Woman using AI technology on smartphone to track fridge inventory

How retail will need to adapt for different agentic futures

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10 minute read 21 Aug 2026
Related topics
Retail
Consumer & Health
AI

AI could transform retail and challenge a sector that has traditionally been human-centric.

In brief
  • AI is reshaping how retailers operate and engage with customers.
  • Success tomorrow will depend on the choices retail leaders make today. 
  • Exploring different future scenarios for AI will support resilience and growth.

Related content

Retailers already recognize the transformational potential of AI. It is having a broad and deep impact across the enterprise by reshaping cost models, customer relationships, workforces and the competitive landscape. Despite recent geopolitical disruption and macroeconomic uncertainty, AI remains a dominant factor in retail investment strategies. The May 2026 EY CEO Outlook Survey found that 80% of retail leaders planned on increasing their investment in AI in the year ahead, despite clear pressures on cost and price. The survey also demonstrated continued business confidence in the ability of AI to deliver growth, with 80% of retail leaders also expressing optimism in their ability to scale the responsible use of AI and customer data across functions.

 

But this optimism is tempered with caution. Retail leaders have a tendency toward pragmatism, and AI, like any other technology, could find itself in its own hype cycle. AI investment also comes with both privacy and cyber risk. The shift toward AI and other digital technologies is increasing retail exposure to cybercrime, with the CEO Outlook also finding that 24% of retail leaders identify cybersecurity and data privacy threats as a top risk to their business in the coming year. This creates a paradox for retailers in which the technology most likely to unlock growth may also be the one most likely to expose weaknesses in strategy, governance and operating models.

 

In planning for the future change that AI will bring, retailers can take a more nuanced approach. Rather than just considering opportunities, or challenges, associated with AI, retailers can consider a range of AI scenarios to build an understanding of where common themes should be addressed to ensure the best path forward.

 

In anticipating different scenarios, EY teams have looked at AI through the lens of a “four futures” methodology. This approach, developed originally by Jim Dator at the University of Hawaii, applies four radical alternative future scenarios to consider:

  • Constraint (discipline or limitations): Economic, social, environmental or political factors restrict growth and hold back progressive development. Legacy systems, lack of right capabilities, silos and poor data quality also limit the ability to scale.
  • Growth (continuation or business as usual): The current trends of end-to-end AI investments continue with minimal disruption, leading to progressive advancement.
  • Transform (a paradigm shift): A transformational change takes place, leading to a fundamental social and economic reorganization around new values and technologies.
  • Collapse (a systemic breakdown): A small number of technology platforms command powerful models and business access is priced at a premium limiting access to fewer larger retailers.

Retailers are already integrating AI into their business infrastructure as they prepare for an agentic future. But the investments they make today may not pay off equally in different scenarios. Winning retailers will be those that can pair technology ambitions with strategic clarity across different outcomes.

Watch our short film about the four possible futures of AI in retail

Store clerk uses facial recognition on female customer for payment
1

Chapter 1

Constraint: AI for efficiency, humans for trust

83% of information and communications technology (ICT) professionals working in retail believe that their organization requires greater understanding of risks relating to AI.

In a constraint future scenario, regulatory interventions and repeated cyber breaches lead to a loss of trust in the ability of AI to deliver on the expectations retailers have today. AI deployments struggle to scale against a backdrop of uneven regulation and escalating cyber threats. Public trust becomes harder to earn but remains easy to lose. Retailers focus AI deployments on lower-risk, higher-control applications in back-office functions such as finance, procurement, inventory management and logistics. Rather than seeing the benefits of scale, customer-facing AI solutions deliver pockets of innovation in benign regulatory environments.

Even amid today’s excitement surrounding AI, there are many factors that could constrain future growth. Regulators are imposing new safeguards such as the EU AI act, China’s comprehensive, state-driven AI governance and state-level interventions in the US.

As policymaking acts to rein in the legal applications of AI, the development of illegal applications is accelerating. The World Economic Forum’s Global Cybersecurity Outlook 2026 reports that 87% of organizations are seeing an increase in cyber risk based on AI vulnerabilities, with 94% seeing malicious AI as significantly affecting cybersecurity in 2026. These vulnerabilities have been keenly felt in retail where customer data, payment systems and legacy technology infrastructure combine with a complex supply chain ecosystem to present a large and growing digital attack surface.

Most importantly, consumer trust remains in the balance, with the EY AI Sentiment Study highlighting multiple concerns in how AI is regulated and deployed.


However, a constrained AI future should not be considered a scenario where retailers cannot seize opportunities to grow their business. Retailers can still thrive by focussing AI where returns are measurable and risk is manageable. Factors such as governance, cybersecurity and responsible AI can be shifted beyond compliance to become strategic capabilities. Reinvestment in other capabilities, especially human expertise, will bring competitive advantage and trust will be the currency which drives financial growth.

Watch our short film about how hypothetical retailer “SuperNova Grocer” navigates a constrained future

Asian man is using facial recognition for payment
2

Chapter 2

Growth: AI integrates, humans delegate

64% of ICT professionals working in retail believe that their organization is already achieving measurable ROI from its AI investments.

How EY can help

In a growth future scenario, the improvements that AI has already delivered keep coming. Pilots scale. Retailers’ efficiency grows. Customer engagement flourishes. Machine learning (ML), generative AI (GenAI) and agentic tools integrate, managed by orchestration agents that radically reduce human intervention. The agentic commerce infrastructure being developed today reshapes tomorrow. Consumers habitually integrate AI into customer journeys. Agentic commerce becomes normalized and a growing number of category purchases are almost entirely conducted by AI assistants as consumers delegate more choice to agents. We are already on the path to AI playing a growing role in purchase decisions, with Adobe reporting that traffic to retail sites from GenAI tools increased by 693% year on year during the 2025 holiday shopping season.

 

This transforms the competitive landscape. Retailers no longer just compete with each other for market share. They also compete with platforms, startups and brands for visibility, preference and recommendations in an agentic ecosystem that curates choice.

 

There is clearly momentum for a growth-led future and Morgan Stanley has predicted that, by 2030, AI agents could account for US$385b in US ecommerce spending. Retail leaders agree, with the EY CEO Outlook Survey finding that 77% are preparing their business for a wave of agentic commerce.

 

Employee behavior is also adapting. The EY Work Reimagined Study found that 29% of retail employees use AI every day at work, while 32% also use personal AI tools to support work tasks. In a growth scenario everything that AI can automate will be automated, from supply chain management through to purchase journeys and transactions. This may create challenges in how AI impacts employment. In 2024 the IMF estimated that 40% of jobs globally would be impacted by AI. Retail could be at the forefront of this as a major global employer. Unemployment, or underemployment, could lead to measures such as shorter working weeks or the introduction of Universal Basic Income which will have additional impacts on consumption patterns. Consumers themselves are also unsure about AI’s growth, balancing optimism with underlying concerns about how AI might impact them. 


Just as a constrained future can present opportunities, a growth future can also present challenges. Retailers will need to avoid mistaking AI access for advantage. As AI lowers barriers to entry, it will level the competitive playing field. Differentiation in retail will come from assets that AI cannot easily commoditize such as proprietary data, quality, price, physical presence and category dominance. Retailers will also make category distinctions between where agentic commerce can dominate and those where experience can guide human choices. A growth scenario will reward the retailers that can deliver algorithmic relevance for agentic transactions while deepening service, expertise and experience where human oversight still matters.

Watch our short film about how hypothetical retailer “Velatte Coffee” navigates a growth future

Carpenter in wood workshop using smart phone and working on project
3

Chapter 3

Transform: AI ecosystems augment human networks

25% of ICT professionals working in retail believe GenAI will radically accelerate their digital transformation, redefining what is possible.

In a transform future scenario, AI does not just optimize retail, it redefines what retail is, driving exponentially efficient enterprises that are largely automated. Mass adoption leads to a root and branch transformation which shifts value propositions away from selling products towards diversified business operations, with retailers finding new sources of value from their assets and infrastructure.

The transformative effect that AI can bring in retail is reflected in the breadth of functions it can deliver value to, with retail leaders seeing capability improvements spanning all aspects of their business.


In a transform scenario, retailers don’t just sell, they use their capabilities to help orchestrate ecosystems that manage products, services, data, logistics, finance, technology and media. Retail support functions become sources of B2B revenue, or they are outsourced to other ecosystem players. Sector boundaries blur, and successful retailers could make most of their profits outside of retail activities.

To increase their influence in this wider business ecosystem, large retailers will combine their scale advantages with technology alliances for both efficiency and engagement. Retail capabilities will become tradeable assets, forming B2B solutions that support micro-entrepreneurs and gig workers as workforces are radically reshaped by underemployment. This may seem radical, but the latest EY CEO Outlook Survey highlights that many retail leaders today are focusing on how to deliver new, and different, value back to their business.

Retail leaders see future opportunities and threats from outside their sector

84%
84%
of our store network will be transformed to better support cross-channel engagement models and to deliver value beyond sales of products.
70%
70%
of my business will see profitable growth driven by noncore activities such as retail media, subscriptions, services or marketplaces.
52%
52%
competitive dynamics are changing, which is increasing competition for my business from outside traditional retail.

Success in a transform scenario comes from adaptability and interoperability. Retailers will have the opportunity to decide which capabilities can scale beyond their own enterprise, as well as where to lead ecosystems and where to let others lead. Assets that can bring a competitive advantage can become tradable services. Assets that cannot should be outsourced. This collective approach will enable broad networks of businesses, creators and service providers to thrive as the competitive landscape becomes a collaborative one.

Watch our short film about how hypothetical retailer “Ideran Living” navigates a transform future

Customer at the checkout counter of a gift shop Customer at the checkout counter of a gift shop
4

Chapter 4

Collapse: Platforms dominate, humans differentiate

83% of ICT professionals working in retail believe their organization requires greater understanding of risks relating to AI.

Collapse does not mean that AI, or retail, disappears altogether. Instead, control of AI becomes concentrated. A small number of technology platforms command powerful models, and business access is priced at a premium. For retailers, this means that the AI tools delivering scale and growth are limited to those with significant budgets and wide market presence. Larger retailers continue to thrive by paying a premium, and ceding data and engagement to their technology partners. This transforms mass market retail into a fulfilment channel which sacrifices margin and control for volume and growth. Those retailers unable to pay the premium to access AI must seek out lower cost options or find new ways to differentiate by stepping away from scale into niche value propositions focused on communities, service, experience and human touchpoints. In this scenario, many mid-market retailers are acquired by technology players or larger retailers to deliver synergistic scale.

There is mounting evidence today that AI, and retail, is in a wave of consolidation. According to recent valuations, the top five companies in the Nasdaq 100 accounted for more than the value of the other 95 companies represented combined. Similarly, in retail, the market capitalization of the top five global retailers accounts for around two-thirds of the top 20.


At the same time, clear and transparent governance of AI remains relatively nascent. The EY Global AI Sentiment Survey found that consumers divide responsibility for AI misuse almost evenly between governments (24%), the organizations that deploy AI systems (22%) and the organizations that build AI systems (22%). Either way, trust in responsible deployment is outweighed by concerns.


Successful retail strategies in this scenario divide between retailers who can afford to deploy complex AI tools, and those who cannot. Larger players can use AI to accelerate efficiency, support engagement and enable scale to deliver growth on thin margins. Smaller and more premium retailers will benefit from focusing on what dominant platforms struggle to replicate, by building their businesses around authenticity, expertise, local relevance and human service. Scaling these value propositions may be difficult but these retailers will enjoy greater margin, and control.

Watch our short film about how hypothetical retailer “Maison Sivelle” navigates a collapse future

How to shape the four futures with confidence

91%
91%
of ICT professionals working in retail believe their organization requires a better understanding of how different transformative technologies can be combined to create value.

No retailer can predict the future, and elements of all four scenarios are likely to emerge at different times and across different markets, categories and functions. Some categories will shift quickly toward agentic commerce while others remain human-led. Some AI capabilities will be accessible through interoperable ecosystems while others are controlled by dominant technology platforms. The key imperative for retailers is to build strategic responses that span different scenarios to support resilience and growth. There are three actions spanning all four futures that retailers can consider:

  • Strengthen foundational tech infrastructure and design for interoperability: AI-readiness is not just about deploying AI, but about ensuring business infrastructure can accommodate and scale new tools easily.
  • Build governance, cyber resilience and trust from the start: Trust from regulators and consumers will be a key factor in defining the success of any AI deployment.
  • Protect and grow human differentiation: Whether AI removes competitive barriers, or becomes relegated to back-office functions, talent, culture, service and experience will continue to distinguish retailers and human interactions will matter more than ever.

Summary 

AI will be crucial in defining the future course of retail, with investments today shaping the retail landscape in the coming decade. To understand its implications, AI should be considered through the lens of different future scenarios to build an understanding of where common themes should be addressed to ensure the best path forward.

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Authors

Related topics
Retail
Consumer & Health
AI

EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients.