Making a purchase involves a multistage journey. Consumers think about their needs and desires, consider various options, research and compare them, and then make their selection, after which they might enter into an ongoing relationship with the seller, as well as post a review or share word of mouth about what they bought. Every single stage in this journey is being influenced and altered, in notable ways, by artificial intelligence (AI). By reviewing those impacts, we might gain a clearer sense of marketers’ efforts to influence the purchase process, both today and for the future. 

Let’s start with the concept of brand discovery. Consumers who have determined an unmet need—let’s say they have decided they really want or require a new geegaw, for illustrative purposes—have to start their search for the best geegaw somewhere. It is up to brand marketers to make themselves known to these consumers, so that they can begin to convince them that their geegaw is the best option. To assist them in that effort, a new industry of AI-enabled services promises to show their clients how to define and establish their own brand identity, in a way that is most likely to reach and appeal to intended audiences.

For example, GoDomainers gathers and analyzes as much information about its small business clients as it can, then recommends which domain names and URLs they should invest in to link with their products. It seeks domain names that are closely associated with the product, relatively easy to memorize, but distinctive enough to spark some interest or intrigue in shoppers. For a seller of geegaws, it might recommend “geegaws-r-us.com” or maybe “gawgees.com.”

But just having a compelling website and domain name is unlikely to be sufficient, considering consumers’ fragmented paths to purchase, which often encompass social media, dedicated online marketplaces, and resellers, as well as physical retail channels. Therefore, another marketing development centers on how to build conversational AI that can function like friends who offer purchase recommendations. Unlike the sometimes random preferences of friends though, these recommendations are backed by extensive, in-depth, evidentiary data analyses.  

In a partnership with NVIDIA, L’Oréal is developing a proprietary, brand-specific, generative AI assistant called Noli that can enter into conversations with consumers. The consumer goods company will provide the technology firm with images and detailed ingredient profiles of its products, along with other relevant details. Then Noli will leverage these details to develop personalized product recommendations. The careful programming being applied to establish Noli ensures that the tool is likeable, polite, and personable. In addition, by feeding the algorithm information about thousands of product ingredients and more than a million facial scans, the partners seek to ensure it is accurate and helpful too. 

Going beyond any single brand, the AI-enabled Alta personal shopper promises to receive users’ unique product specifications (say, for a particular type of geegaw), search for viable options, and then present the results, displayed on a digital avatar that mimics users’ own proportions and appearance. The company recently raised more than $10 million in seed capital, and it has attracted intense interest from the luxury conglomerate LVMH. 

Outlining these sorts of implications of AI adoption for digital marketing might seem predictable. But the effects are not limited to digital channels. When it comes to consumers whose purchase journeys include visits to physical retail locations, AI-supported cameras and sensors can establish advanced analytics and insights. A company called Displayforce.ai promises to keep track of foot traffic in stores at any given time, detailing where in the store shoppers seem to gravitate. Do they spend more time checking out geegaws near the entrance, or does a display closer to the back of the store attract more attention, for example? Combining such information with customer segmentation data, Displayforce.ai can establish sophisticated, detailed predictive forecasts, in real-time, which stores can use to adjust their in-store marketing. In particular, they can adjust their digital displays to display geegaws in the most effective ways, tailored to inform, attract, and entice nearby shoppers. 

In parallel with the implications for the customer journey, AI applications in both digital and physical settings also enhance marketers’ ability to manage their employees. Algorithms can measure how well customer service employees respond to customers’ requests and questions, as well as how effectively sales associates interact with shoppers. Is one particular sales associate really good at engaging shoppers? Does another make sure to restock geegaws at the moment they disappear from the shelf or address customer complains especially efficiently? By offering answers to such questions, AI tools can improve in-store and online staff management too.

Assuming they do so well, and the customer finds just the geegaw they want and completes the purchase, good marketers still cannot consider the journey complete. Rather, they want to find ways to encourage repurchases and loyalty. One popular means to do so relies on reward or loyalty programs, another field in which AI has made some remarkable contributions. At Starbucks, the Deep Brew system records a massive range of specific data points, including purchase histories, seasonal trends, and foot traffic at specific locations, then calculates which incentives, offered to which consumer, on which day and at what time, is most likely to drive further purchases.

Nor are these efforts limited to consumer markets. In agricultural sectors, an AI-enabled loyalty scheme called GROWERS helps farmers record, keep track of, and analyze repeat business transactions. On the basis of the compiled performance statistics, it creates real-time forecasts of purchasing trends and inventory management, then suggests personalized incentives for repeat clients, according to their unique characteristics, needs, and purchase history.

Across all these stages, caution remains necessary. Artificial intelligence is not the only option for effective marketing, nor should it be used without supervision. Algorithms represent remarkable and valuable tools, but they also are fallible. Their functionality and appropriateness depend on their access to extensive, accurate data, as well as the integration of clear, actionable, ethical goals. The potential for unscrupulous brands to target vulnerable consumers, produce misleading and unsupported claims, and exploit biases also increases with powerful AI capabilities. 

Such potential threats highlight the need for marketers to act responsibly and ethically when leveraging AI to facilitate their customers’ purchase journeys, whether they are seeking geegaws or something much more important to their lives. That responsibility is even more pressing considering evidence of how rapidly people already are adapting to and integrating AI tools into their own purchase considerations. In one recent survey, more than one-third of respondents noted that they regarded AI like a friend sometimes. Another study found that one-third of customers already feel comfortable using AI-enabled products to interact with brands, and nearly three-quarters of them expressed interest in using AI solutions for various elements of their consumption, such as customer service. 

Discussion Questions

1. Do AI tools represent effective supplements to traditional marketing tactics? Or are they likely to replace them? 
2. Are certain seller or retailing segments better suited to integrating AI technology?
3. Do you trust artificial intelligence to aid with your shopping decisions?

Sources: Jill Standish, “Generative AI Rewriting the Rules of Retail,” Forbes, June 6, 2025; “GoDomainers Introduces AI-Powered Domain Recommendation Engine for Smarter, Brandable Name Discovery,” Financial Content, September 9, 2025; Peter Allen Clark, “One-Third of US Adults Use AI Agents for Discovery,” EMARKETER, September 10, 2025; Jill Standish, “How Retailers Win Hearts, Wallets and the Algorithm,” Forbes, July 16, 2025; “L’Oréal Teams With NVIDIA to Power the Future of Beauty Through Next-Gen AI,” Global Cosmetics News, June 12, 2025; Jessica Kwon, “AI Personal Shopping Tool Alta Raises $11 Million,” The Business ofFashion, June 16, 2025; Blake Kelley, “Digital Signage Performance Marketing Is Now Easy: Meet Displayforce Box With Video Analytics and Targeted Advertisement,” DPAA Global, October 5, 2021; Kevin Rozario, “How ‘Minority Report’ Gave Birth to DISPL, an AI-Led In-Store Retail Media Platform,” Forbes, June 20, 2025; Michael Brady, “Will AI ‘Completely Rewire’ Loyalty Programs?,” Marketing Dive, July 2, 2025; Business Wire, “GROWERS Revolutionizes Agriculture Loyalty Program Through Use of AI,” Yahoo! Finance, January 30, 2025.