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The 2026 FIFA World Cup is the largest in the tournament's history: 104 matches across 16 cities in the United States, Mexico and Canada (40 matches more than the last edition), running from 11 June to 19 July, with an estimated six billion people — roughly three-quarters of the planet — expected to engage with it. For scale, the Paris 2024 Olympics drew around five billion viewers. The magnitude of the audience makes headlines, but the actual impact comes elsewhere: audiences have only a modest national effect, with the main beneficiaries being host cities through tourism, services, and consumption. As a result, the most interesting story may not happen on the pitch but in retail, especially in department stores that are seizing the moment as both a business opportunity and a chance to become cultural destinations. Here's how the biggest names in retail are playing the game.

The economics: large in aggregate, modest in practice

A vast audience, a small footprint

The macroeconomic case for the World Cup is surprisingly thin. The U.S. is projected to gain approximately $17 billion in incremental GDP — less than 0.1% of annual output. Canada's impact is similarly marginal at around 0.1% of GDP. Mexico is the relative winner: with 13 matches generating an estimated $3 billion in economic benefit, the impact represents between 0.2% and 0.5% of GDP, a meaningful uplift by comparison. Mexico is also expected to benefit from tourism, as tightened U.S. immigration controls may dampen international arrivals to the largest host nation. Around 5 million visitors are anticipated in Mexico, generating tourism revenues exceeding $1 billion.

The real commercial action, however, is not at the national level. It is highly localised and concentrated in host cities and in the strategies of brands and retailers willing to invest in the moment.

The sportswear equation

Adidas, Nike and Puma collectively kit out more than 75% of the 48 participating nations. Adidas leads with 14 national teams, followed by Nike with 12 and Puma with 11. With North America accounting for over 40% of Nike's annual revenues, the brand enters this tournament with a structural home advantage and estimates the tournament could generate $1.3 billion in incremental revenue. Adidas projects a comparable $1.2 billion uplift. Retailers stocking Nike products have committed to offering 40% more football merchandise by volume than during Qatar 2022, when an estimated 14.4 million shirts were sold. Projections for 2026 range from 18 to 23 million units, with the three major brands expected to capture 80% of that market.

With the demand for football products largely pre-allocated to mono-brand stores and sportswear retailers, the strategic question for a department store is elsewhere: what to do with a sport they don't necessarily own? Also, what does the World Cup mean for footfall, dwell time, brand perception, and customer acquisition?

El Palacio de Hierro: the full playbook

The tension every premium retailer has to resolve

Football is mass, emotional and culturally democratic. A premium or luxury department store like El Palacio de Hierro is none of those things by default. The instinct to drape the building in tournament colours would lack credibility with customers accustomed to more elevated store communications.

El Palacio de Hierro articulated this tension clearly. With Mexico having hosted in 1970 and 1986 — both woven into national memory — the 2026 edition carries emotional weight. But the company understood it could not wrap itself in soccer colours and claim authenticity it does not have. Instead, El Palacio de Hierro positioned itself as the stage on which the World Cup experience is elevated. The campaign's central premise, "if the World Cup brings the world to Mexico, El Palacio de Hierro sets the stage", aims at reconciling premium and mass through emotion.

Three phases for an unprecedented campaign

The warm-up phase activates Noches Palacio, the store's flagship loyalty promotion. The mechanic (purchases earn coins, coins are redeemed for tiered prizes at the end of each promotional weekend) creates urgency and repeat visits. Crucially, as observed by El Palacio de Hierro in the first days, the promotion has proven to attract both loyal, affluent customers and new entrants, serving as a retention and acquisition tool simultaneously. Live music, performers, F&B programming and World Cup theming transform participating stores into destination experiences.

The pre-tournament phase shifts to experiential and pop-up activation. The standout is a branded pop-up that deliberately juxtaposes brands that do not typically coexist in luxury retail: Adidas, Hisense, Don Julio and Buchanan's. The logic is curation beyond product selling: assembling a premium watch-party environment in which the purchase of merchandise, the consumption of premium spirits, and the viewing of a World Cup match become a single, continuous experience.

The match phase is the most commercially intensive: special gastronomy programming aligned to which national teams are playing on a given day, watch parties in the store's restaurants, and interactive installations, including the Palacio Arcade, a soccer-themed entertainment zone designed to extend visit duration across entire families.

Beyond the in-store programme, two additional initiatives deserve particular attention.

The Yellow Pitch, a publicly accessible soccer pitch built directly in front of the Durango flagship in Mexico City, is the campaign's most provocative element. It requires no purchase and is open to everyone. It is designed to generate organic social content and street-level energy. For a luxury retailer, it is an act of deliberate democratisation: the tension between free public access and luxury equity should result in a new form of brand authority for El Palacio de Hierro.

The luxury city guide, distributed to premium hotels and airport arrival lounges in Mexico City, Monterrey and Guadalajara, functions simultaneously as a tourist service, a brand ambassador and a commercial acquisition tool. It reinforces El Palacio de Hierro’s position as a cultural authority, helping visitors to make the most of their visit.

From New York to Stuttgart: same tournament, different perspectives

Bloomingdale's: the lifestyle and menswear lever

Bloomingdale's approach to the World Cup is to connect several commercial objectives at once: menswear growth, Father's Day gifting, host-city relevance and fashion discovery.

The flagship activation, Game Day with Boss, occupies the 59th Street Carousel pop-up space from June 4 through August 24, a timeline that deliberately extends well beyond the tournament. The assortment of approximately 200 products spans fashion, accessories, beauty, wellness and lifestyle, anchored by around 70 Boss exclusives, including a performance collection developed for the U.S. Men's National Soccer Team. The addition of curated vintage jerseys connects World Cup culture to fashion nostalgia, elevating merchandise into collectable territory.

The format is being replicated across six additional locations near host-city markets (SoHo in NYC, Aventura in Florida, Century City in Los Angeles, Lenox Square in Atlanta and Bergen County in New Jersey), with the SoHo store receiving an expanded version featuring FIFA 1904, a heritage-focused football collection. Father's Day activations on June 13 add a commercial layer, blending food, beverages and wellness experiences with the World Cup framing.

Bloomingdale's experiment suggests that a World Cup activation does not require deep soccer credentials or sportswear-only activations, but rather the definition of its own version of the World Cup. For Bloomingdale's, the answer is a focus on male customers embedded in a lifestyle approach.

Macy's: the inclusive community play

Where Bloomingdale's focuses on lifestyle aspiration, Macy's has built its activation around inclusion and community access. World Soccer HQ is a multi-brand activation spanning Nike, Adidas and Puma, avoiding any single-sponsor dependency. The more distinctive element is the partnership with the U.S. Soccer Foundation, directing investment toward grassroots soccer access in underserved communities. This is not cause marketing in the traditional sense, but an attempt to build emotional legitimacy with a soccer audience that the brand does not yet own.

The activation extends nationwide with live entertainment, athlete appearances, and product customisation events. Macy's is using the World Cup to make a claim about its role in American cultural life, not simply to sell merchandise.

Nordstrom: the sponsor-led merchandiser

Nordstrom's partnership with Adidas takes a different stance, built around product discovery, localisation and a structured cadence of weekly activations across 35 stores. Every Thursday brings new gift-with-purchase offerings and sweepstakes; every other week, an Archive Zone spotlights a historically significant Adidas piece linked to that week's featured country. Weekend programming is aligned to whichever national teams are in focus, a country-by-country journey through the tournament that gives customers a reason to return week after week. The $75 qualifying purchase threshold for customisation events is worth noting.

What about Europe? Breuninger and Manor

Mexico and the United States are not the only countries to reclaim their share of the event. Breuninger's approach is more localised. The Stuttgart flagship has transformed its signature Eduard's Bar into a dedicated sports bar with Adidas for the duration of the tournament. This conversion builds on the store's identity as a destination for gastronomy and community, not just retail, as demonstrated by Breuninger’s annual Fashion x Food events, which bring gastronomy and fashion together. The Adidas partnership, which in 2024 already produced the redesign of the flagship facade for the soccer European Championship, is being extended with World Cup-themed activations across multiple locations: jersey customisation pop-ups, exclusive product drops, and competitions for signed merchandise.

Manor’s One Game, One Love campaign for the FIFA World Cup 2026 features official national team jerseys from Puma, Nike and Adidas, as well as exclusive fan merchandise, lifestyle apparel, and collectable items, to attract sports enthusiasts without losing fashion customers. Creative collaborations, such as the limited-edition Football Bags by Geneva-based designer Joana Bender, anchor the store locally while mixing exclusive products with street style. The campaign’s themed activations and limited-time collections are designed to drive footfall, customer engagement, and cross-category sales during the tournament.

For department stores, the FIFA World Cup 2026 is not about soccer or promotions but about their strategic self-knowledge. The retailers that will emerge strongest are not those with the deepest soccer credentials, but those who answer the question of who they are and what this moment means for them. From that perspective, the World Cup is not a retail strategy or a must-have, but an additional opportunity to show more than just a house of brands and to become a host and experience curator, while increasing repeat visits and dwell time. As such, the initiatives will amplify whatever a retailer already does well, and whatever remains unconvincing.

Credits: IADS (Christine Montard)

What: Organisations can only capture value from agentic AI when teams are empowered to redesign how work gets done.

Why it is important: For most organisations, the bottleneck in AI adoption has shifted from tool access to organisational capability — whether teams have the mandate and capacity to change how they work.

Agentic AI is changing how organisations approach change itself, shifting the focus from central technology programmes to team-led workflow redesign. While GenAI has reached 70% adoption in three years, only 16% of Australian executives report significant value from it. BCG argues that technology access has ceased to be the main constraint; the gap now lies in whether teams have the confidence, capability, and permission to change how work is done. The authors identify the two or three domains most likely to affect business metrics as the right starting point, rather than launching broad portfolios of pilots. The CHRO sits at the centre of this agenda, with responsibility for reskilling, organisational design, and new human-AI workflows. AWS is presented as a case study, having embedded experienced peer engineers into teams and linked GenAI use to outcomes such as customer-facing features, resulting in 27% more features shipped.

IADS Notes: BCG's argument that agentic AI value depends on empowering teams to change how they operate is reinforced by a cluster of recent reporting. BCG reported in June 2026 that autonomous agents introduce overlapping risks across privacy, cybersecurity, governance, third-party exposure, and data quality, making clear accountability and enforceable standards essential before scaling. In April 2026, BCG showed how AI agents are already changing merchandising by coordinating pricing, promotion, assortment, and inventory decisions continuously, but only where retailers rebuild operating models around cleaner data and end-to-end ownership. BCG's March 2026 work on the CHRO role highlighted the workforce gap behind AI adoption, stressing systematic upskilling and closer alignment between talent strategy and organisational change. Retail Touchpoints in January 2026 noted that nearly half of retailers are piloting autonomous AI, while successful scaling depends on proprietary data, integration, governance, and human oversight. BCG also reported in November 2025 that CEOs must lead workflow redesign, reskilling, talent strategy, and cross-functional collaboration if AI is to lift performance rather than remain another technology rollout.

Agentic AI turns every team into its own transformation engine

What: Depop’s model reveals how second-hand fashion platforms use emotional rewards, data-driven nudges, and scarcity to drive engagement and sales.

Why it is important: This highlights the growing relevance of circular fashion, as resale platforms increasingly combine consumer psychology with data-led conversion tactics.

Depop’s success lies in how it turns second-hand shopping into an emotionally rewarding and commercially effective experience. The platform appeals to consumers through sustainability, allowing shoppers to feel that they are extending the life of products and reducing unnecessary waste. This “feel-good” element helps make resale more meaningful than a standard transaction.

Depop also uses behavioural triggers that many traditional retailers could learn from. Its wish-list function enables sellers to identify interested shoppers and send targeted discounts, turning passive intent into immediate conversion. At the same time, each listing is typically unique, which creates urgency and scarcity. When shoppers see that an item cannot simply be restocked, they are more likely to act quickly.

The broader lesson is that resale is not only about lower prices or sustainability. It is also about psychology, personalisation, and timing. Depop demonstrates how retailers can use emotional motivation, data signals, and scarcity to build stronger engagement and encourage faster purchase decisions.

IADS Notes: The article’s reading of Depop as a lesson in retail psychology aligns with several recent developments in the resale and digital commerce landscape. In February 2026, Retail Week showed how Vinted’s rise to become the UK’s third-largest fashion retailer confirmed that peer-to-peer resale has become a direct competitive force, driven by affordability, sustainability, and discovery. In April 2026, Forbes similarly framed resale as a mainstream growth engine for fashion, with technology, authentication, and changing consumer values making second-hand commerce more scalable and trusted. The article’s emphasis on wish-list signals and proactive discounting also connects with April 2026 coverage of Macy’s AI shopping assistant, which demonstrated how capturing intent and personalising recommendations can significantly increase spending. Meanwhile, BoF’s October 2025 analysis of resale platforms shifting toward curated, AI-enhanced shopping experiences reinforces the importance of reducing choice overload, while Manor’s June 2025 Labubu drop illustrates how scarcity and FOMO can turn limited availability into a powerful retail event.

Unpacking the psychology of Depop

What: Change management in organizations demands genuine leadership alignment, clear communication, and a shared understanding of organizational culture — conditions that are far less common than leaders assume.

Why it is important: Most senior leadership teams believe they are aligned when they are not. Without genuine agreement on why, what, and how to change, execution stalls, misdirects, or produces watered-down compromises at every level of the organization.

Most organizations today are navigating significant change — yet most leadership teams are not as aligned on it as they believe. Senior leaders routinely fall into what the authors call the "false alignment trap": they assume a shared vision exists when, in practice, it does not. This produces three predictable outcomes — paralysis, wasted effort, or misdirected activity across the organization. Reaching genuine agreement requires structured debate, tolerance for early dissent, formal commitment, and a single unified message communicated downward. These conditions rarely emerge on their own. When leaders rely on vague discussions, avoid real disagreement, or prioritise speed over clarity, confusion compounds at every level of execution. Organizations that surface and resolve these disagreements before execution begins consistently achieve more durable outcomes than those that defer them.

IADS Notes: AI is reordering how retail organizations manage change — accelerating decision timelines, altering skill demands, and exposing the gap between leaders who plan for it and those who do not. Yet 72% of employees globally now use AI tools regularly while only 36% feel well-prepared for the shift, pointing to missing foundational skills and insufficient training structures (BCG, September 2025; The Economist, May 2026). CEOs are now directly responsible for closing this gap — redesigning workflows, committing to structured upskilling, and leading by example on adoption (BCG, November 2025; BCG, June 2026). AI adoption is simultaneously outpacing governance: accountability structures remain unclear, and employee readiness lags behind tool deployment. Direct leadership communication and structured training programmes are proving necessary conditions for sustained performance gains (BCG, June 2026; BCG, May 2026). Automation is also compressing some roles while elevating others, and the sector's deeper challenge is protecting the human-facing capabilities — judgment, relationship-building, creativity — that drive customer loyalty and operational depth. Organizations that integrate AI without undermining these capabilities are the ones positioned to lead (BCG, May 2026).

Change managent - The false alignment trap

What: Global conflict is becoming a workforce strategy issue, with direct implications for employee wellbeing, continuity, and retention.

Why it is important: Crisis preparedness belongs inside workforce planning — treated as a standing operational discipline, not triggered only when events escalate.

Global conflict and instability are creating workplace challenges that extend beyond immediate business disruption. Amy Dufrane, CEO of HRCI, argues that employees can be affected through military obligations, family connections abroad, caregiving responsibilities, immigration concerns, financial pressure, or exposure to distressing news. Those with direct links to war-affected regions may experience depression, anxiety, and trauma-related symptoms, while others can feel the impact through uncertainty or higher costs. The article urges organisations to stop treating conflict as a series of isolated emergencies and instead make crisis preparedness a permanent part of workforce strategy. This includes planning for employee wellbeing, operational continuity, workforce flexibility, and crisis response before disruption occurs. The risks are not limited to large employers: small and mid-sized companies face similar pressures when global events affect morale, productivity, and retention, as well as disruptions to supply, delivery timelines, and customer service. HR leaders need systems designed for repeated activation — because the next disruption is a matter of when, not whether.

IADS Notes: HR Dive's argument that global conflict should be treated as a standing workforce risk is supported by several recent sources. Seramount reported in July 2025 that workplace mental health challenges are affecting burnout, employee support expectations, and retention, particularly among hourly workers, managers, and younger employees. Harvard Business Review noted in May 2026 that companies are increasingly considering Chief Resilience Officers to coordinate responses to complex disruptions, including geopolitical shocks, cyber threats, operational continuity, and stakeholder trust. Inside Retail reported in March 2026 that the Middle East war was raising energy and food supply risks, logistics costs, inflationary pressure, and inventory concerns for retailers. The Robin Report also showed in March 2026 that wartime disruption was leading to store closures, weaker consumer confidence, and greater pressure on leaders to communicate transparently. Seramount reported in January 2026 that labour market volatility is pushing HR leaders toward adaptive, scenario-based workforce planning, including internal mobility and reskilling as standing capabilities.

What HR leaders should do when world events hit the workplace

What: AI agents are transforming retail by shifting decision-making from human consumers to autonomous systems that prioritise data quality and transparency.

Why it is important: As AI agents mediate more transactions, retailers must overhaul traditional marketing and operational models to avoid losing relevance and control to digital intermediaries.

The emergence of AI agents as autonomous shoppers is fundamentally altering the retail landscape, shifting the locus of decision-making from human consumers to sophisticated algorithms. Retailers are now compelled to adapt their strategies, as AI-driven systems prioritise structured, transparent product data and authentic reviews over traditional marketing cues rooted in human psychology. This evolution challenges established notions of brand loyalty and customer engagement, demanding a redefinition of marketing science that focuses on influencing artificial neural networks rather than people. As AI platforms increasingly become the primary interface for shopping, retailers face the risk of losing direct control over the customer relationship and brand experience, potentially relegating themselves to mere fulfilment roles. The operational complexities of this shift are significant, requiring robust machine-readable data, new payment and governance systems, and advanced security protocols to mitigate risks such as fraud and misuse by autonomous agents. Retailers who fail to adapt to these changes risk being marginalised in a marketplace where visibility and trust are determined by algorithmic gatekeepers rather than human preference.

IADS Notes: In April 2026, Liontree reported that nearly half of consumers, particularly Gen Z and affluent shoppers, are now influenced by AI-driven recommendations, underscoring the shift in retail decision-making. The Harvard Business Review in May 2026 confirmed that traditional marketing strategies are becoming ineffective, as AI agents prioritise data quality and transparency over classic persuasion techniques. The Robin Report, also in April 2026, highlighted the necessity for brands to invest in proprietary data and domain-specific AI models to remain relevant, as AI platforms increasingly act as digital gatekeepers, threatening direct customer relationships. RH-ISAC, in April 2026, emphasized the emergence of new cybersecurity risks with autonomous agents, calling for real-time monitoring and adaptive governance. Finally, Journal du Net in June 2026 stressed that consolidating and validating structured data across platforms is now essential for customer satisfaction and brand visibility.

How do you market to an AI customer?

What: AI agents must reflect a retailer's unique culture and values to maintain brand differentiation and customer loyalty.

Why it is important: Retailers who align AI with their brand identity can build stronger customer relationships and stand out in an increasingly automated market.

As AI agents assume a greater share of customer interactions in retail, brand differentiation is increasingly a function of whether those systems carry the organisation's culture, not just its instructions. Technical proficiency in accuracy, efficiency and compliance remains a baseline; it cannot, on its own, produce loyalty or meaningful differentiation. Two retailers using identical AI models can deliver vastly different customer experiences. The variable is the cultural logic embedded in those systems: whether agents are built to prioritise process or to treat the customer as an individual. Repeated across millions of interactions, that divergence either compounds into a genuine brand distinction or erodes into generic service delivery. The challenge for retailers is to translate tacit cultural knowledge into explicit operational logic that AI systems can execute, ensuring every interaction is not only efficient but also meaningful and consistent with the brand's ethos. Achieving this requires prompt architecture, value-weighted training and governance structures designed to prevent cultural drift, alongside the harder organisational work of making culture explicit enough to teach to a system. The retailers who succeed in this next phase will be those whose agents consistently reflect who they are, not merely how efficiently they operate.

IADS Notes: The stakes for retailers are already playing out in consumer behaviour. Liontree's April 2026 analysis found that nearly half of consumers now act on AI-driven recommendations, making the question of how agents are built and what values they carry a commercial priority. WWD reinforced this in May 2026, documenting how AI is fundamentally altering the customer journey and placing mounting pressure on retailers to balance technological capability with emotional engagement. Journal du Net sharpened the competitive risk in June 2026: without a distinctive brand language, AI amplifies sameness across every customer interaction, eroding differentiation at the point where it matters most. On the operational side, BCG's April 2026 report on always-on merchandising showed that AI agents now occupy the centre of product discoverability, shifting influence from consumer choice to autonomous recommendation and demanding new approaches to data governance. McMillanDoolittle captured the governance dimension in May 2026, warning against over-automation and the gradual erosion of human oversight, and emphasising the need for structured upskilling as organisations deploy these systems more broadly.

Why AI agents need an identity, not just instructions

What: Overreliance on AI is accelerating the erosion of critical human skills in organisations, threatening judgment, creativity, and long-term resilience.

Why it is important: Without systematic upskilling and governance, organisations risk undermining talent pipelines and losing the judgment and adaptability essential for long-term success.

BCG names the phenomenon precisely: ‘distributed de-skilling’—not just the erosion of any individual’s capabilities, but the simultaneous, system-wide degradation of human judgment, problem framing, and creative thinking across an organisation. This distinction matters: a talent problem can be solved by hiring; a system design problem requires redesigning how an organisation builds governance, workflows, and culture around AI. The scale of the risk is already visible. Half of the 70 C-suite leaders surveyed are observing de-skilling now; more than 60% expect it to become a material threat within three to five years. Only one in ten companies has a strategy to address it. The symptoms compound: 90% of leaders report uncritical acceptance of AI outputs; 53% flag slower junior talent development as formative experiences disappear into automated workflows. BCG’s most counterintuitive finding shapes its conclusion: the skills most at risk—judgment, problem framing, causal reasoning—survive only through active use. Treated as a renewable asset, human capability atrophies without deliberate practice and grows with it. For BCG, acting on this now is a source of competitive advantage.

IADS Notes: Recent analyses give the BCG finding both statistical weight and sectoral context. The Economist in May 2026 documented significant shifts in job roles and skill requirements driven by AI integration, with entry-level and white-collar positions carrying the greatest exposure. Harvard Business Review in March 2026 identified the specific mechanism: when early-career roles are automated, organisations lose the formative experiences through which judgment and resilience develop—a finding that directly supports BCG’s concern about junior talent pipelines. Inside Retail’s September 2025 analysis brought the dynamic into sectoral focus, warning that over-reliance on AI is already eroding customer insight and innovation at the operational level. BCG’s own September 2025 research found that only 36% of retail workers feel prepared for AI-driven change, making systematic upskilling urgent rather than optional. Journal du Net in June 2026 reinforced the governance dimension: fragmented data systems and inadequate oversight are the primary constraints on effective AI deployment, making structured governance the foundation of both AI performance and human capability.

When everyone uses AI, companies risk losing critical skills

What: AI transformation depends on building trust, supporting managers, and integrating human judgment alongside technological change.

Why it is important: Organisations that prioritise trust, upskilling, and human-centric leadership are more likely to achieve sustainable value from AI investments and avoid the pitfalls of over-automation.

AI transformation is advancing rapidly, but the pace of technological change often outstrips the development of the human infrastructure needed to support it. While executives may express optimism about AI’s potential, a significant gap persists between leadership perceptions and the lived experience of frontline employees and managers. This disconnect is reflected in the persistent “productivity paradox,” where substantial AI investment has yet to yield broad-based operational gains for most organisations. The article highlights that trust, transparent communication, and empathetic leadership are essential for overcoming employee scepticism and ensuring that AI adoption is not perceived as a top-down imposition. Managers, who serve as the hinge between strategy and execution, require clear guidance, training, and support to navigate the complexities of AI-driven change. Over-reliance on automation risks eroding critical thinking, engagement, and workplace culture, making it vital to balance technological innovation with human judgment and values. Ultimately, sustainable AI transformation will be achieved not by accelerating tool adoption but by building a culture of trust, learning, and shared accountability across all levels of the organisation.

IADS Notes: The article’s emphasis on trust, human infrastructure, and the centrality of managers in AI transformation is strongly validated by recent findings. In April 2026, Harvard Business Review documented how persistent misalignment between executives and managers is slowing AI adoption, with less than 10% of companies achieving scalable value and middle managers facing the brunt of operational strain. McMillanDoolittle’s May 2026 analysis highlighted the risks of over-automation and the loss of human oversight as advanced AI tools become central to operations, underscoring the need for upskilling and robust governance. The Economist in February 2026 confirmed that despite heavy AI investment, broad productivity gains remain elusive, with workforce adaptation and upskilling gaps hindering operational results. BCG’s July 2025 research revealed that only 36% of workers feel prepared for AI-driven change, making systematic upskilling and balanced AI-human integration critical for sustainable productivity. Finally, in April 2026, Harvard Business Review warned that overreliance on AI can erode employee engagement and critical thinking, reinforcing the importance of human-centric practices and cultural transformation in AI adoption.

Humans transforming AI transformation

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Everlane made transparency its commercial proposition. Shein has now bought the remains of that proposition at a price shaped less by brand heat than by financial distress.

In May 2026, Everlane said it had reached an agreement to be acquired by Shein, the ultrafast-fashion platform IADS examined in its January 2026 Exclusive, ‘The Shein paradox: when digital ultra-fast fashion meets physical reality’. That article documented what happened when Shein tested that ambition at BHV Marais in Paris: 300,000 initial visitors gave way to near-empty floors within weeks, as in-store prices far above the online average undermined the very proposition that drove the brand. The Everlane acquisition extends the same question: can Shein acquire the trust it cannot earn, through a brand once built on radical transparency?

The reported price was about $100 million, although the companies did not publicly disclose financial terms. Six years earlier, Everlane had been valued at $550-600 million. By the time the sale was being discussed, the company had accumulated around $90 million in debt, and common shareholders were expected to receive no payout.

How Everlane weakened before the sale

Everlane, the San Francisco direct-to-consumer label founded in 2010, built its following on minimalist basics and a ‘radical transparency’ proposition: publishing product cost breakdowns, naming its factories, and showing customers how their clothes were made. In March 2020, as the pandemic shut down retail, Everlane laid off 42 of its 57 customer experience workers. Those workers had been organising a union since 2019 and had formally requested recognition weeks earlier. US Senator Bernie Sanders accused the company of using the crisis to union-bust. Three months later, a group of former employees released a document titled “Everlane’s Convenient Transparency,” alleging anti-Black behaviour, unequal advancement, bullying and a toxic internal culture. Everlane’s founder and then-CEO Michael Preysman acknowledged that the company had “urgent work to do to rewrite its code of ethics.”

Everlane was transparent, where transparency supported the brand. Where transparency would have exposed how the company itself operated, it went quiet. That mattered because transparency was not a communications theme for Everlane; it was the reason customers accepted the price. Once that trust broke in 2020, Everlane lost the distinction that had separated it from a crowded field of brands selling clean aesthetics, minimalist basics and ethical language.

Later, the repositioning backed by L Catterton turned that credibility problem into a pricing problem. L Catterton, the consumer-focused private equity firm created through a 2016 partnership between Catterton, LVMH and Groupe Arnault, invested in Everlane in 2020, the same year the culture document broke, and was reported as its majority owner by the time of the Shein sale. Under that ownership, Everlane was pushed upmarket, toward the territory occupied by Theory and Frankie Shop — a poor fit for a brand that had trained customers to accept its prices by explaining what went into them. Moving closer to premium fashion asked those same customers to pay more for a brand whose ethics promise had already been broken.

In 2022, Everlane announced a $25 million term loan from Gordon Brothers. The wording of the announcement presented the facility as support for growth and sustainability. The lender profile told a different story. Gordon Brothers describes itself as a global advisory, restructuring and investment firm. Its retail work has included distressed and restructuring-linked situations, such as Laura Ashley, Brooks Brothers, and Toys “R” Us.

That was a form of convenient transparency in its own right. Everlane disclosed the loan and described it as growth capital. It did not dwell on what it meant for a brand built on trust to depend on a restructuring specialist — a brand that had built its following by showing customers exactly what their clothes cost to make, and was now calling a restructuring facility growth capital.

Everlane had also taken on a $65 million revolving credit facility from CIT Northbridge in September 2022. Together, the two facilities brought its debt load to around $90 million. Revenue had reportedly slipped from $198 million in 2024 toward $170 million by early 2026, while the business was close to breaking even rather than turning a profit on the capital behind it.

By March 2026, L Catterton was reportedly seeking investors to address the debt problem. There were also reports of overdue rents at Everlane’s San Francisco offices. When no investors emerged, the board approved the Shein deal. Preysman had stepped down as CEO in 2021, formally moving into the executive chair role in January 2022, and had left Everlane’s board earlier in 2026. He reportedly found out about the sale from the news.

What Shein bought

Of the arguments behind the deal, the logistics case is the least discussed and the most consequential. Shein’s US model had benefited from shipping low-value parcels directly to consumers. The end of the de minimis threshold (the US duty exemption on packages under $800) for China and Hong Kong changed the equation. Everlane gives Shein something it cannot acquire under its own name in the US market: domestic brand credibility. On the reported numbers, the math is hard to ignore: a $100 million valuation against approximately $90 million in debt leaves almost nothing once the debt is set against the sale price. Shein was not paying a rich price for the romance of 'radical transparency.' It was buying a US brand footprint, domestic operating knowledge, a higher-income customer file and a cleaner story to tell investors.

Maxine Bédat, founder of the New Standard Institute, a nonprofit developing transparency and accountability standards for the fashion industry said Shein was looking for “access to a higher price point, a marketplace that is more higher-end.” Everlane gives Shein a customer it could not easily reach under its own name: older and more affluent.

The IPO logic is also visible. Shein’s listing ambitions have been delayed by scrutiny over labour practices, supply chains, and data privacy. Neil Saunders, managing director of GlobalData’s retail division, described Everlane’s function directly: “Everlane is not revolutionary for Shein, but it does support a narrative of having a more balanced portfolio that can be sold to potential investors during any future IPO.”

Alfred Chang, who became CEO in 2021 following Preysman’s transition to executive chair, has defended the sale by saying Everlane will remain independent, keep its standards and use the partnership to expand its mission. That defence answers the wrong question. A subsidiary can maintain its own sourcing rules while its parent company’s total greenhouse gas emissions rise 81% in a single year. Whether Everlane preserves its ethics policy does not change what Shein ships globally. Sustainability, for Everlane’s customers, will now be judged against the parent company’s aggregate footprint, and that footprint keeps growing.

The supply chain argument… and its limits

Shein’s make-to-sell model produces small batches in response to real-time demand signals, then scales only when data confirm interest. Compared with traditional fashion forecasting, where brands order months ahead, warehouse excess inventory, and mark down what fails to move, Shein’s model can reduce waste per item. Chainge Capital, a supply chain advisory firm, has noted that Shein “makes five and sells five” in an industry that typically “makes ten to sell three,” achieving sell-through rates close to 100% against an industry average where 40-50% of goods end up discounted or unsold.

Analysts argue that the distinction goes deeper: Shein is not simply a faster fashion retailer, but a data-led supply chain business that happens to sell clothing.The efficiency is real, but it is measured per item. At Shein’s scale, the harder question is whether near-100% sell-through reflects responsive demand, or demand continuously stimulated by the pace of assortment refresh.

In 2025, Greenpeace Germany reported that 18 of 56 Shein products tested contained hazardous chemicals above EU legal limits. For Everlane's customers — whose decisions were shaped partly by sourcing claims, material safety, and factory standards — the Greenpeace result is a direct product-safety finding, not a general sustainability concern. It is a direct challenge to the type of product trust Everlane sold. Shein’s absolute greenhouse gas emissions rose by 81% in 2023, growing faster than revenue. Its demand-responsive production may reduce some per-item inventory waste, but it does not offset the footprint of an enormous assortment, high volume, and frequent deliveries: its reported transport emissions rose 13.7% to 8.52 million metric tons of CO2 equivalent in 2024, more than three times the transport emissions reported by Inditex.

This is where Chang’s defence runs into the numbers. A brand can keep its own sustainability language and still sit inside a corporate model whose aggregate impact keeps climbing. Shein may reduce waste on a per-item basis, but Everlane's customers will now judge the brand inside a parent company defined by scale, speed, chemical-risk scrutiny and transport emissions.

The EU’s Ecodesign for Sustainable Products Regulation (ESPR) is about to turn that direction into law. Everlane may be a US brand, but Shein’s European footprint means the combined entity faces these obligations directly. The destruction ban for unsold apparel, clothing accessories and footwear applies to large companies from 19 July 2026, while disclosure rules already apply to large companies, requiring them to report the number and weight of unsold products discarded and the reason for their disposal[19]. Broad sustainability language will not be enough.

Three exits, three numbers - Everlane is now part of a comparison set

Allbirds, the New Zealand-founded direct-to-consumer footwear brand known for sustainable materials such as merino wool and sugarcane-based foam, went public in 2021 and reached a market value of more than $4 billion. In early 2026, it agreed to sell its brand and footwear assets to American Exchange Group for about $39 million. Everlane, once valued at $550-600 million, exited at a reported $100 million, with common shareholders expected to receive nothing. Quince, which sells minimalist clothing essentials, accessories, and home goods with ethical sourcing claims at materially lower prices, raised $500 million in March 2026 at a $10.1 billion valuation.

Swap Commerce, a commerce infrastructure platform working across returns, cross-border commerce and recommerce, captured the failure pattern across several mission-driven brands: “Allbirds, Outdoor Voices, now Everlane – mission-driven brands with genuine cultural cachet, undone not by a lack of purpose, but by a lack of operational foundation. Everlane had the audience, just not the engine.” Quince is the contrast case from the same period: same minimalist positioning, same ethical sourcing claims, but a price point built to compete rather than justify. The Kearney Consumer Institute named the pricing problem: “The biggest challenge with any value-based product is the price has to be right for the right consumer. And Everlane, I think, just was exposed to a category that got crowded.”

The timing of the two deals is worth holding together. Quince raised $500 million in March 2026 at a $10.1 billion valuation. Weeks later, Everlane was being sold to Shein at a reported $100 million, with around $90 million in debt. Quince and Everlane sat at different stages, so this is not proof that cost structure alone sank Everlane. But it does show that capital was still available for minimalist basics with ethical sourcing claims, backing the version that priced more aggressively. Everlane charged a premium for transparency. Quince made transparency part of the baseline and competed on price, though Quince's sourcing claims have yet to face the same scrutiny that broke Everlane's.

What this means for department stores

Inditex can be taken as a point of reference as it did what Everlane could not: it moved parts of the offer upward without losing control of price, speed or inventory risk. Zara's premiumisation has been backed by larger stores, stronger presentation, designer collaborations and a supply chain that can still react within the season. At the same time, Inditex has used Lefties to answer lower-price demand without forcing Zara itself into a direct race with Shein. IADS documented the outcome of a direct test: when Shein opened at BHV Marais in Paris in November 2025, 300,000 initial visitors gave way to near-empty floors within weeks — higher in-store prices and a limited selection could not transfer the endless-assortment, low-price proposition that drives the brand online. That case study is set out in full in IADS Exclusive, ‘The Shein paradox: when digital ultra-fast fashion meets physical reality.’

In 2025, Inditex reported €39.9 billion in sales and €6.2 billion in net income. It has continued to optimise its store base, reducing store count while increasing the weight of larger, better-integrated flagships. Zara has moved parts of its offering upmarket through higher-quality fabrication, designer collaborations, and more premium store environments. At the lower end, Lefties gives Inditex a separate vehicle for price-sensitive demand. Lefties grew 17.44% to €644.81 million in the year to January 2025, moving from a small loss to a profit of €21 million. Inditex is not asking a single brand to cover every price tier at once.

As IADS set out in a previous Exclusive on Zara’s strategic evolution,  Zara’s speed is not a merchandising habit; it is built into sourcing geography. Roughly half of its production is near-shored in Spain, Portugal, Morocco, and Turkey for fast-turning items, with Asia reserved for basics – a dual-speed supply chain that lets the brand react to trends mid-season while competitors are locked into collections planned six months ahead. That architecture is not transferable for department stores if they place wholesale orders up to six months before delivery.

The buying problem and the compliance problem are the same problem: the data ESPR requires retailers to disclose is the same data buying teams need to catch over-ordering before the season closes .A retailer that cannot report its discarded unsold products does not just have a reporting gap — it lacks the inventory visibility that would have caught the excess before it built.

What Everlane’s former CEO and founder concluded

Preysman’s response to the sale was immediate: “appalled.” Within days, he launched Still Radical, a new venture presented as having no venture capital and no private equity.

His diagnosis is clear: private equity killed Everlane. Once L Catterton held majority control, the final decision belonged to investors whose obligations were financial, not philosophical. But this diagnosis leaves too much out.

Preysman ran Everlane for eleven years. He was CEO during the 2020 union controversy. He was the executive chair when former employees documented allegations of racism and toxic culture. He sold his shares to L Catterton in 2020, beginning the ownership transition he now criticises.

Industry observers put part of the problem in founder terms: “When Michael Preysman stepped back after L Catterton took majority control, Everlane lost its centre and never recovered it. The brand’s identity lived inside one person and left with him.”

Everlane’s identity depended too heavily on its founder, and its internal practices did not consistently support its external promise. Both weaknesses were present before L Catterton became the controlling investor. Avoiding venture capital answers the financing lesson. It does not answer the trust lesson. Preysman has not said what happened to the 42 customer experience workers let go in 2020, or what Still Radical would do differently in the same situation.

Here, the timing turns from coincidence to choice: Preysman sold his stake to L Catterton in 2020, the same year the union controversy and the culture document broke. He sold while the brand still carried much of its market credibility. Revenue had not yet collapsed. That makes the timing harder, not easier, to explain away: Preysman exited before the trust damage had fully shown up in the numbers, leaving later owners to manage the financial consequences of a credibility problem that began under his leadership.

Revenue held near $200 million through 2024, including $198 million in that year, so the trust break did not kill the company at once. It capped what the brand could credibly ask from customers. Everlane could still sell accessible basics to people who liked the product. What it could no longer do easily was ask those customers to follow it upmarket on the strength of an ethics-led promise. The damage became terminal when L Catterton pushed prices above that ceiling. Debt that was manageable at $200 million in revenue became harder to carry as revenue fell toward $170 million, and the premium strategy produced no growth. The Shein sale followed from that.

Everlane could publish the cost of a product. It could not show that its ethics held when they were costly.

Credits: IADS (Maya Sankoh)

What: Agentic marketing is moving from theoretical promise to operational reality, with AI-driven strategies now central to growth and competitive advantage.

Why it is important: The operationalisation of agentic marketing is now a key differentiator, with only 32% of CMOs currently deploying AI agents across meaningful workflows — and 42% at risk of an adoption that pilots without ever scaling.

The BCG CMO Survey 2026 offers a clinical correction to the optimism of recent years. Nearly every CMO surveyed (96%) claims that AI is driving end-to-end change across their function. Yet BCG's own maturity mapping tells a different story: only 32% of CMOs are genuinely deploying agents across strategy, content, and activation; 42% remain reliant on GenAI as a task-level assistant. The challenge is structural rather than motivational: most organisations have run successful pilots but have not yet redesigned their operating models, upgraded their martech stack, or built the internal AI talent that cannot yet be recruited externally. The results for those who have done so are measurable: 20–30% efficiency improvements and, for the leading cohort, a threefold gain in marketing ROI. The CMO's role has shifted from campaign leadership to structural build.

IADS Notes: Multiple recent analyses extend and sharpen the BCG CMO Survey 2026's central argument. In April 2026, Inside Retail and BCG warned that AI-driven agents are now mediating purchase decisions — shifting control from brands to algorithmic intermediaries — and that brands absent from agentic systems risk becoming invisible regardless of media spend. The need for robust data governance and scenario planning is pressing, as the absence of these systems translates directly to lost revenue. The gap between ambition and execution is well-documented across both sources: BCG's survey classifies only 32% of CMOs as genuine leaders, while the Financial Times reported in May 2026 that just 10% of retailers have successfully scaled agentic AI at an organisational level, citing persistent challenges in integration, governance, and workforce readiness. The evolving CMO role, as noted by BCG in November 2025, now centres on building the infrastructure, talent, and governance required for agentic marketing — a remit that extends well beyond campaign management.

Moving the agentic marketing transformation from illusion to reality

What: AI amplifies both the strengths and weaknesses of brand content, making unique brand language essential for differentiation.

Why it is important: For retail brands, developing a proprietary language system and fostering community engagement are now prerequisites for loyalty and resilience in an AI-accelerated market.

The article argues that artificial intelligence magnifies what a brand brings to it: a distinctive language is accelerated; a generic one is amplified into indistinction. As AI scales content production across articles, campaigns, and digital touchpoints, brands risk producing messaging that is indistinguishable from competitors' if they rely on shared promises and generic vocabulary. Differentiation has always been a core strategic concern, particularly in naming and visual identity, but it is frequently neglected in verbal expression. How many brand platforms still rest on promises of innovation, proximity, excellence, and trust? Legitimate notions, widely shared ones. To stand out, brands must formalise their own language system before deploying AI, defining priority messages, narrative territories, distinctive lexicons, and signature expressions. Only then does AI become a powerful accelerator of brand uniqueness rather than a force for standardisation.

IADS Notes: This concern is well supported by recent industry evidence. In May 2026, analysis of how AI is altering the customer journey confirmed that AI-driven content creation risks homogenisation unless brands invest in a unique narrative and language system . In April 2026, the case for dedicated AI visibility strategies reinforced the urgency: brands must adapt to new digital gatekeepers and optimise for AI-driven discovery before homogenisation sets in . Zalando's approach to generative AI, documented in May 2026, demonstrates how speed and personalisation can coexist with editorial distinctiveness — but only when a brand's language is already well defined . More broadly, the shift towards participatory, community-driven engagement evidenced in May 2026 and September 2025 shows that brands fostering cultural fluency and authentic storytelling are better positioned to build loyalty and resilience . AI amplifies what brands bring to it. Retailers who have formalised a distinctive language system can use it as an accelerator; those who have not risk being standardised further.

Standardisation of brand content: what if the problem isn't AI?

What: Most organisations are failing to translate AI upskilling into measurable performance improvements due to gaps in integration, training, and leadership engagement.

Why it is important: The gap between AI investment and measurable performance is not narrowing — and the cost of that gap compounds as the pace of change accelerates.

Significant investment in AI upskilling rarely delivers proportionate performance gains. More than 60% of organisations report little to no ROI, and nearly 80% of AI transformations fall short of expectations. The problem is one of effectiveness: training happens, but performance does not follow. Value is created only when new tools are used inside real workflows, with learning embedded in the moment of need rather than taught in isolation. Organisations that close the gap embed capability building into actual work, address the identity shifts AI creates for employees, and realign incentives to reinforce new behaviours. Balancing technical AI skills with enduring human capabilities — judgment, collaboration, and problem solving — is equally critical. Converting capability investment into performance infrastructure is the defining challenge for organisations seeking sustained competitive advantage.

IADS Notes: Despite 71–72% of employees now using AI tools weekly, only 36% feel adequately prepared for AI-driven change, and just 10% of organisations have managed to scale their AI initiatives effectively, as highlighted by BCG and Journal du Net in June and September 2025 . AI adoption is forcing a fundamental rethink of workforce structures, skill requirements, and talent strategies — yet the gap between investment and workforce readiness persists. Harvard Business Review's March 2026 findings echo this: generative AI can accelerate productivity but also intensifies cognitive fatigue if not managed with well-structured training and clear practice frameworks . Human-centric approaches — comprehensive upskilling, workflow redesign, and leadership engagement — are repeatedly identified as critical success factors for translating AI capability into performance gains . A July 2025 BCG analysis identifies a parallel failure: skills-based organisations are not realising their potential, held back by the incomplete integration of business objectives, technology, and culture . The organisations that pull ahead will be those that treat capability building as performance infrastructure, investing in human judgment with the same seriousness they invest in tools.

How to turn AI skills into better performance 

What: AI-driven transformation often stalls at the manager level due to gaps in readiness, leadership support, and execution clarity.

Why it is important: Enabling managers through upskilling, clear strategy, and supportive organisational structures is essential to turn transformation ambition into operational success.

Transformation initiatives frequently falter at the manager level, where the pressure to translate AI-driven strategies into daily execution is most acute. Managers are now expected to lead through complex changes, balancing traditional responsibilities with new demands such as AI adoption, hybrid work, and evolving team structures. However, many lack the training and clarity needed to navigate these shifts, resulting in confusion, resistance, and stalled progress. The leadership pipeline is under strain as entry-level roles are automated and fewer employees aspire to management, creating a shortage of future leaders. Friction at the manager level often goes unnoticed, manifesting as misalignment, inconsistent communication, and execution risk. Addressing these challenges requires making manager enablement a core part of transformation strategy, redefining readiness for new work realities, and shifting from generic feedback to actionable execution insights. When managers are equipped and supported, they become the leverage point that turns strategic ambition into real, sustainable change.

IADS Notes: In April 2026, BCG identified the decisive role of leadership, culture, and systematic upskilling in scaling digital transformation, noting that most organisations still face significant gaps in workforce development and leadership engagement . BCG's March 2026 findings add a sharper data point: only 36% of workers feel prepared for AI-driven change, with systematic upskilling a critical gap at the manager level . The Economist's July 2025 analysis found that nearly three in four middle managers felt overwhelmed, and 40% of new managers were seeking new positions . Harvard Business Review in January 2026 pointed to hands-on leadership, operational agility, and cross-functional collaboration as key drivers of innovation and high performance in organisations undergoing transformation . BCG's July 2025 framework for change strategy demonstrated that transformation success depends on leadership-driven change, robust social networks, and clear communication of benefits . Equipped and supported managers are the primary lever for translating strategic ambition into execution.

3 reasons transformation gets stuck at the manager level

What: AI is transforming procurement, but without governance and high-quality data, it increases operational risks.

Why it is important: For retail, effective AI in procurement now depends on robust governance, integrated data, and human oversight to ensure reliability and mitigate risk.

AI is rapidly reshaping procurement by automating processes and enabling agentic autonomy, but the absence of governance and reliable data introduces significant risks. When AI operates without a clear framework, companies face errors in judgement, untraceable decisions, and increased complexity, especially as multiple specialised agents proliferate. The solution is a unified, governed system where human expertise guides, supervises, and validates AI actions — not a proliferation of independently configured agents. Data quality remains a critical barrier, with 74% of procurement managers reporting their data is not AI-ready, and 80% of CPOs planning to deploy generative AI in the next three years. Fragmented supplier data and siloed systems undermine structured autonomy, making it impossible for AI to deliver reliable outcomes. A centralised supplier repository is essential, consolidating all relevant information to enable safe, effective AI operations. The hybrid human-agent model only works when both rely on the same well-governed data and clear accountability structures. Governance is what transforms AI from a liability into a trusted decision-making asset.

IADS Notes: These risks are well documented in recent industry evidence. In June 2026, BCG reported that enforceable standards and clear accountability are now essential for scaling agentic AI, with unmanaged data risk constraining ambitions and exposing retailers to new cybersecurity threats. Journal du Net, also in June 2026, found that the effectiveness of AI agents is fundamentally limited by fragmented data systems, making structured, high-quality information critical for both operational efficiency and brand visibility. The May 2026 analysis of Anthropic AI Merchant and Andon Labs AI Store Manager highlighted the dangers of over-automation and the loss of human oversight, underscoring the need for robust governance frameworks as AI becomes central to retail management. BCG's September 2025 study on GenAI in supplier negotiations demonstrated that measurable productivity gains and risk reduction are only achieved when AI is integrated across end-to-end operations with strong data and governance foundations. Finally, Retail Touchpoints in January 2026 showed that successful AI adoption depends on a blend of technological innovation, proprietary data, and responsible implementation, with only 10% of retailers succeeding due to persistent integration and governance challenges.

The real risk to procurement is not AI, but AI without governance

What: The secondhand market's next phase of growth depends on industrializing operations through technology, logistics, and trust-driven infrastructure.

Why it is important: Secondhand platforms can no longer differentiate on price and sustainability alone — the operational bar for quality, transparency, and delivery reliability has risen to match new goods retail.

Secondhand commerce has moved past its first phase. The original growth drivers — lower prices, easier resale, more sustainable consumption — are now baseline expectations. At volume, the sector faces a structural challenge unique to its nature: every item is different. Unlike new goods retail, where identical products can be processed in bulk, secondhand operators must identify, assess, price, and list millions of individual items without standardised templates. AI and machine learning are increasingly handling the repetitive work — image recognition, pricing models, warehouse routing — while human teams manage the judgment calls automation cannot. Trust has had to follow the same path: built through quality checks, accurate descriptions, and reliable delivery, embedded in operations rather than stated in marketing. The players pulling ahead are those treating technology and logistics as the core of the model, not an addition to it.

IADS Notes: The secondhand sector's operational shift is already documented across recent industry analyses. Platforms like Vinted and The RealReal reported record revenue and user growth in 2026, driven by digital curation and the mainstreaming of circular economy models . As resale has consolidated as a mainstream retail channel, the operational gap between leading and lagging platforms has widened — with advanced technology now required to manage unique inventories, pricing, and logistics at the volumes consumers expect . AI and machine learning are increasingly handling identification, quality control, and workflow optimisation, while human expertise remains central to product assessment and trust-building . Quality control, transparent descriptions, and reliable delivery have moved from differentiators to entry requirements. Major partnerships — Vestiaire Collective and Zalando among them — and the growth of dedicated circular retail spaces like Sweden's ReTuna mall point to the same structural shift: investment in technology and logistics is now the price of operating credibly in secondhand at volume .

The next challenge for secondhand goods will be industrial

What: E-commerce sites must now adapt to AI agents that automate shopping decisions, demanding structured data, transparent actions, and machine-readable content to remain competitive.

Why it is important: When AI agents handle the purchase decision, brands that cannot be read and executed by machines are cut from the transaction — regardless of how well their site performs for human visitors.

Consumer delegates are already arriving. When a shopper assigns a purchase task to their AI assistant, the agent navigates the site alone — reading data, triggering actions, completing transactions. Sites built for human eyes present four consistent obstacles: authentication designed to block bots rather than welcome authorised agents; sales funnels reliant on visual cues an agent cannot interpret; product data buried in images and colour-coded signals; and page instability that leaves an agent acting on unreliable state. Emerging standards like WebMCP address this directly, enabling sites to declare their capabilities to agents rather than leaving machines to guess at button locations. The benefit runs both ways: a site precise enough for an agent to navigate is almost always cleaner, faster, and more clearly structured for human visitors too. The diagnostic question is concrete: run an agent through your purchase funnel tonight and identify the exact screen where it fails.

IADS Notes: For most e-commerce sites, the infrastructure gap is already open. Journal du Net's January 2026 analysis finds that most sites remain designed for human-centric browsing, even as nearly 40% of consumers have used generative AI for shopping and over half trust AI to make purchase decisions . Inside Retail's November 2025 report finds algorithm-driven agents now automating purchase decisions outright — making structured data and machine-readable content the determining factor in whether a product is considered at all . By April 2026, agentic commerce had altered retail strategy at the point of discoverability: AI agents, not consumers, were mediating which products reach consideration, requiring brands to overhaul digital infrastructure to stay in the running . Journal du Net's June 2026 research finds that nearly half of shoppers now act on AI-driven recommendations, putting pressure on data quality and integration across the product catalogue . Harvard Business Review's May 2026 analysis identifies a sharper problem: traditional marketing tactics do not work on AI agents, which prioritise data accuracy and ratings over persuasion — requiring retailers to rebuild testing and adaptation capabilities entirely . Across all five analyses, the directional signal is consistent: the advantage in agentic commerce will go to those whose infrastructure can be executed, not just visited.

Is your e-commerce site ready for AI-powered buyers?

What: Persistent financial stress is driving Europeans to reduce consumption, switch brands for better deals, and shift spending toward essentials, health, and digital discovery.

Why it is important: The trend confirms that economic pressure is now driving structural change in retail: brand loyalty is eroding, digital discovery is shifting, and spending on essentials is the only reliable growth pocket.

European consumer pessimism has reached its highest level in three years, with 56% expressing concern about the economy in 2026. Financial stress is widespread, as 53% worry about daily finances and 63% seek discounts or only buy at a deal. Brand loyalty is weakening, with 62% willing to switch for a better price and 44% making recent purchases from unfamiliar brands. Spending cuts are concentrated in discretionary categories, while groceries and pet care remain the only segments with positive net spending. Younger consumers are less loyal to brands and more open to second-hand purchases, while older cohorts are reducing overall consumption more sharply. Health and wellness have become a durable priority, with two-thirds of consumers calling them essential and nearly half reducing alcohol intake. Digital discovery is shifting rapidly, with generative AI and social media now leading product research, especially among younger shoppers. These changes appear structural, as nearly half of consumers would save rather than spend a hypothetical windfall.

IADS Notes: The BCG survey from June 2026 confirms a third year of rising consumer pessimism, with financial worries and spending restraint now entrenched. Visa’s July 2025 data highlighted the resilience of essentials, while discretionary categories continue to decline. Forbes and BCG/WWD in early 2025 noted that younger consumers are less brand-loyal and more likely to buy second-hand, while older generations are cutting back more than ever. Health and wellness remain robust, supported by the adoption of GLP-1 drugs and new wellness platforms, as seen in May 2026 reports. The rapid growth of generative AI and social media in product discovery, documented in April 2026, is changing how consumers find and evaluate products, signalling a lasting shift in retail engagement and strategy.

European consumers are still cutting back

More than half of europeans are worried about their personal finances, driving spending cutbacks - press release

What: The rise of agentic commerce is shifting control from consumers to autonomous AI systems, making data quality and governance essential for visibility and trust.

Why it is important: This shift demands that organisations prioritise structured data and robust governance, as only those prepared for AI-driven discovery will remain visible and trusted.

The article draws a sharp distinction between trusting AI to recommend a product and trusting it to make a purchase. At the recommendation stage, the consumer retains control; at the action stage, they delegate it, and that delegation carries new stakes. Generative AI has already changed the purchasing journey: consumers now describe needs in natural language, while AI filters, ranks, and summarises options before any product page is visited. Brand visibility no longer depends solely on search rankings or marketplace positioning, but on whether an AI agent can interpret and select their offer. A poorly structured or vague product description risks being deprioritised, even if the product itself is superior. The article raises three core challenges: transparency in recommendations, accountability when agents err, and the risk that AI-assisted simplification erodes consumers’ ability to compare independently. The conclusion is clear: the commerce of tomorrow will be a battle of trust, clarity, and information quality—not price or advertising alone.

IADS Notes: Recent analyses extend and sharpen the article’s central argument. In April 2026, Inside Retail and BCG warned that AI agents are now mediating discovery and purchase decisions, making agent-ready APIs and data governance non-negotiable for brands seeking commercial relevance. The Financial Times documented the practical consequence: retailers are moving beyond traditional search engine strategies, with structured data and generative engine optimisation becoming decisive for algorithmic discoverability. Journal du Net quantified the shift in April 2026—AI-driven recommendations already influence 10% of consumer purchases, making data quality a competitive variable. By June 2026, the same outlet reported that fragmented data systems are the primary constraint on AI agent effectiveness, reinforcing the article’s core argument: governance is the foundation on which trust, discoverability, and commercial performance all depend.

Do you trust AI to do your shopping?

PRINTABLE VERSION HERE 

Retailers have long drawn on behavioural techniques, nudges, to persuade consumers to purchase. Some have given rise to eponymous concepts like the ‘IKEA effect’ where consumers attribute higher value to products assembled themselves, fostering brand resonance. In digital advertising, nudges include complete-the-look carousels, star ratings, and one-click shoppable ads on social media. However, the implicit assumption is that consumers pay attention to these. But does this remain true in 2026?

Economists now treat human attention as a scarce resource comparable to land, labour, and capital reflecting that attention is finite, rivalrous, and exhaustible. Social media platforms have industrialised the harvesting and monetisation of attention, creating a paradox: the more content floods the environment, the less effective each individual message becomes. In this context of structural overstimulation, brands including Gentle Monster and New Balance are moving from persuading through exposure to cultivating cultural belonging, offering a new angle to a job department store historically used to excel at: shaping their communities’ culture.

The commodification of attention

Nobel Laureate Herbert Simon theorised the “attention economy” in 1971, stating that ‘a wealth of information creates a poverty of attention.’ He identified attention as the finite resource that limits action in information-saturated environments. Attention has emerged as the currency of the digital era where platforms compete for user engagement by deploying algorithms designed to retain monetisable eyeballs. An unending stream of short-form videos ensures that stimulating material keeps individuals scrolling, transforming focus into a coveted commodity. On average, TikTok users spend 58 minutes daily on the platform, but only 1.7 seconds viewing each piece of content, with teenagers toggling between apps every 44 seconds.

Social media platforms have built trillion-dollar enterprises by monetising the extraction of human attention. Platforms offer free services while harvesting personal data (browsing patterns, micro-interactions, location, emotional states) to build behavioural profiles enabling micro-targeted advertising, sold in real-time programmatic auctions. These platforms use variable reinforcement schedules (the same mechanism that makes gambling addictive) through notifications, likes, and algorithmic content serving as unpredictable rewards triggering compulsive engagement

. Shoshana Zuboff’s framework of “surveillance capitalism” calls this converting raw behavioural data into ‘prediction products’ sold to advertisers seeking to influence future purchases. Social media ad revenue grew +36.7% in 2024, with Meta, Google, and Amazon together representing 62% of total worldwide digital ad spending in 2026. Deloitte found that social platforms capture over 50% of US ad spending, with 63% of Gen Z and 49% of Millennials saying that social media ads are most influential on purchasing decisions.

Retail media has emerged as a force in the advertising ecosystem by capitalising on first-party data but does not inherently address the broader issue of attention attrition. Retail media is becoming a priority for department stores, with David Jones investing $250 million in its Amplify retail media arm, Falabella hosting Fmedia Day for brands and sellers, and Breuninger strengthening its retail media infrastructure to address customers and brands. Despite using proprietary data such as purchase histories, search behaviour, and loyalty programme insights, to enable hyper personalised advertising, it is increasingly insufficient to engage already overwhelmed consumers.

AI is simultaneously accelerating attention extraction and disrupting the ecosystem through which it is monetised. Fitch Ratings estimated a 15% decline in global search traffic as of June 2025 due to AI-generated summaries. Bain & Company estimated 80% of internet users receiving answers on search pages without clicking external links, reducing traffic for advertisers by up to 25%. This contributes to the advertising saturation that overloads consumers.

The paradox of saturation is that the more advertising floods the environment, the less each individual advertisement works, desensitising consumers. 74% of users cite intrusive ads as their main reason for using ad blockers, costing the advertising industry $54 billion globally in 2024. Procter & Gamble's 2017 decision to cut $200 million from digital ad spending had no measurable impact on sales. The causes identified included significant spend reaching bots and hyper-targeting creating frequency waste. Algorithmic glut and the relentless extraction of attention, evidenced by the online shopping overwhelm of 78% of Gen Z, is forcing an analysis of the nature of advertising itself.

The post-broadcast era: rebuilding shared meaning

The transition from twentieth-century mass broadcasting to hyper-personalised targeting has fractured the cultural infrastructure that sustained a cohesive monoculture. Historically, universally experienced media and advertising served as shared touchstones that fostered collective discourse; for instance, IKEA's 2017 Game of Thrones mock assembly manual generated a unifying buzz experienced simultaneously by millions. Today, this connective tissue has been eroded by on-demand consumption, algorithmic precision, and platforms incentivised to cater to niche audiences. As traditional cultural gatekeepers have been ousted by engagement-driven algorithms, collective narratives have been replaced with individualised content, dismantling the mechanisms that enabled mass culture.

This dissolution of monoculture was stark by the summer of 2025, which lacked the overarching narratives of 2024’s Brat or 2023’s Barbie that saw retail activations surrounding these cultural moments. While disconnected trends like Pucci dresses and capri pants surfaced without mutual reinforcement in 2025, the era of algorithmic micro-trends like "cottagecore" and "mob wife" collapsed as consumers reject manufactured movements in favour of offline authenticity. As economic pressure and information overload dissolve shared context into individualised fragments, consumers and especially lonely younger generations, are turning to brands that offering the connection created by shared culture.

Culture is the pillar of economic infrastructure that generates trust and social cohesion required to legitimise institutions and ensure commercial transactions. In times of disruption, shared cultural foundation fosters the collective adaptability necessary for economic resilience. Like a power grid provides physical infrastructure, a cultural infrastructure provides the shared meaning for any overarching economic system to function.

Brands and retailers increasingly fill this vacuum as cultural gatekeepers with consumer purchasing decisions no longer driven solely by product features and price; rather, they are tethered to a brand’s cultural legitimacy. Failing to navigate this landscape can result in the social backlash and declining sales following Target's DEI rollback or the criticism surrounding American Eagle's culturally disconnected campaigns. As the metrics of short-term attention become less reliable, department stores must build long-term cultural capital, centring the social cohesion of their consumer base.

The business of belonging

The shift from broadcast persuasion to cultural belonging draws on theoretical frameworks, some that retailers have already been using, operating in concert. “Collective effervescence”, sociologist Émile Durkheim’s concept of unity and shared emotional energy generated by communal gatherings, is being used as a commercial mechanism. When individuals participate in shared rites, they transcend their individuality and produce a sense of collective identity. Brand-engineered analogues of this experience — limited-release queuing events, pop-up activations, community-only drops — trigger emotionally charged group experiences reinforcing brand association.

Pierre Bourdieu's cultural capital theory explains the feeling of knowing a brand's quirks and references which confers status on those who possess subcultural capital. Those who "get it" are elevated; those who don't, aspire to. Social identity theory explains that people partly build their sense of self based on groups they belong to, and this feeling is stronger when they are visibly differentiated from outsiders.

For brands, this produces consumers who feel elevated because others do not understand the reference. Gentle Monster commodified this exclusivity as a private joke with their Bratz collaboration. Absurdist references, including the egg packaging, created meaning understandable only to someone fluent in Y2K nostalgia, Korean fashion culture, and internet irony. Especially for Gen Z, this credentialing creates a strong sense of in-group belonging addressing their need for community.

New Balance: a case study in cultural repositioning

Cultural strategy around brand-driven community-building addresses a genuine need rather than manufacturing belonging. 54% of Gen Z favours brands that make them feel part of a community and 84% of this demographic are more likely to purchase from brands perceived as cool.

New Balance's trajectory from ‘dad shoe’ to Gen Z darling is one of the most studied cultural repositioning cases of the 2020s. Starting from $3.3 billion in revenue in 2020, the brand reached $9.2 billion in 2025, while Nike's revenue fell from $51.4 billion to $46.4 billion over a comparable period.

New Balance did not distance itself from the dad shoe aesthetic to appeal to Gen Z, it reframed its 1990s running heritage when nostalgic styles returned to fashion post-COVID. Curating partnerships with Aimé Leon Dore and Kith, whose community-embedded credibility introduced New Balance to younger and more diverse audiences, it also signed younger sports stars like Coco Gauff and Cooper Flagg to reposition the brand. New Balance maintained its authenticity and used cultural intermediaries to reposition it as ‘cool’ for Gen Z.

Department stores as the infrastructure of cultural belonging

We believe department stores have an underutilised asset in today's fragmented market: institutional continuity. While micro-trends evaporate rapidly and pop culture remains volatile, retailers with decades of brand history can provide stability. Rather than participating in fleeting cultural moments, department stores possess the capacity to function as platforms for multiple communities. Despite being commercially driven, department stores can partly fill the vacuum left by the demise of cultural gatekeepers that allowed the formation of a mass culture. They can strategically define and build on what authenticity looks like for their consumer base, knowing that its impact may not be fully quantifiable especially in the short term. This potential was exemplified by Le Bon Marché’s rock and roll exposition, which fostered intergenerational cultural engagement and shared experiences unintentionally.

The transition from a transactional environment to a cultural hub is quantified in the value of a department store’s retail media network. Culturally resonant networks offer brands an avenue to connect with increasingly rare attentive audiences, elevating a secondary revenue stream for department stores into an asset built upon cultural capital. Behavioural nudges and individualised AI recommendation systems only succeed if consumers are engaged in noticing them. As trust in conventional advertising wanes and AI systems intercept direct searches, capturing consumer focus requires broader relevance than personalisation.

Retailers like Gentle Monster and New Balance built rituals that resonated with communities aligned with what these brands strive to represent, letting influence flow from a sense of belonging. Department stores can leverage their unique institutional continuity to provide a focal point for communities to organise naturally in an increasingly individualised environment.

Credits: IADS (Anchita Ranka)

What: Strong workplace culture alone does not guarantee improved productivity, as operational barriers like unclear accountability and inconsistent expectations continue to undermine performance in retail.

Why it is important: As Millennials and Gen Z approach three-quarters of the global workforce by 2030, retailers that fail to align their culture and management practices with expectations around transparency, flexibility, and meaningful work risk losing the talent they need to compete.

The analysis argues that weak productivity is rarely a culture failure; it is an operational one. Unclear accountability, inconsistent expectations, and misaligned hybrid norms drain discretionary effort long before it reaches the work. Gallup's 2026 data puts a number on it: employee engagement has fallen from 23% to 20% since 2022, costing the global economy $10 trillion in lost productivity annually. The piece reframes what culture actually does. Its function is not to make people feel connected but to create the conditions under which work moves well: clarity about expectations, trust in leadership, and recognised contributions. With Millennials and Gen Z approaching three-quarters of the workforce by 2030, those conditions match what younger employees say they need. Organisations that build them into day-to-day management rather than treating them as a separate initiative hold on to the people who drive performance.

IADS Notes: The patterns the piece describes are documented in granular detail across recent industry research. Gallup's April 2026 State of the Global Workplace report found that global employee engagement has fallen to 20%, its lowest point since 2022, with management quality and leadership clarity identified as the primary determinants of whether organisations recover or continue to slide. Seramount's own January 2026 analysis traced unclear expectations, inconsistent accountability, and misaligned communication directly to burnout and disengagement that typically go undetected until performance has already declined. BCG's February 2026 productivity study of the UK retail sector found that the gap between leading and lagging retailers is driven more by structural and organisational barriers than by differences in technology adoption, reinforcing the argument that the issue is rarely what organisations have access to, but how they operate. HR Dive, writing in December 2025, documented the generational dimension: Gen Z and Millennial employees report high stress and elevated turnover risk when expectations around flexibility, transparency, and meaningful work go unmet. The Harvard Business Review, in January 2026, identified the most effective retail leaders as those who combine strategic direction with hands-on operational involvement, building the clarity, trust, and consistency that allow teams to perform at pace without burning through goodwill.

What’s missing when strong cultures fail to improve productivity

What: Agentic AI is accelerating a shift in enterprise data risk, exposing gaps in privacy, cybersecurity, and governance as autonomous agents operate across workflows.

Why it is important: The shift to agentic AI makes structured data governance, real-time monitoring, and cross-functional collaboration non-negotiable for retailers seeking to manage the new risk vectors that autonomous systems introduce.

BCG's analysis finds that most enterprises still manage data risk through siloed functions: privacy handles regulatory compliance, cybersecurity handles breach defence, and governance handles classification. Yet a single agentic AI deployment now simultaneously triggers all three, alongside regulatory and performance implications. As autonomous systems plan, decide, and act across workflows with limited human oversight, they introduce five interconnected risk categories: propagation, persistence, autonomy, emergence, and third-party exposure. Data quality compounds the challenge: where poor data once produced inaccurate reports, it can now trigger real-time decisions and downstream processes before human intervention is possible, elevating data quality to a governance priority in its own right. BCG's recommended response is a taxonomy-driven framework that integrates policies, controls, and architectural choices across functions, with monitoring extending beyond technical uptime to track how agents access data, how access rights evolve over time, and where interactions involve sensitive datasets. Nearly half of enterprise leaders surveyed expect cybersecurity spend to rise over the next three to five years, with investment concentrating in data security, identity and access management, and cloud security. Organisations that embed enforceable standards and clear accountability now will scale agentic AI with confidence; those that wait will find that unmanaged data risk, not technology, constrains their ambitions

IADS Notes: Where BCG addresses enterprise architecture, recent retail-specific reporting documents the consequences already playing out on the ground. RH-ISAC, writing in April 2026, found that the rapid deployment of autonomous AI agents is exposing retailers to cybersecurity threats that existing frameworks were not designed to address, identifying adaptive governance and real-time monitoring as baseline requirements rather than enhancements. The Harvard Business Review, across its March and April 2026 issues, drew a direct comparison between AI agent behaviour and malware, arguing that integrated security strategies and comprehensive staff training are now prerequisites for safe deployment. Inside Retail's April 2026 analysis showed that agentic commerce is already shifting competitive standards and customer relationship management, making data governance and agent-ready APIs commercial priorities rather than purely technical ones. The Robin Report in August 2025 illustrated the financial and operational consequences of prompt injection attacks — a category of threat that exploits AI's autonomous decision-making to manipulate systems and amplify existing risks. Bain & Company's September 2025 technology report placed the governance gap in quantitative terms: despite AI-driven operational gains, only 18% of companies have achieved mature digital core security, confirming that investment in risk management and cybersecurity infrastructure must advance in step with capability for agentic AI to deliver sustainable value in retail.

Agentic AI is rewriting the rules of data risk management

What: AI agents are advancing rapidly across e-commerce, but their effectiveness is limited by fragmented data systems and the need for structured, high-quality information.

Why it is important: Ensuring AI agents have access to structured, reliable data is now critical for customer satisfaction and brand visibility in an AI-driven retail landscape.

AI agents are advancing rapidly across e-commerce, handling product search, offer comparison, customer service, and order tracking. A persistent limitation emerges in the post-purchase phase, however: AI responses are often imprecise or inconsistent, not because the models are flawed but because the data they rely on is fragmented.
Most companies hold the information AI needs — carrier statuses, delivery events, logistics incidents, customer service interactions. The problem is that this data is scattered across multiple platforms and stakeholders (carriers, OMS, WMS, CRM, marketplaces), making it difficult for AI to access and use in real time. The real challenge is therefore not the AI model itself but the consolidation and validation of the data it is fed. Emerging standards like the Model Context Protocol (MCP) address this by providing a standardised layer between AI agents and business systems, simplifying integration and improving response accuracy. Post-purchase processes represent a strong use case for this approach: high request volumes, structured data, and a clear need for immediacy.

IADS Notes: Liontree and Journal du Net in April 2026 found that accurate, well-governed product data has become a brand visibility issue as AI-driven shopping enters the mainstream, with BCG in September 2025 noting that AI can manage product data at scale only within robust governance structures. Debenhams' deployment of AI-powered post-purchase solutions in January 2026 illustrates the sector's wider effort to integrate fragmented operational data across returns and claims management. McKinsey in May 2026 and Emerge in April 2026 found that nearly half of shoppers now act on AI-driven recommendations, raising the floor for data quality and machine-readable content. Retail Touchpoints in January 2026 tracked the shift toward domain-specific AI models as a direct response to accuracy requirements. Journal du Net in July 2025 and Fashion Network in January 2026 documented measurable gains in efficiency and customer satisfaction where AI has been integrated into post-purchase processes.

AI agents in e-commerce: why data makes all the difference

What: The midyear 2026 global economic update forecasts slower growth, persistent inflation, and regional divergence, with major implications for consumer spending and retail strategy.

Why it is important: Persistent inflation and regional divergence require retailers to rethink pricing, sourcing, and investment strategies to sustain growth and profitability.

Euromonitor’s midyear 2026 global economic update points to a challenging macroeconomic environment for retailers worldwide. Slower growth, ongoing inflation, and significant divergence between advanced and emerging markets are reshaping consumer spending patterns and retail demand. Currency volatility, supply chain disruptions, and geopolitical risks continue to pressure pricing and profitability, forcing retailers to adapt sourcing and investment strategies. As real income growth and consumer confidence fluctuate, value-seeking and cautious spending are becoming more pronounced, particularly in discretionary categories. Retailers are responding by balancing digital and physical channels, accelerating omnichannel innovation, and focusing on operational efficiency to maintain resilience. The outlook highlights the need for agile leadership, robust scenario planning, and a willingness to innovate in order to navigate uncertainty and capture growth opportunities in a fragmented global market.

IADS Notes: Euromonitor (December 2025) highlights that the 2026 global economic outlook is marked by persistent uncertainty, inflation, and regional divergence, requiring retailers to balance digital and physical channels to sustain growth. The Robin Report (April 2026) emphasizes that consumer power, technology, and new business models are reshaping retail, with operational agility and innovation becoming critical as retailers navigate a slower, more volatile macroeconomic environment. MBS (January 2026) underscores the importance of agile leadership, systematic upskilling, and balanced AI-human integration, noting that only 10% of retailers have successfully scaled holistic, cross-functional digital strategies in response to macroeconomic pressures. McMillanDoolittle’s Retail Innovations Report 2026 (May 2026) points to digital transformation, operational agility, and purpose-driven strategies as essential for resilience and sustainable growth in a complex retail landscape. The Retail Bulletin (March 2026) documents how Danish retailers like Magasin du Nord and Salling are adapting to evolving consumer expectations and macroeconomic headwinds through omnichannel innovation, experiential formats, and investment in local brands. Collectively, these sources illustrate that the global retail sector’s outlook for 2026 is defined by the need for agility, innovation, and a balanced approach to investment and channel strategy in the face of ongoing economic uncertainty and shifting consumer behavior.

2026 global economic mid-year update