Goldman Sachs launches "The Most Important Trade of 2026": AI Productivity Beneficiary Portfolio

Three years have passed since the release of ChatGPT, and enterprise AI applications are moving from concept to reality. Goldman Sachs believes that going long on a portfolio of beneficiaries from AI productivity will be the most important trading opportunity in 2026.

Goldman Sachs has recently launched a new portfolio that includes several non-tech companies, with the new investment portfolio code being GSXUPROD. The constituent stocks cover industries such as finance, retail, logistics, healthcare, and dining, and these companies have clearly integrated AI into their workflows to reduce costs and improve profit margins.

In this earnings season, many S&P 500 constituent companies specifically mentioned their use of AI in terms of productivity and efficiency during conference calls. The latest survey by Goldman Sachs investment bankers shows that the corporate AI adoption rate has reached 37%, while according to the U.S. Census Bureau, the AI adoption rate among large enterprises is 13%, despite the latter using stricter definitional standards.

This portfolio has underperformed the market so far this year, even when excluding the Magnificent Seven (Mag7). However, the framework analysis by Goldman Sachs' equity portfolio strategy team shows that the GSXUPROD portfolio has a potential for earnings per share changes driven by AI adoption and labor productivity improvements that exceeds that of the Russell 1000 Index and the S&P 500 Index.

Here is the complete list of AI beneficiaries:

Banks and Insurance: Automation and Cost Control Go Hand in Hand

Financial institutions are deploying AI on a large scale to enhance operational efficiency, with key application areas including coding, institutional services, fraud detection, credit, collections, marketing, and underwriting. These companies are automating daily tasks and enhancing customer interactions through AI platforms and virtual assistants. Many financial institutions view AI as a tool to augment human capabilities rather than replace them, supporting employees' work while reducing costs. Some companies are piloting agent AI for broader integration and controlling employee headcount growth.

JP Morgan: Emphasizes that it had accumulated deep AI expertise before the generative AI boom and is currently using AI as a rationale for controlling headcount growth while maintaining cost discipline.

Bank of New York Mellon (BK): Launched a platform called "Eliza 2.0," with 117 AI solutions already in production, including agents for business leads, coding, payment processing, customer onboarding, and reconciliation, with over 100 digital employees working alongside staff.

Rocket Companies (RKT): The deployed AI agents have significantly improved operational efficiency, with pipeline manager agents sorting leads and increasing conversion rates, home purchase agreement review agents reducing processing time by 80%, and underwriting agents cutting task completion time from 4 hours to 15 minutes. AI has enabled team members to handle 63% more loans than two years ago Citigroup (C): Has embedded AI into operations, with nearly 180,000 employees using proprietary AI tools 7 million times, saving hours each day through automation, data analysis, and material creation.

Bank of America (BAC): Views AI as "augmented intelligence" to support employees, with its Erica platform handling 2 million customer interactions daily, expanding the number of questions it can answer from 210 to 700.

Morgan Stanley: Is implementing artificial intelligence across multiple use cases, including DevGen.AI for code modernization, Parable for data analysis and aggregation, and LeadIQ for AI-driven lead allocation to match clients with financial advisors, all aimed at enhancing productivity and efficiency across the firm.

UWM Holdings: UWM has launched the AI loan officer assistant Mia, which has made over 400,000 calls on behalf of mortgage brokers to help them reconnect with past clients for refinancing opportunities, completing over 14,000 loans with a response rate of 40%, exceeding the expected 10-15%.

Ally Financial: Launched its proprietary AI platform Ally.ai to 10,000 team members to help streamline tasks, automate daily work, and make more informed decisions as part of its cost control efforts.

Bread Financial (BFH): Has adopted a "fast follow" strategy, leveraging the experiences of early adopters and focusing on AI use cases that have the most significant business impact. The company has deployed over 200 learning models in areas such as credit, collections, marketing, and fraud prevention, and optimized over 100 processes through robotic process automation (RPA).

Citizens Financial Group: Is implementing AI-powered initiatives as part of its "Reimagining Banking" program, which accounts for about 50% of its strategy to improve operations and customer experience, with plans for technology investments over the next three years.

Truist Financial: Is integrating AI-driven technology into new branches for smarter customer interactions, using the AI-supported chat feature "Truist Assist," and implementing AI across the company.

In the insurance sector, AIG: Is deploying a generative AI solution called "AIG Assist" in underwriting and claims processes, enhancing data processing, shortening cycles, and improving decision-making capabilities through automated extraction and analysis of unstructured documents.

Neptune (NP): Operates as an AI-first company, with AI models supporting underwriting, quote conversion optimization, and renewal retention, achieving $2.5 million in revenue and $1.5 million in adjusted EBITDA with high efficiency.

Retail and Warehousing: Comprehensive Optimization from Frontend to Backend

Retailers and warehouse operators are deploying AI technology across multiple functional departments. At the client end, AI enhances user experience through personalized shopping experiences, intelligent search, and customer service assistants. In the supply chain, AI optimizes "best shipping location" logistics, forecasting, and inventory management. In terms of internal operations, AI automates financial, human resources, and technical processes, improving store efficiency through queue detection and shelf space control. Proprietary warehouse execution systems are achieving double-digit productivity improvements.

Amazon (AMZN): Has made significant investments in AI across various areas, including AWS AI services, custom chips, AI agents, and shopping assistants, such as AWS AI services (SageMaker, Bedrock), custom chips (Trainium chips), AI agents (AgentCore, Strands), and shopping assistants (Rufus).

Walmart (WMT): Is building four super agents in core operations: a customer-facing shopping and discovery assistant Sparky, an employee agent for scheduling and sales data, a vendor/seller/advertiser agent for managing onboarding and events, and a developer agent to accelerate innovation and product launches.

PSA: Is leveraging artificial intelligence to directly provide customer service and optimize property staffing, reducing labor hours by over 30% while improving employee engagement and lowering turnover rates.

Lineage: Its proprietary warehouse execution system LinOS has been deployed at seven regular sites, achieving double-digit productivity improvements in key metrics such as units per hour, translating into higher output and lower unit costs. The company expects to complete 10 deployments by the end of the year and plans to accelerate promotion by 2026.

Best Buy (BBY): Is utilizing artificial intelligence in multiple areas, including AI-enhanced laptops with Copilot+ features, collaboration with Meta AI glasses, AI-driven search technology for its marketplace, and AI-centered advertising campaigns.

Target (TGT): Has deployed over 10,000 AI licenses within its teams, using AI and other tools to build and update forecasts more accurately while reducing the time taken to create forecasts.

Lowe's (LOW): Is leveraging artificial intelligence in two key applications: the MyLowe's Companion app, which helps employees support customers across departments; and FBM's AI blueprint extraction technology, which automatically extracts material quantities and dimensions from digital construction plans.

Home Depot (HD): Is using AI and machine learning to optimize "shipping from the best location" technology, determining the best delivery modes to maximize speed and efficiency, and improving search functionality on digital platforms.

Williams-Sonoma (WSM): Is implementing AI in three key areas: enhancing customer experience through AI-driven customer service assistants and digital design tools, optimizing the supply chain through end-to-end forecasting and inventory management, and achieving internal operational automation in finance, human resources, and technology, resulting in measurable productivity gains and cost savings Wayfair (W): Utilizing artificial intelligence across three strategic pillars: reshaping the customer journey through personalized shopping experiences, enhancing operations through automated processes, and driving its platform ecosystem with enhanced vendor tools and search optimization.

Tractor Supply (TSCO): Implementing artificial intelligence in three areas: enterprise software (including AI modules provided by vendors), custom applications (such as GURA and Tractor Vision), and automated agents integrated with OpenAI (with over 1,500 users).

DRVN: Take 5 is testing AI-driven camera technology that can detect queue issues in real-time, helping managers adjust staffing and workflows to move more vehicles and serve more customers more effectively.

Transportation and Logistics: Automation Processes Enhance Efficiency

The transportation and logistics industry is applying AI technology to significantly improve productivity and reduce costs. Key applications include automated loading, quoting, call handling, scheduling and booking, as well as intelligent digital twin systems, real-time route optimization, and predictive customer experiences. AI also supports automation in carrier check calls, invoice payments, quote generation, as well as agent-assisted tools, customer retention analysis, cybersecurity, and sales content creation.

United Parcel Service (UPS): Utilizing AI in two main applications: next-generation brokerage capabilities that digitize over 90% of cross-border transactions using AI, and integrating Agentic AI into customs brokerage operations to streamline formal entry processes.

XPO: Implementing AI in five key areas: two for revenue generation (AI pricing bots and sales assistance tools), and three for cost savings (trunk optimization, pickup/delivery route optimization, and dock efficiency). Its AI capabilities include reducing empty miles by 12%, cutting rerouting by 80%, and improving overall productivity by 2.5 percentage points in the third quarter.

FedEx (FDX): Leveraging AI to create intelligent digital twin systems that predict disruptions, provide real-time route optimization, and deliver predictive customer experiences, supported by daily data from 17 million packages amounting to 2 petabytes.

ArcBest (RCB): Implementing artificial intelligence to enhance productivity, streamline operations, and reduce costs through automated processes, including AI-enhanced full truckload quoting, automating loading, quoting, and email responses, as well as inbound call automation and scheduling/booking automation.

J.B. Hunt (JBHT): Has deployed 50 AI agents in its operations to automate tasks and streamline operations, achieving significant automation milestones, including 60% automation of carrier check calls, 73% automatic acceptance of orders, 80% automation of invoice payments, 2 million automated quotes annually, and over 100,000 hours of automation annually across highways, dedicated, and CE teams Landstar (LSTR): Is actively implementing artificial intelligence solutions covering three key areas: customer service automation, agent assistance tools (such as suggested pricing), and BCO retention analysis to predict driver turnover signals, while also investing in AI infrastructure projects to drive revenue growth.

Old Dominion (ODFL): Uses artificial intelligence in multiple operational areas, including cybersecurity email protection, trunk transportation planning for load optimization, safety guidance through Lytx camera video analysis, billing automation, sales content creation, and application development, with future research focusing on equipment utilization, predictive maintenance, mechanic training, and weather route optimization.

Ryder (R): Is deploying intelligent AI technology to enhance service levels and efficiency in its transportation management and brokerage business, particularly in optimizing customer rates, improving service levels, and enhancing freight bill auditing and payment activities in supply chain, fleet management, and dedicated business units.

RXO: Has been leveraging proprietary data for years to develop artificial intelligence and machine learning capabilities, implementing intelligent AI solutions to streamline carrier inquiries, deploying AI image solutions for last-mile delivery verification, implementing AI-driven pricing models, and utilizing AI tools for code generation, all aimed at increasing sales, profit margins, productivity, and service levels while freeing up employee time to provide solutions for customers.

SAIA: Has been investing in AI-based network optimization tools for years to improve operational efficiency, including route planning, urban operations management, staffing optimization, and trunk network design to reduce cargo handling steps.

Schneider National (SNDR): Is deploying Agentic AI across multiple business functions, achieving double-digit productivity improvements in logistics operations, with efficiency gains in certain areas reaching 50%-60%.

Werner Enterprises (WERN): Has implemented AI automation throughout its business operations, reducing back-office costs by 40% while maintaining service levels, with AI handling thousands of customer and driver interactions weekly through conversational AI and orchestration intelligent systems.

Uber: Is embedding generative artificial intelligence into its platform to enhance productivity, optimize operations, and provide personalized consumer experiences, while also launching Uber AI solutions to offer AI training work for global clients, including model training, voice audio response rating, video annotation, and query response evaluation.

Healthcare: Dual-Driven by Clinical and Administrative

Healthcare services utilize AI for patient stratification, care management, and improving diagnostic accuracy through AI tools designed by healthcare experts. AI plays a significant role in automating administrative tasks, including HIPAA-compliant medical record keeping and claims processing, as well as optimizing revenue cycle management to reduce denials. The overall goal is to enhance the affordability, accessibility, and personalization of healthcare services, improving the experience for patients and healthcare providers HCA Healthcare (HCA): Is implementing an AI program focused on revenue cycle management to combat payer denials and underpayments, while piloting environmental AI documentation tools to help physicians create more complete, accurate, and timely clinical documentation.

Elevance Health (ELV): Is deploying AI at scale to drive affordability, accessibility, and personalized care. By the end of the year, over 10 million members will have access to AI-supported virtual assistants, with AI embedded in clinical workflows, customer service, provider platforms, and administrative processes to enhance efficiency, reduce costs, and improve member and provider experiences.

Doximity (DOCS): The AI suite includes DoxGPT, which integrates drug references and provides instant peer-reviewed answers, AI Scribe for HIPAA-compliant environmental notes (with user growth doubling in Q2), and AI-optimized integrated programs (accounting for 40% of bookings, up from 5% last year).

Alignment Healthcare (ALHC): Uses AVA AI for clinical stratification and care management, with a centralized data architecture providing cross-functional visibility to execute star rating metrics and effectively manage Medicare Advantage risk.

HealthEquity (HQY): Is leveraging AI technology for claims automation, service center operations, and enhancing member experience, using AI for automated adjudication to speed up claims processing, reduce costs, and improve efficiency.

Restaurant Industry: Operational Automation and Workforce Optimization

The restaurant industry is actively integrating AI, primarily for automating ordering processes, especially in drive-thru restaurants, and enhancing overall operational efficiency. Restaurant-specific AI tools improve throughput, accuracy, and consistency, significantly saving labor costs and reducing cost of goods sold. AI also provides data-driven operational optimization recommendations for store managers and is used by developers to improve code quality and productivity.

Yum Brands (YUM): Is implementing AI Byte Coach to provide AI recommendations to store managers, deployed in over 28,000 restaurants, with plans to enhance personalized guidance using operational, consumer feedback, and audit data. One-third of developers use AI development tools to boost productivity, with plans to expand to nearly all Byte software developers by early 2026. Voice AI is being implemented in Taco Bell drive-thrus, showing a 14% increase compared to the previous quarter.

Sweetgreen (SG): Infinite Kitchen is an advanced food automation technology developed by Spyce, providing faster throughput, improved accuracy and consistency, enhanced food quality, approximately 700 basis points of labor savings, and nearly 100 basis points of sales cost improvement compared to similar restaurants.

Chipotle (CMG): Continues to invest in backend automation, with Chippy automating the chip frying process (capable of continuously cooking chips throughout the day, helping to alleviate labor pressure), and the latest version of the automated digital production line includes Autocado, which can cut, pit, and peel avocados The updated automated digital production line will be rolled out to the first restaurant in the second half of 2024.

SHAKE SHACK: The self-service ordering machine has become the largest and most profitable ordering channel for SHAK, with an average order value nearly 10% higher than traditional in-store ordering. This is attributed to recent digital enhancements to the user experience, and the company plans to optimize the self-service ordering machine experience in the future to promote limited-time offers and premium products, with a navigation system update planned for late 2025.

Starbucks (SBUX): In addition to a strong mobile ordering and payment platform, it is highly focused on improving operational throughput by launching the Siren System. This system integrates ice dispensers, milk dispensers, and blenders in an easily accessible location, alleviating congestion for baristas and improving customer wait times. Stores using the updated Siren Craft System are estimated to contribute 1% to same-store sales from increased peak throughput.

Wendy's (WEN): FreshAi is Wendy's automated ordering technology used for drive-thru operations to provide more consistent, high-quality interactions while improving upselling and productivity