Surf, don’t drown: How retailers can ride the AI wave successfully

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As retail becomes a real-time business powered by constant connection, artificial intelligence is opening new opportunities to help retailers respond faster, operate more intelligently and deliver better experiences for shoppers and employees alike. But as AI evolves from predictive tools to generative and agentic capabilities, many retailers are finding that ambition alone is not enough. The challenge is no longer whether AI has value. It is how to apply it in a way that is practical, secure, scalable and aligned to the realities of modern retail. For retailers looking to move beyond experimentation, success will depend on building the right foundations for long-term business outcomes.
Opportunity and challenge
Retail now operates in real time. Customer expectations shift quickly, digital and physical channels are increasingly connected, and store and fulfillment environments need to respond with greater speed, accuracy and resilience than ever before. In that context, AI has become more than a technology trend. It is increasingly seen as a way to support smarter operations, more connected experiences and better decision-making across the retail business.
The opportunity is clear. AI can help retailers personalize engagement, improve service, strengthen operational visibility and streamline tasks across stores, e-commerce, and fulfillment. Yet for many organizations, turning that potential into measurable value remains a challenge.
According to McKinsey, end-to-end AI transformation could deliver significant EBITDA uplift for retailers. At the same time, many organizations that have already adopted AI are still not seeing meaningful bottom-line impact. That gap highlights an important reality: adopting AI is not the same as embedding it successfully into day-to-day retail operations.
One common challenge is moving too quickly to advanced use cases before the business is ready to support them at scale. As AI evolves toward more autonomous and agentic models, retailers need more than experimentation. They need the right data, infrastructure, governance and operational alignment to scale securely and effectively.
“Retailers are under pressure to move quickly with AI, but success comes from connecting innovation to operational reality,” says Matthew Bertucci, Head of Sales, Lenovo Retail Solutions. “In retail, value is created when technology works reliably in the moments that matter most — for shoppers, employees and the business as a whole.”
That is why trusted foundations matter. In an always-on retail environment, businesses need solutions that are reliable, scalable and secure — supported by deployment models and services that can sustain long-term performance, not just short-term pilots.
Investment is clearly increasing. Lenovo’s CIO Playbook, developed with IDC, found that 92% of retail organizations in Europe and the Middle East plan to increase their AI budgets over the next 12 months, with growing interest in agentic AI. But increased spending alone will not guarantee stronger outcomes. What matters is whether AI is being implemented in a way that supports connected operations across customer engagement, stores, employees and fulfillment. 
Setting up for success
The retailers most likely to succeed with AI are those that treat it as part of a broader modernization effort rather than a standalone innovation project. That means focusing not only on what AI can do, but on how it fits into the wider retail ecosystem — from digital experiences and in-store service to employee workflows, IT support and fulfillment operations.
In practice, that starts with a clear view of where AI can reduce friction and improve performance in meaningful ways.
For some retailers, that may mean helping shoppers navigate products and promotions more intuitively. For others, it may mean equipping store employees with faster access to information, improving issue resolution, or reducing the operational burden on already stretched teams. In other cases, it may involve improving visibility across fulfillment or making store technology environments more responsive and resilient.
“The strongest AI strategies are built around clear business outcomes,” says Bertucci. “Retailers need to focus on where AI can improve service, productivity and performance in ways that can scale across the business.”
This is where structure becomes critical. Retailers need to validate use cases quickly, but they also need a clear path to scale. That requires solutions that can integrate with existing systems, support secure deployment and evolve alongside the business with minimal disruption.
A future-focused approach to AI is not just about adding new capabilities. It is about modernizing operations in a way that improves agility, productivity and profitability, while also supporting more sustainable ways of working over time.
From experimentation to better outcomes
As AI matures, the retail conversation is becoming more practical. The focus is shifting away from what AI could do in theory and toward where it can deliver better outcomes in everyday operations.
That may include conversational online assistance that helps shoppers find products more naturally, in-store tools that support product discovery and service interactions, or technologies that help employees work more productively and resolve issues faster. It can also extend to IT responsiveness, transaction efficiency, store uptime and smoother fulfillment processes.
The key point is that these are not isolated moments. They are connected parts of the retail experience.
“AI is most powerful when it fits naturally into the retail experience,” Bertucci notes. “That means supporting customer engagement, employee enablement and store operations in ways that feel seamless and practical.”
This is why tailored deployment matters. No two retailers operate in exactly the same way and no single AI journey looks the same. Success depends on understanding the specific pressures, systems and opportunities within the business, then applying the right mix of solutions to address them.
For retailers, that creates an opportunity to think more holistically about modernization. Intelligent, connected solutions can help improve experiences, increase productivity and support more profitable performance across the business. When built on reliable foundations and supported by secure deployment and accountable services, AI becomes more than an experiment. It becomes part of a smarter operating model.That model also has a future-facing dimension. As retailers modernize, they are not only looking to increase speed and performance but also to build more sustainable operations. Smarter infrastructure, better visibility and more efficient workflows can all contribute to reducing waste and supporting more responsible growth over time.
Building for the future of retail
Retailers do not need to chase every new AI development to stay competitive. But they do need a clear approach to building for what comes next.
The businesses most likely to benefit from AI over the long term will be those that balance innovation with trust — modernizing on reliable foundations, scaling securely and keeping a clear focus on outcomes. In a real-time retail environment, that means using AI to improve not only customer engagement, but also employee effectiveness, operational resilience and overall business performance.
As Bertucci says: “Retailers do not need AI for AI’s sake. They need practical innovation they can trust — solutions that enhance engagement, strengthen operations and scale in ways that support the future of the business.”
The AI wave is moving fast. The retailers that ride it successfully will be the ones that combine ambition with a strong foundation, using AI not as a headline, but as a tool to create more connected, resilient and future-ready retail.
Explore how Lenovo Retail Solutions helps retailers modernize with intelligent, connected solutions that improve experiences, increase productivity and support more sustainable growth.
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