Fortune 1000 enterprises across industries are embracing generative AI (e.g. large language models like GPT-4) to enhance employee productivity, improve customer service, and streamline operations with partners. In 2025, many well-known U.S. companies have launched pilots or full-scale projects using generative AI to empower their workforce, engage consumers in new ways, and optimize supply chains. Below we explore how big businesses in retail, finance, consumer goods, and industry are leveraging generative AI in real-world initiatives.
Retail & E-Commerce: Personalized Service and Employee Assistants
- Walmart: The nation’s largest retailer unveiled a strategy to use generative AI for “profoundly personal experiences” in shopping[1]. Walmart developed its own retail-tuned large language models (“Wallaby”) and launched a new AI Customer Care Chatbot that recognizes customers and can take actions like finding orders or processing returns[2]. In testing, this personalized support assistant made self-service smoother for customers. Walmart is also “actively building dozens of GenAI tools for customers, members, associates and partners” across the enterprise[2]. These include internal tools for employees and enhanced AI assistants for Sam’s Club members and international markets, aiming to empower store associates and improve customer experiences at scale.
- Lowe’s: The home improvement giant (a Fortune 50 retailer) launched Mylow Companion, an AI assistant rolled out to 1,700+ stores in 2025, marking the first at-scale generative AI deployment for retail associates[3][4]. Mylow Companion provides store employees with instant access to product details, project how-to advice, and real-time inventory data on their handheld devices. This generative AI tool “elevates the know-how of staff” – even a new hire can confidently answer complex DIY questions (e.g. “How can I fix a leaky faucet?”) with expert-level guidance[5][4]. Built in collaboration with OpenAI and grounded in Lowe’s 100 years of home improvement expertise, Mylow Companion has improved customer service and sped up onboarding of associates. Lowe’s also offers Mylow, a customer-facing virtual home improvement advisor on Lowes.com that uses the same AI foundation to give shoppers project guidance and product recommendations[6]. Together, these tools democratize expertise for customers and employees alike, merging Lowe’s industry know-how with advanced AI capabilities.
- Ralph Lauren: In high-end retail, fashion brand Ralph Lauren debuted an AI stylist chatbot called “Ask Ralph” in late 2025[7]. This Azure OpenAI-powered assistant engages customers in a personal, conversational shopping experience. Shoppers can input natural language prompts (e.g. “What should I wear to a concert?” or “How do I style a navy blazer?”), and Ask Ralph will analyze the query and recommend complete outfits pulled from current Ralph Lauren inventory[8][9]. The chatbot acts like a virtual personal stylist, offering visual outfit suggestions and styling tips similar to an in-store associate but available 24/7. Customers can even follow up with clarifying questions and seamlessly add recommended items to their cart[10]. This generative AI project – developed with Microsoft’s help – aims to boost customer engagement by blending the luxury brand’s expertise with interactive, AI-driven personalization.
(Note: Other retailers are also piloting generative AI. For example, fast-food chain Wendy’s tested an AI chatbot for drive-thru ordering, and apparel retailer Levi’s experimented with AI-generated fashion models. These illustrate a broader retail trend of using GenAI to enhance customer service and marketing, though our focus here is on Fortune 1000 companies with notable 2025 projects.)
Financial Services: AI Advisors and Process Automation
- Morgan Stanley: This leading wealth management firm partnered with OpenAI to create an internal AI assistant for financial advisors. In September 2023, Morgan Stanley rolled out a GPT-4 powered chatbot (called the AI@MS Assistant, “AIMS”) to ~16,000 financial advisors, allowing them to query the bank’s vast research vault and get answers for clients within seconds[11]. Instead of telling clients “I’ll research and get back to you,” advisors can now ask the AI during a call and retrieve information almost instantly[12]. By early 2024, 98.5% of Morgan Stanley’s advisor teams had adopted the tool (at least one member using it weekly)[11]. The chatbot is tuned to reference only approved internal content (to avoid errors or off-topic answers) and excels at tasks like summarizing market research, comparing investment options, or explaining complex financial strategies. This has freed up advisors’ time to be “more human” – spending more time on client interactions and less on paperwork and manual searches[13][14]. Buoyed by this success, Morgan Stanley promoted its wealth tech head to lead AI efforts firmwide and is expanding generative AI projects across other divisions[11].
- JPMorgan Chase: The largest U.S. bank is likewise making a sweeping push into generative AI to boost efficiency. In 2024 it announced the rollout of a custom AI assistant (internally called “LLM Suite”) to 140,000 employees across the company[15]. JPMorgan expects this broad deployment to yield up to $2 billion in productivity gains by automating workflows and speeding up decision-making[16][17]. The AI assistant will help employees in many roles – from front-office bankers to back-office operations – by “optimizing operational services and every single process using AI and large language models,” according to the COO[17]. For example, generative AI can assist with fraud detection (a major benefit cited by JPMorgan), draft reports or code, answer employees’ IT or HR questions, and more. Alongside this, JPMorgan has been training its workforce in AI and ensuring data security as it modernizes its tech infrastructure[18][19]. Other banks are following suit: Capital One is leveraging its cloud foundation to scale AI, Bank of America invested $3.8B in new tech (with an eye on “data hygiene” for AI), and Discover is taking a measured approach with employee training and guardrails for generative AI[20]. Across the finance industry, generative AI is being embraced to augment employees – helping them sift through research, write code or reports, handle customer inquiries, and ultimately serve clients faster and more accurately.
Note: Investment firms are also using GenAI for specialized tasks. For instance, JPMorgan’s analysts built an in-house ChatGPT-like tool as an AI research analyst to scan market data
Consumer Goods & Food/Beverage: Innovation in R&D, Marketing and Supply Chains
- Coca-Cola: The beverage giant is using generative AI both for solving business challenges and for creative endeavors. In 2025 Coca-Cola became a founding member of MIT’s Generative AI Impact Consortium, a group of businesses and researchers applying AI to real-world problems[25]. The consortium’s first project “Save the Orange” leverages AI to combat citrus greening disease, which threatens the global orange supply crucial for Coca-Cola’s orange juice products[25]. This initiative unites Coke with agritech experts and even rivals (like Tata and SK Telecom) to develop AI solutions that can detect and manage the plant disease at scale. More broadly, Coca-Cola says “AI and other digital tech are transforming nearly every aspect” of its operations – from R&D and product development to marketing, inventory and supply chain[26]. The company has already used generative AI in advertising campaigns, and in 2023 it even released a limited-edition soda (“Y3000”) that Coca-Cola touted as the first flavor co-created by humans and AI[26]. In marketing, Coke ran a contest (“Create Real Magic”) inviting consumers to generate artwork with the DALL-E2 AI image model for its brand. These experiments illustrate how generative AI is helping Coca-Cola innovate products and engage customers, while also tackling supply challenges alongside partners.
- PepsiCo: As Coca-Cola’s industry peer, PepsiCo has likewise invested in generative AI to drive efficiency and personalization. PepsiCo built an internal genAI platform called “PepGenX”, and in 2025 it announced a major cloud partnership with AWS to enhance this platform[27]. By integrating PepGenX with Amazon’s Bedrock (which offers multiple foundation models), PepsiCo gave its developers a choice of advanced AI models and “agentic AI” tools to build various applications[28]. Use cases span from marketing to operations: For marketing teams, generative AI can provide real-time insights on ad performance, refine audience segmentation, and generate hyper-personalized content for campaigns[29]. (For example, PepsiCo’s snack brand teams could use AI to suggest new flavor ideas or craft tailored promotions for different demographics.) In operations and supply chain, PepsiCo and AWS are exploring AI-driven predictive maintenance for manufacturing lines and route optimization in logistics[30]. By quickly analyzing sensor data from factories or delivery fleets, AI can foresee equipment issues or improve scheduling, boosting efficiency across PepsiCo’s global production network. This end-to-end approach – from consumer engagement to factory floor – shows how PepsiCo is weaving generative AI into its digital transformation, in close collaboration with a tech partner. As AWS’s CEO noted, PepsiCo is applying AI “across their organization” to deliver personalized experiences, optimize supply chains, and build new capabilities[31].
- Procter & Gamble (P&G): The world’s largest consumer packaged goods company (behind brands like Tide, Crest, and Pampers) views generative AI as a catalyst for innovation and teamwork. P&G has developed several proprietary generative AI platforms internally[32] and in 2024 it ran a large-scale experiment with 776 employees (from R&D and marketing teams) to quantify AI’s impact on productivity[33][34]. In this “live” study – done in collaboration with Harvard and Wharton researchers – some teams had access to GPT-4-based AI assistance (via Microsoft Azure) while others did the same task without AI[35][36]. The results were striking: teams using generative AI were ~12% faster in developing new product ideas than those without AI[37]. Moreover, AI-assisted groups produced more “balanced” cross-functional solutions, as the tool helped bridge knowledge gaps between, say, a marketer and a scientist[38]. P&G also observed a positive effect on employee morale – the AI served as a creative partner that boosted engagement during the brainstorming, rather than replacing human collaboration[39]. According to P&G’s Chief Innovation Officer, this validated that “AI is a game-changer for innovation…unlocking new ideas and accelerating our speed to innovation”[40]. Beyond this pilot, P&G is actively deploying generative AI in areas like consumer research, supply chain planning, and advertising. For instance, its marketers use AI to generate and test ad copy variations in days (versus weeks) at a fraction of the cost[41][42], and the company is exploring AI tools to assist in product design and formula optimization. All of this is aimed at helping P&G’s employees make better decisions faster, so the company can deliver new and improved products to customers more efficiently.
(Note: Other consumer goods firms are experimenting with generative AI. Rival Unilever has an AI design tool to automate creating marketing assets[[43]](https://consumergoods.com/pg-harvard-study-says-gen-ai-gets-cpg-teams-working-12-faster%23:~:text=,Design%20With%20AI%20Tool), and Kraft Heinz and Nestlé have tested GPT-style models for developing recipes and product ideas[[44]](https://www.supplychaindive.com/news/coca-cola-joins-ai-group-to-combat-orange-disease-other-real-world-probl/760013/%23:~:text=,pickle%20%20%20Food%20Dive). These indicate a broader trend of AI augmentation in product innovation and marketing across the sector.)
Industrial & Manufacturing: AI for Operations, Design and Support
- John Deere: An iconic manufacturer of farm and construction equipment, Deere & Co. is using generative AI to improve both customer and dealer support. John Deere leverages OpenAI’s APIs to assist its customer service teams, field dealers, internal operations staff, and even data scientists working on its products[45]. One practical example is an AI-powered technical assistant for mechanics: Deere’s dealer technicians historically spend hours poring over thousands of pages of equipment manuals and past repair records to diagnose issues. Now a generative AI tool can instantly parse those massive technical documents and output precise diagnostics, parts lists, and repair instructions to fix a machine[46]. This enables Deere’s dealer partners (and farmers who do self-repairs) to troubleshoot problems much faster, minimizing downtime for expensive combines and tractors. Deere’s advanced farming machines also generate huge amounts of sensor data in the field – here AI helps by providing real-time insights and recommendations to farmers. For instance, Deere’s See & Spray system (which uses computer vision to spot-spray weeds) is complemented by AI-driven advice: the farmer can ask a natural-language question about optimal settings or get a preseason recommendation on chemical use based on their past usage and weather forecasts[47][48]. If the system isn’t being utilized fully, the AI can alert the local dealer to reach out with guidance so the customer gets maximum benefit[49]. In short, Deere is weaving AI into every step of the customer lifecycle – from purchase and setup (answering “How do I use this feature?”), to in-season operation (data-driven tips), to maintenance and ROI reporting – scaling personalized support to thousands of customers with a relatively small support team[50][48]. This aggressive adoption of generative AI in a 180-year-old manufacturing firm underscores how even industrial sectors are using AI to be more responsive to customers and partners.
- General Motors: In the automotive industry, generative AI is enhancing both design processes and in-vehicle customer experiences. A notable example is GM’s addition of an AI virtual assistant to OnStar, its vehicle safety and concierge service. Working with Google, GM augmented OnStar with a conversational AI model that can better recognize a driver’s intent and respond naturally to voice commands[51]. This means drivers can ask their car for help (directions, vehicle diagnostics, scheduling service appointments, etc.) and get human-like, context-aware answers powered by generative language models, rather than rigid scripted responses. GM is also exploring generative AI in engineering – for instance, using AI-driven generative design software to optimize parts (lighter, stronger components devised by AI algorithms) and to simulate autonomous driving scenarios. According to industry surveys, about 75% of automakers plan to integrate generative AI into vehicles by 2024[52], whether for voice assistants, personalized infotainment, or even AI-generated marketing content for car sales. Luxury carmakers like Mercedes-Benz have introduced a “smart assistant” for drivers that uses a tuned LLM to enable conversational search of the vehicle’s features and navigation system[53]. These moves by GM and others illustrate how generative AI is helping transform the driving experience and the auto industry’s operations. From the factory floor (where AI can generate simulations to improve manufacturing processes) to the showroom, generative AI is becoming a tool for innovation, efficiency, and improved customer service.
- Manufacturing Design and Partner Collaboration: Beyond autos, manufacturers in aerospace, electronics, and other domains are adopting generative AI to assist employees and partners. For example, Boeing has experimented with generative design AI to craft airplane components that meet strict weight and strength criteria, reducing development time. Siemens Energy uses a ChatGPT-based assistant to help field engineers and clients troubleshoot turbine equipment by querying technical documentation in natural language. And UPS has used machine learning and AI tools (some generative) to analyze shipping data and assist its business customers with logistics planning[54]. These instances show that Fortune 1000 industrial firms are finding diverse ways to apply generative AI – whether it’s an employee-facing chatbot to improve technical support, a customer-facing feature to personalize services, or a back-end tool to optimize design and supply chain decisions.
Conclusion
From retail and finance to consumer goods and heavy industry, generative AI is becoming a key enabler for big businesses in 2025. Companies are launching pilots and full deployments that use AI’s generative and conversational abilities to support employees (e.g. answering questions, drafting content, writing code), to delight customers (e.g. personalized recommendations, AI chatbots, co-created products), and to strengthen partner relationships (e.g. supply chain forecasting, dealer support tools). Early results are promising – retailers report faster customer service and more personalization[2][5], banks see productivity gains and better fraud detection[17][55], and manufacturers achieve more efficient operations and enhanced customer uptime[46][51]. Executives emphasize that AI is not replacing humans but augmenting them: it “provides a powerful boost” to human creativity and decision-making, as P&G’s CIO put it[40], and can even free employees to spend more time on high-value “human” tasks[14].
That said, companies are proceeding thoughtfully – deploying AI tools internally in a pragmatic, secure manner (often with proprietary models or vetted cloud services) and training staff to use them effectively[19]. Many pilots remain in early stages, and firms are carefully evaluating outcomes (especially given reports that a majority of experimental AI projects have failed to deliver ROI so far[56][57]). Still, the rapid adoption by Fortune 1000 leaders suggests that generative AI’s capabilities – natural language understanding, content generation, and pattern analysis at scale – are being recognized as transformative. In the coming years, we can expect these pilot projects to expand and mature, turning generative AI into a ubiquitous co-pilot for employees, a personalized concierge for customers, and a smart collaborator for business partners across the corporate world.
Sources:
- OpenAI, “Lowe’s leverages AI to power home improvement retail,” May 5, 2025. [6][5]
- Lowe’s press release – Mylow Companion launch, May 13, 2025. [5][4]
- Walmart Inc., “Walmart Reveals Plan for Scaling AI, GenAI, AR…,” Oct. 9, 2024. [2][58]
- CIO Dive (TechTarget), “JPMorgan Chase to equip 140K workers with generative AI tool,” Sept. 11, 2024. [17][55]
- Business Insider, “Morgan Stanley is betting on AI to free up advisors’ time…,” Apr. 11, 2024. [11][12]
- Supply Chain Dive, “Coca-Cola aims to help solve orange supply crunch with AI,” Sept. 16, 2025. [25][26]
- PepsiCo Press Release, “PepsiCo and AWS collaborate to accelerate digital transformation,” May 7, 2025. [28][29]
- Consumer Goods Technology, “P&G, Harvard Study Says Gen AI Gets CPG Teams 12% Faster,” Apr. 4, 2025. [37][59]
- OpenAI, “AI helps John Deere transform agriculture,” 2025. [45][46]
- Google Cloud Blog, “601 real-world Gen AI use cases… (Google Cloud Next ’25),” Apr. 2025. [51][53]
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