned I’d be.” The increased willingness of consumers to learn about new products with AI points to a change in how manufacturers should approach the market. Consumer AI agents, authorized by consumers to find deals on small purchases or everyday essentials, may choose to go directly to manufacturers if the option exists, bypassing retailers. While large retail stores and websites may be convenient for consumers, AI agents that can efficiently navigate multiple suppliers can consolidate products from a wider range of sources in less time. This will open doors for manufacturers to deliver directly to consumers, without the traditional overhead or market friction associated with doing so. Consumers 55+ lead in AI tool comfort As expected, not all consumer groups share the same propensity to use AI-enabled tools in product research. For example, the youngest cohort (18–24) posts technology comfort scores of 41 and 42, respectively, for essentials and small purchases, compared with the average of 38 for both product categories. Yet, this cohort also had some of the lowest AI tool comfort scores (26 and 24 vs. the average of 29). So, while this age group is tech-savvy, they’re not necessarily the biggest AI enthusiasts. In <a href="https://www.waltonfamilyfoundation.org/about-us/newsroom/gen-z-is-using-ai-but-reports-gaps-in-school-and-workplace-support">a recent Gallup study</a>, in fact, 47% of Gen Z respondents said they used AI weekly; however, 41% felt anxious about the technology, and 49% fear AI will harm their ability to think carefully about information. Meanwhile, the 55+ group scored highest in AI tool comfort for all product categories except luxury goods. This is not entirely surprising, as these consumers—who expressed lower technology comfort—would stand to benefit from AI tools that would remove complexity from the online experience. Our research also finds that AI use is very income-sensitive, with higher-income respondents showing a greater inclination to use AI to learn about consumer goods than medium- or lower-income consumers, with index scores of 36, 27 and 24, respectively. While high-income consumers posted the highest scores in luxury and unexpected purchases, low-income consumers had the highest conversational AI scores for not only essential goods but also large purchases. This indicates that consumers of all income levels are open to using AI to learn about more complex, higher stakes purchases. AI adds a new dimension to product discovery The data that consumer AI agents require will fundamentally transform how manufacturers can assist and influence customer research and product discovery. For instance, maintenance and performance data provided by connected products, such as home gym equipment and smart baby products, could prove invaluable to both consumers and manufacturers. It would help consumers find reliable products while helping manufacturers prove the credentials of their goods. By providing this information, manufacturers allow consumer agents to parse and evaluate their offerings when searching for low-maintenance, high-performance replacements. While this may seem far-fetched, the market is already packed with comparison websites and intermediaries that examine this data and present it to consumers—from energy usage to total cost of ownership. By providing more transparency into this data, manufacturers could ensure that a product gets on the AI agent’s radar and makes the buyer’s short list, while withholding it could mean exclusion altogether. This shift also highlights the potential for AI to be used for decision-making, even in high-value and high-risk purchases. As one consumer remarked, the prospect of having AI simplify evaluations and pinpoint superior options demonstrates a powerful use case that manufacturers cannot afford to ignore.

<h5>The Buy phase: AI opens a checkout lane for manufacturers</h5> <ul> <li>Familiarity with digital tools bolsters comfort with AI </li> <li>Older consumers once again lead in AI tool comfort </li> <li>Higher-income consumers are more willing to automate purchasing with AI</li> </ul> Consistent with the findings of our cross-industry study, consumer interest in AI drops from the Learn to the Buy phase. At the same time, the above-average AI inclination scores suggest consumers are more ready to automate the purchase of manufactured goods than other products and services in other industries. With an index score of 61, consumers demonstrate a higher propensity than the cross-industry average (56) for using AI at this phase. This gives manufacturers an edge when it comes to expanding the customer relationship. In some industries, particularly in business-to-consumer sectors like retail, the Buy stage of the customer journey is purely transactional—the business already has a relationship with the customer. What these businesses lack, however, is control over the product. The job for manufacturers is to ensure consumer comfort with this rewired automation through the entire product lifecycle. Consumer goods manufacturing AI Inclination Index: The Buy phase

Figure 3 Base: 8,451 respondents in the US, UK, Germany and Australia Source: Cognizant Research Familiarity with digital tools bolsters comfort with AI As in the Learn phase, AI index scores were higher for purchasing essential goods and small purchases than for larger purchases and luxury goods. This is partially attributable to the lower stakes of these smaller-value transactions. However, it also represents consumers’ comfort with using digital devices such as PCs and smartphones for purchasing. For most consumers, it’s a small jump from clicking “buy” on a smartphone to asking a voice assistant to handle the purchase—at least for lower-risk transactions. As the efficacy of AI increases, so too does consumer comfort. As one consumer noted, “A while ago, I wouldn't have trusted it in any buying process. Now, with the recent improvements, perhaps I would trust it in minor purchases.” Older consumers once again lead in AI tool comfort Technology comfort is especially high for the 25- to 34-year-old cohort, with a score of 37. <a href="https://theharrispoll.com/briefs/gen-z-shopping-study-findings/" target="_blank" rel="noopener noreferrer">According to recent studies</a>, this age group includes the most digitally savvy online shoppers, with over a quarter saying they leverage digital technology while shopping online. However, comfort with using AI tools for essentials and small purchases once again tilted higher with the older cohorts. Consumers over the age of 35 had AI tool comfort scores ranging from 33 to 42, compared with a range of 23 to 34 for younger consumers. This reflects a greater ability to see clear use cases for AI among older consumers. As one consumer in this age category noted, “I’m open to AI assisting with purchases, especially if it makes the process smoother and more efficient.” Another noted AI could “save me time, help me make more informed decisions, and save me from making any sketchy purchases or losing out on a deal or sale.” Higher-income consumers are more willing to automate purchasing with AI Income matters here, too. According to the AI index, higher-income consumers are twice as likely to use AI to purchase consumer goods as low-income respondents, with the former scoring 24 vs. the latter’s 12. This dynamic is particularly pronounced for higher-cost and luxury purchases, while essential and small purchases saw a narrower gap between the income groups. This higher risk appetite at the purchase phase is partially attributable to the greater financial resilience that accompanies a higher income—those who can afford to take risks are more likely to do so. However, it is also possible that automating purchases to third parties is statistically more likely for wealthier consumers. Assistants, concierges and personal shoppers are all more prevalent among these consumers—and extending that to AI is a smaller gap to bridge. This segment of global consumption is as important one. Personal shopping and sourcing drives 15% of global luxury sales, <a href="https://www.telegraph.co.uk/fashion/shopping/inside-the-lucrative-personal-shopping-boom/">according to some sources</a>, in many cases going directly to manufacturers and suppliers to secure the best deals and products.

<h5>The Use phase: Consumers are (somewhat) reserved, for now</h5> <ul> <li>Conversational AI introduces opportunities for larger purchases </li> <li>Younger consumers will lead the charge in the Use phase </li> <li>Clear path for manufacturers to ride AI into new markets</li> </ul> AI inclination declines to 51 in the Use phase, well below the cross-industry average of 56. This bucks the trend seen in our cross-industry study, where comfort with AI rebounded from the Buy phase to the Use phase. This divergence could stem from consumers struggling to identify the value propositions possible in the post-sale stage, such as automated maintenance, real-time troubleshooting, personalized assistance with product usage issues and curated recommendations for relevant add-ons and services. While consumers showed some comfort with AI-driven repurchasing of consumables and everyday purchases, that interest dropped off for high-value and one-off purchases. As one consumer said, “While the convenience of AI repurchasing products and services is appealing, I have concerns about privacy and control over my purchases. Could it misinterpret my needs and send unwanted products?” As such, the Use phase highlights the opportunity and challenge for manufacturers hoping to expand their reach into new markets and to become more active in customer engagement. Consumers are generally keen when they see value; it’s time for product manufacturers to develop models that bring this directly to the end customer. Appliance manufacturers, for example, could embed AI-driven reordering capabilities for consumables such as recommended detergents, or even proactive maintenance services. Overcoming consumer wariness with practical product- and service-enhancing features will improve revenue streams and potentially carve out new after-market opportunities. Consumer goods manufacturing AI Inclination Index: The Use phase

Figure 4 Base: 8,451 respondents in the US, UK, Germany and Australia Source: Cognizant Research Conversational AI introduces opportunities for larger purchases Consumers are less likely to see the value of conversational AI in the Use phase for lower- value goods, such as everyday essentials, than for larger purchases. This represents another important value proposition for manufacturers. Consumers recognize that when things go wrong with expensive items, AI could offer a quick and effective route to help protect their investment. One consumer noted that combined with visual search, conversational AI could help them build, repair or highlight issues with complex or high-value products. Another argued that AI “can help me get the most value from a product or service without needing to read a manual or set of instructions or search for tutorials online,” which is time-consuming and doesn’t offer the ability to ask questions. So, while lower-value consumer products invite comfort with AI handling routine repurchases, manufacturers of higher-value products have ample opportunity to embed AI into products to both improve services and enhance the customer relationship after the sale. Younger consumers will lead the charge in the Use phase The differences between AI comfort scores by age group are especially stark in the Use phase, with the 25–34 age group posting the highest scores, and the 35–44 the lowest. This suggests younger consumers will lead the charge on AI adoption in the Use phase. One of the strongest use cases for some products is AI helping to resolve issues and support repairs. This “fix, don’t replace” mindset dovetails with Gen Z and millennial consumers’ stated <a href="https://corporate.primark.com/en-gb/a/news/primark-cares/the-rise-of-regeneration-z-new-penneys-research-reveals-whats-behind-the-new-mend-it-mindset-in-ireland" target="_blank" rel="noopener noreferrer">desire for sustainability</a>. What these cohorts may lack in do-it-yourself repair experience could be augmented with personalized AI-enabled training for various products. Clear path for manufacturers to ride AI into new markets Traditionally, consumers have had little in the way of a relationship with consumer goods manufacturers. More often than not, their loyalty was with the retailers or other intermediaries, not the manufacturer itself. However, the combination of high prices, AI-enabled shopping tools and manufacturers’ ambition for larger markets is about to change that equation. One opportunity ripe for the taking is with the multibillion-dollar maintenance and service business. Not only is this in manufacturers’ wheelhouse (they know their products), but escalating product prices will likely change the consumer mindset from “replace” to “repair.” Currently, consumers are far more likely to replace a product like a smartphone, washing machine or TV than repair it—this is true for 60% of consumers, according to <a href="https://www.sciencedirect.com/science/article/pii/S0921344922002919">one recent study</a>. And even when they were open to repair, the product had to be broken, not simply malfunctioning. But those economics are overdue for a course correction. As price-sensitive consumers hang on to durable goods longer, those goods will be more apt to require repair. Further, as the designers and producers of these goods, manufacturers can embed AI capabilities into their products to enable more proactive, efficient and user-friendly service models. For example, Sony India has launched a multilingual voice AI agent to handle service requests, respond to customer inquiries and provide maintenance support for its televisions. Sony says the system greatly decreases customer wait times while increasing the accuracy and relevance of support.

<h4>AI agents usher in the consumer purchasing era for manufacturers</h4> AI stands to redraw the boundaries of the manufacturer-consumer relationship, opening up new markets and opportunities. As consumer AI uptake could be relatively fast in consumer goods manufacturing, we believe leaders have less than five years to navigate this change. To prepare for the AI-driven consumer era ahead, manufacturers will need to make changes and reconsider several factors: Deploy AI agents that work on the customer’s behalf As manufacturers pursue a customer-centric approach to product marketing, sales and post-sales service, it will alter the traditional intermediary path. Retailers and other third parties have traditionally functioned as a bidirectional interface between manufacturers and customers. This involved promoting the manufacturer’s product while supporting customers’ decision-making and transactional processes.  Going forward, AI agents will take on functions traditionally performed by intermediaries, such as curating product lists based on pricing, quality and availability and aligning products with consumer values. Use AI agents to shape the brand With the deployment of intelligent decision-making agents, combined with smart manufacturing, consumer goods manufacturers are positioned to expand their market reach. While this new posture enables direct customer interaction, it also raises expectations for manufacturers’ customer-facing efforts. AI agents must do more than drive efficient back-end operational processes; they also need to support customers in performing product evaluations and comparisons. This support will not only help drive sales and customer satisfaction but will define the brand for the consumer. Make it personal Not too long ago, the level of AI-enabled personalization possible today was unimaginable. Going forward, personalized rewards based on preferences, behavior and purchase history will be standard fare; one-size-fits-all reward systems are fast becoming obsolete. Personalized rewards and incentives can include invitations to early product rollouts and personalized discounts. These perks can be dynamically adjusted based on individual engagement patterns, then delivered via voice, web, mobile, email and apps. Combined with leveraging empathy capabilities in AI, manufacturers can develop an emotional and durable connection with their customers. Use audience segmentation to capture customers’ attention Manufacturers will be expected to use generative AI to produce content for various customer segments. As our research has demonstrated, younger consumers are eager to use technology, while older consumers seek the conveniences AI could offer. Manufacturers will need to be sensitive to pricing and messaging to these consumers as well as those from different income bands. For high-income customers, messaging might highlight exclusivity, premium features or luxury experiences; for other segments it can emphasize value, practicality or accessibility—all without making any group feel overlooked. Use AI agents to turn costs into revenue One of the most immediate opportunities for manufacturers is to increase their post-sales presence with customers. This means resolving issues quickly, offering relevant solutions and using every interaction to reinforce the brand’s standards and values. It’s also a revenue opportunity. First, good customer service drives continued business. Further, AI is transforming maintenance and service from reactive cost centers into proactive loyalty systems. By analyzing real-time product usage patterns and data, manufacturers can anticipate issues before they happen and then use this data to schedule maintenance and upgrades. Adapt business operations to dynamic market demands As consumer AI adoption accelerates, consumer goods manufacturers will encounter new opportunities and challenges across their entire value chain. Consumers are embracing AI-powered tools for product research, comparison and purchasing. This heightened engagement means consumer-goods brands must ensure their AI agents provide seamless, personalized experiences that foster loyalty and differentiation. Organizations should clearly establish their consumer engagement strategies and determine the appropriate operating models. Depending on the market, this may involve direct-to-consumer engagement or collaboration with partners and retailers to facilitate more effective responses to consumers and their agents. As consumers leverage AI to comparison-shop and seek out best-value options, consumer goods companies will need to be more agile in their pricing strategies. AI-enabled competitive intelligence will help them monitor market trends and competitor moves, allowing for swift pricing adjustments that maintain competitiveness without sacrificing brand equity.