Retail Holiday Newsletter
Successfully leading a retail business is getting harder—you’re not imagining it. The S&P Retail Index grew only 12% over the past three years, while the broader S&P rose 21%. The top 100 retailers had an average CEO turnover rate of 22% during the same period, up from 17% over the previous three years, according to our analysis of BoardEx data. Cycles are compressing, there’s no longer safety in scale alone, and iconic brands are going bankrupt.
But this environment will reward practical leaders who can turn volatility into advantage. We believe 2026 can be a year of extraordinary success, not just in sales and profits but also in building trust and momentum with the stakeholders who matter most: your customers, suppliers, strategic partners, investors, communities, and associates.
What follows are seven letters to the C-suite, distilling what we’ve learned from working alongside the best in retail and beyond. Each is focused on how to sharpen strategic clarity, elevate the contributions of new technologies, and achieve exceptional performance.
That said, the individualized format isn’t intended to suggest working in silos. Many leadership teams divide and conquer—and it’s a costly mistake. It slows decisions and fragments accountability. Typical resource attribution models don’t help.
By contrast, winning leadership teams don’t think of themselves as a group of individuals. Instead, they see the organization as a complex system more powerful than the sum of its parts. They operate in tight alignment with shared goals, then use cohesion as a competitive advantage. Consider how successful merchants partner with heads of stores and e-commerce to create brand-enhancing channels for their vendors, or how top technology leaders garner support from finance to invest in next-gen capabilities.
The very best leadership teams are doing something more: adding AI to the team in ways that expand the value-creation capacity of the entire organization.
Letter to the CEO
When Edgar Schein, a professor at MIT Sloan School of Management, asked students what it meant to “be promoted to manager,” they quickly and unanimously replied, “It means I can now tell others what to do.”
The best CEOs disagree. They understand that managing means unleashing the full potential of people, technologies, and other resources—putting them to higher and better uses than any competitor can.
In retail, the path to that full potential is shifting fast, with AI propelling much of the change. Third-party AI agents increasingly determine which retailers and products appear in the consideration set. Zero-click journeys are recasting online traffic and performance measurement. And consumers now get radical transparency on price, assortment, and speed in a single query. Internally, leaders are trying to decide where AI and automation can improve operations and where traditional, people-powered disciplines still matter most.
At this pace of change, it’s easy to let the next crisis set the agenda. The strongest leaders will stay anchored to a clear long-term direction, so reactive moves don’t undermine their strategy.
A winning strategy will get the best from both humans and machines. Humans still have ownership: They set purpose and values, envision the kind of organization they want to build, define what winning means, determine acceptable vs. off-limits trade-offs, and establish AI guardrails. From there, AI interrogates strategic choices. By analyzing outcomes, decision patterns, and environmental shifts, it can uncover drifts from strategy, inconsistencies, biases, threats, and opportunities. This creates a healthy loop: People constantly refine strategy and guardrails as AI delivers a sharper, more honest view. Done right, AI is neither an autopilot nor a neglected tool buried in the shed. It’s a serious partner that amplifies human insight yet is firmly constrained by human values.
Too often, however, AI is muddying strategy rather than strengthening it. Cost reduction comes at the expense of innovation, customer experience, and employee engagement. Seemingly bright ideas start to cloud strategic clarity as the business system loses coherence. People start to question: “Are we shifting from highest quality to lowest cost?” “Is talent truly our most valuable asset if thousands are being let go?” “Are AI predictions quietly pushing us into riskier bets?” When AI improves one element of strategy while quietly undermining others, teams start to make conflicting choices.
This is where you have a unique opportunity: to design a cohesive system that clarifies purpose and values, sets AI guidelines, and integrates people, technology, and capital in ways that ultimately create more value than ever before. Of course, this responsibility isn’t yours alone. It requires every senior leader and their teams to make day-to-day choices in concert.
A practical starting point is bringing functions together to answer a few hard questions: “Where will we be best in class or best in cost?” “How does that determine where we invest (whether building, buying, or outsourcing)?” Winners will strike the right balance. In some areas, they’ll streamline, doing work faster and cheaper to expand human capacity where it matters most. In others, they’ll differentiate, solving problems and creating experiences that deepen loyalty in ways that were unimaginable just years ago.
Meaningful results come from the C-suite collaborating on a few prioritized initiatives, rather than launching dozens of disparate ones. Sharp customer and employee value propositions are the best places for you to start. For customers, this means specific, defensible reasons to shop directly with you—not competitors or AI platforms—for each occasion, across channels. For employees, this means earning their trust by matching actions to promises, especially by deploying tech in ways that make work simpler and more rewarding.
Letter to the Chief Merchant
In many ways, the fundamentals of great merchandising haven’t changed. Your goal is to take what you believe your customers want and turn that insight into profitable results: sourcing and curating the right products at the right prices; getting them to the right places; and presenting them in ways that are intuitive, compelling, and relevant to your target customers.
Now, however, you’re navigating a sea of data, greater transparency, shorter planning cycles, and the ability to make dynamic changes, almost in real time. The challenge is harnessing all of this in a way that sharpens your team’s judgment and strengthens the customer value proposition, rather than fragmenting decisions.
The way consumers discover and buy products is changing. AI agents are increasingly shaping purchasing decisions, especially among younger shoppers. “Where you show up” now includes third-party platforms and agents, not just search rankings, social feeds, or endcaps.
Winning in this new agentic battleground will likely require evolving merchandising, with a focus on:
- clean, rich product data that AI agents can easily access and interpret;
- needs-based bundles tailored to natural-language queries that grow basket size;
- distinct and exclusive products, including private label, that boost discoverability;
- pricing and promotion logic that agents can surface accurately and contextually; and
- closed-loop feedback on shoppers’ prompts and purchase signals for your assortment decisions.
How shoppers choose products is also changing, given the now effortless, near-instant ability to compare. In most categories, best value for money—not lowest price—is the top purchase criterion, according to a recent Bain survey. Additionally, as brand loyalty continues to erode post-pandemic, private label has become a primary differentiator to signal value.
Here, too, AI gives your team a step-change advantage. It can pinpoint market opportunities quickly, synthesizing shopper insights and external signals. It can also accelerate own-brand development by simplifying specifications, running tenders, and managing cost pressure amid inflation.
AI is not only a customer-facing opportunity but also a functional one. AI can enable merchants to be both more efficient and more effective. We estimate your merchants can automate a large share of tasks—as much as 70% to 90% of administrative buying activities, for example—freeing them up to focus on high-value judgment calls, such as product innovation or customer experiences. And we’re already moving beyond dashboards toward prescriptive engines. Within five years, it’s plausible that activities like supplier negotiations will be largely automated, with humans approving only the most critical decisions.
Merchandising may offer the highest ROI for AI in retail, through sharper relevance, stronger differentiation, faster execution, and better buying. But AI shouldn’t be viewed as just a tool. It needs the surrounding data, improved merchandising processes, and well-trained merchants to be effective.
Letter to the CMO
Growth disproportionately fuels total shareholder returns (TSR), and marketing disproportionately fuels growth, often influencing 25% or more of revenue.
A key imperative for CMOs in 2026 is to amplify the customer value proposition more efficiently and convincingly than competitors. That starts with insight into what matters most to each of your customers. Then bring the message to life with relevant data, personalization, AI-enabled martech, and modern marketing teams, with more specialized expertise, integrated activities, and dynamic decision-making.
Retail marketing leaders will keep pulling ahead of the laggards. We define leaders as those gaining at least 7% market share in the previous year, or at least 4% share paired with at least 11% revenue growth. Laggards, by contrast, see shrinking share or grow less than 3% with flat revenue. The best:
- Reimagine strategy through an AI and generative search (GEO) lens. Leaders are four times more likely than laggards to view AI as a core capability and three times more likely to deploy it at scale. They also track GEO performance and use partnerships to navigate a fast-evolving landscape.
- Expand non-trade profit pools. For example, invest in a differentiated retail media network. The best not only monetize metadata but also use it to improve the in-store and online experiences.
- Personalize to elevate experiences. Leaders go beyond emails and promos with the aim of boosting customer lifetime value. They curate distinctive moments to delight customers and reduce detraction—think AI-enabled auto-replenishment or cultural moments like Spotify Wrapped.
- Modernize the operating model. Marketing leaders are hiring and nurturing agile, tech-savvy, and change-oriented team members. They’re also rethinking which capabilities to build in-house vs. with agencies. Many are finding efficiencies and reinvesting resources in strategic priorities—these CMOs are on the front foot when called upon to do more with less.
Marketing leaders vs. laggards
x
more likely to view AI as a core capability
x
more likely to deploy AI at scale
x
more likely to have consistent, structured experimentation
Three enablers support these priorities. First, there’s customer empathy and advocacy. It’s more than loyalty programs; it’s about capturing true voice-of-the-customer insight through measurement and closed feedback loops. Second, it’s important to establish a strong data and tech foundation, built through close CMO-CIO partnership. Third is a culture of testing and learning: Leaders are five times more likely to have consistent, structured experimentation.
Dedicating equal mindshare to the math and magic of marketing will help you fuel industry-leading growth and, subsequently, TSR.
Letter to the Head of Stores and Head of E-commerce
The best channel leaders prioritize deepening relationships with customers by meeting them where they shop for each occasion, across stores, online, and omnichannel. Here, we’re seeing top retailers double down on the moments of truth that can spur brand promoters—or create detractors.
In physical stores, you’re likely already evolving your store network based on relative local market share and productivity. But footprint alone is rarely the answer. A store visit is now a choice, not a given, raising the bar for the in-store experience. Bain research shows that 68% of customer detractions—when they wouldn’t recommend a retailer—stem from a negative experience. Conversely, great in-store experiences build trust and create a halo effect across other channels.
The best retailers are turning stores into destinations again through experience, layout, execution, availability, and service. They treat tech and talent as enablers, such as AI copilots that help frontline staff serve faster and better. About half of retailers expect their store technology investments to improve their bottom line by 1.5 percentage points or more.
More foot traffic also unlocks monetization opportunities, such as store-in-store partnerships and in-store retail media (RM). This is a timely objective: A Bain survey shows advertisers expect to allocate 20% of RM spending to in-store media by 2027, up from 7% in 2022.
E-commerce is hitting its next inflection point, becoming as critical as stores for many retailers. Leaders use digital to expand their catchment area. In categories including grocery and home improvement, convenience and speed can attract customers beyond traditional reach or serve new occasions. For example, Walmart+ extends the retailer’s reach with offerings including fast, unlimited delivery from store and at-home pickup for returns. In categories such as apparel or health and beauty, success hinges on inventory visibility and frictionless returns. Top retailers also connect digital and physical seamlessly—with pickup, ship-from-store, and easy returns—using omnichannel to extend their brand halo while improving store economics. Think of how Amazon uses online pickup and return counters, plus Prime promotions, to bring shoppers into Whole Foods stores.
Finally, agentic commerce is moving fast. By 2030, we expect it to account for 15% to 25% of the US e-commerce market, reaching up to $500 billion. Across channels, great agents elevate your unique value proposition. For instance, citing efficiency, service, and recommendations, 45% of users say they’d recommend Amazon’s Rufus, and 40% Walmart’s Sparky, per a Bain Consumer Lab survey.
Retailers that rethink their operations, experience, and profit pools across channels will be the ones that keep shoppers coming back throughout 2026.
The Global Consumer Lab
Develop a deeper understanding of your customers, beyond their shopping baskets.
Letter to the CHRO
You’re focused on attracting, onboarding, and developing the best talent to deliver great customer experiences. At the same time, the company needs your help in protecting what makes retail work human and building and maintaining employee trust in the organization.
Yes, new technologies can enable significant productivity and efficiency gains throughout the business. But the real opportunity is reinvesting those gains in the workforce as a competitive advantage. Ask 100 customers, and they’ll tell you the same thing: When they can’t reach a human employee, it’s more than a one-off frustrating experience. It affects whether or not they ever come back.
Start with a clear view of which tasks must be performed by humans and which can shift to AI, automation, or robotics. This isn’t just about technological feasibility. It’s about where empathy and judgment matter. For example, in the near future, you might be able to shift some back-of-house duties to automation and humanoid robots, but you’ll want to keep people front-of-house to help customers and add a personal touch. Then, reimagine how that mix evolves over the next three to five years. You’ll own and enable this strategy, but it doesn’t fall to you alone. Your COO, CIO, and head of stores will be critical partners.
Next, explore how AI can enhance every role. On its own, giving copilots to frontline associates or AI assistants to merchandisers won’t move the needle. It takes redesigning processes and expectations so teams know how to work differently. Then, reinvest productivity gains into serving customers exceptionally well. With more digital tools, data, and time, frontline employees can move from “good enough” interactions to surprise-and-delight moments that bolster loyalty and sales.
Finally, winners will make retail the best place to work for frontline and corporate teams. Here’s the reality: We expect US labor supply to grow only 4% by 2050, down from an average of 19% over the past 25 years. Other countries will dip further into negative territory: Germany to –16% (from –6%), China to –23% (from 14%), and Japan to –25% (from –16%). As the labor pool stagnates, engagement and retention will matter more than ever. Think smarter scheduling, better coaching, and technology that make jobs easier. Upskilling, in particular, will be key to closing the talent gap and strengthening the employee value proposition. For example, facing a shortage of skilled tradespeople, Walmart is upskilling associates into in-house refrigeration, HVAC, and facilities-maintenance technicians, creating a path to better pay and future opportunities.
A concrete people-plus-tech roadmap for 2026 and beyond is more than a strategic edge. It’s a chance to improve the lives you touch, from the back office to the customer.
Letter to CIOs, CTOs, and CDOs
Your peers continue to lengthen the list of tech solutions for you to build for them. Your board has been asking: “Are we investing enough in the right places? Are we moving fast enough on AI and agentic commerce?” while pushing finance to radically reduce costs. Four themes can help you accelerate progress in 2026.
First, your data foundation enables—or constrains—everything you do. It affects how organizations uncover critical business insights, make fast decisions, and get the most out of AI. You don’t need perfection, but you do need a consistent version of the truth on customers, locations, items, and suppliers. That doesn’t mean having a single repository, but logically stitching together data across functions to power real-time decisions. You can’t fix everything at once. Those that succeed will start where value is highest.
Second, make decisions around agentic design and architecture. What agents will you build vs. buy or partner for? How will they connect? It helps to define a taxonomy and hierarchy of agents: customer-facing, internal, and “headless” agent-to-agent workflows. Then, sequence them in a roadmap with clear prioritization based on their value, interdependencies, and interactions. Leaders will avoid the pitfall of building dozens of stand-alone agents that fragment the enterprise.
Third, rethink your tech investment model. According to Gartner, more than 70% of tech spending goes to keeping the lights on (KTLO), while subscription software and cloud costs keep rising. The strategic imperative is to bend the run-cost curve. That takes big, multiyear moves to reduce KTLO through AI and automation, rather than chasing nickels and dimes to satisfy annual budgets. Then, you can reinvest freed-up funds into the next wave of AI and tech priorities.
Senior tech leaders
%
cite insufficient talent or skills as one of the biggest obstacles to scaling AI
Finally, all of this implies a rapidly evolving talent model. Today, 64% of senior tech leaders cite insufficient talent or skills as one of the biggest obstacles to scaling AI. Overcoming that means hiring for new skills while also retooling and retraining your people. Return on AI investment hinges on employee adoption of new processes, tools, and technology. Top technology leaders will partner with other function leaders to fundamentally change how people work.
Letter to the CFO
Strategy is what a company does—its pattern of interdependent trade-offs, not the rhetoric it shares with stakeholders. Those trade-offs eventually come down to one thing: where you allocate financial resources.
Looking to the year ahead, you’re up against continued trade disruptions, stretched consumers, and rising costs. Meanwhile, the list of “must-do” investments from across the business keeps growing. Cost and balance sheet management will be critical to liberate the funds needed to reinvest in pricing, customer value and experience, and, of course, technology and generative AI.
It’s understandable if you’re skeptical. Your colleagues are celebrating step-change productivity gains from AI and automation, but you’re still wondering: Where, exactly, is the ROI?
The issue is process complexity. Dropping generative AI into step No. 6 of a broken process delivers the same outcomes, just faster.
Tangible ROI requires concentrated bets on full-scale changes—a zero-based redesign of your processes from end to end. Start by asking, “If we were designing this process with today’s technology and data, what would it look like?” Gains usually don’t come from shaving minutes off a task but rather from reimagining workflows from the ground up in a few functions. We recommend putting merchandising at the top of the list. Bain typically sees a 2% to 4% reduction in costs of goods sold (COGS) through robust category management and disciplined negotiation tactics. AI can unlock an additional 1 to 2 percentage points by injecting more rigor into long-tail supplier negotiations. Other high-priority, proven areas include marketing personalization (5% to 10% revenue uplift by campaign) and AI-enabled inventory management (8% to 10% reduction in working capital).
Zero-based redesign in merchandising
%
reduced COGs from advanced buying capabilities
+
percentage points unlocked by AI
If you need a proving ground for the rest of the organization, start with your own house. Redesign a few finance workflows from end to end, combining classic process redesign, automation, and AI. Take, for instance, financial planning and analysis. Picture an interactive, scenario-based experience, where users input “what if” queries and receive real-time modeled outcomes, enabling continuous planning. With finance setting the precedent, you can partner across functions to go upstream, fix broken processes, and get more from the technology you’ve already invested in.
In 2026, it’s time to move past “AI innovation theater.” You have an opportunity to champion a cohesive investor narrative that links a unified, defensible strategy to maximizing TSR. That means finding fuel for growth and investment through cross-functional cost and process changes, supported by AI when it’s genuinely the right tool, not a boardroom buzzword.
The authors would like to thank Stephanie Koszyk, Francois Vayleux, Katherine Hall, Ricky Swieton, and Sarah Dang for their contributions.
First published in enero 2026