The retail industry is experiencing a period of dramatic change. Today’s consumers expect a fundamentally different shopping experience – both online and offline – and new technology is raising the stakes faster than many retailers can cope with.
Add in cost pressures from new tariffs, restrictive trade policies, and tough economic conditions, and it’s clear why many retailers are making sweeping changes to the way they operate to increase revenue and improve margins.
These changes include eliminating data silos, introducing AI to make operations and marketing more effective, and deploying more IoT devices – but these developments risk introducing complexity and vulnerability into the network they all rely on.
Retailers Are Reuniting Long-Lost Data
According to IBM, more than four in five enterprises (82%) say that data silos disrupt their critical workflows, and it’s not hard to see why.
When data is isolated, there’s no comprehensive visibility across functions and departments. Without visibility, it’s difficult for retailers to make workflows more efficient and uncover insights on how to increase margins and operational resilience.
Data silos also impact retailers’ ability to provide seamless omnichannel customer experiences, and to gain the 360-degree customer view that’s needed for stand-out service and effective personalized marketing.
This lack of customer visibility, and its effect on customer service, matters. Nearly a quarter of consumers will stop purchasing from a brand after only one bad experience, and 59% of customers say customer service is more important than price.
Intelligent Data Integration and Store Management
Like almost all other sectors, retailers are exploring how AI can help them drive efficiencies.
Some retailers are using AI to intelligently connect data silos. This allows users to interact with complex datasets using natural language queries, and get business and customer insights back in minutes or even seconds.
Others are using AI to dynamically manage operations within individual stores, instead of relying on the ability of managers to oversee everything at once, or on generic company-wide insights which may not be applicable to every location. For example, AI can:
- Prioritize urgent tasks during a rush
- Automatically re-order stock when levels are low
- Assign workers depending on their efficiency at different times of day
- Make predictions about buying behavior and manage stock accordingly
AI Is Improving the Success of Marketing and Speeding up Customer Service
Since AI has the capacity to analyze far bigger datasets than humans can, it’s extremely valuable in examining customer behavior for marketing purposes. For example, AI-powered social listening can give wide-ranging insight into consumer views on a retailer’s products, marketing, and customer service.
AI is instrumental in creating more focused and hyper-personalized marketing, as it can analyze large quantities of data for better targeting, segment audiences with fine granular detail, and dynamically adjust marketing and pricing tactics depending on the results. This can be a powerful tool to boost sales, particularly when it’s combined with AR and VR which allow customers to explore products from their homes.
We’re also seeing the deployment of increasingly intelligent chatbots, which can answer customer queries, solve problems, and help customers research, compare, and choose products. The fast responses that chatbots can provide are attractive: more than half (51%) of customers say they prefer interacting with bots over humans when they want immediate service.
Retail IoT Deployments Continue To Grow
The global IoT in retail market size is projected to grow from $70.1 billion in 2025 to $350.9 billion by 2032. Retailers are increasing their use of IoT to help improve supply chain visibility, use resources more efficiently, keep stock levels steady even when there are spikes in demand, and reduce stock lost to theft and fraud.
IoT use cases in retail include:
- RFID tags and wireless sensors to track products across the supply chain and monitor stock levels within warehouses and stores in real time
- Smart shelves which use weight sensors, cameras, and RFID tags to monitor and automatically replenish products when stock is running low
- Connected equipment like HVAC and refrigeration systems to predict which equipment needs maintenance, preventing technical failures and minimizing energy consumption
Retail Networks Are Becoming More and More Complex
From a network perspective, these developments paint a hugely complicated picture.
Data silos often reside in different locations, and AI and analytics systems may be spread across more than one cloud. Depending on the size of the retailer, physical locations like stores and warehouses might have thousands of POS and IoT devices. Then there are enterprise apps like CRM, ERP, e-commerce, POS, logistics and inventory systems.
And of course, all this information and all these apps, systems, clouds, and locations need access to each other.
That’s why, as their business models and the technologies they use have evolved, many retailers have ended up with a tangled mix of network links and connectivity types.
This complexity leads to a networking environment that’s labor-intensive to manage – but that’s not the only problem.
Achieving comprehensive visibility over a complex, piecemeal network is challenging at best, if not downright impossible. Without this oversight, it’s hard to optimize network performance, manage connectivity costs, and keep the network secure – and it’s much tougher for the network to flexibly support wider business strategy too.
The IT team may be drowning in the huge number of alerts that disparate networks produce on a daily basis. It’s difficult for employees to work out which ones need urgent attention, which prevents them proactively managing the network to avoid problems, and increases the risk of downtime.
Downtime Is Expensive for Retailers
And the implications of this connectivity failing, or even just running slow, are significant.
Without reliable connectivity, sales in online and physical stores may not be completed. Retailers can’t monitor stock levels or track shipments, staff can’t access the apps they need to do their jobs, and business decisions are being made blind.
This, of course, costs retailers dearly. Every minute of downtime is estimated to cost the largest global companies an average of $9,000 per minute, or $540,000 every hour. This is made up of lost revenue, fines, penalties, and legal costs.
There are costs that are harder to measure too, like loss of customer confidence and reputational damage.
Retail Networks Are Not Prepared for AI
AI can be incredibly demanding of IT resources, and a staggering 86% of CIOs don’t think their networks are ready for it. The main issues are scalability, performance, and lack of bandwidth – all of which are critical for supplying AI systems with the huge quantities of real-time data they need to achieve their full potential.
The Impact of Security Breaches Is Growing
Retailers are an attractive target for cyber attacks, as they hold confidential customer data which can have catastrophic implications if stolen, and because an IT system shutdown can be disastrous for revenue. These threats can be valuable leverage for ransom payments.
A cyber attack in April 2025 on UK retailer Marks & Spencer’s, for example, forced the company to shut down its website and left it struggling to keep stores stocked. The incident affected sales badly, with online orders suspended for nearly two months, and click-and-collect services out of order for nearly four. The company’s pre-tax profits dropped by 99% for the first half of the year as a result.
With the proliferation of networked devices and a greater range of digital touchpoints, the average retailer now has a startling number of attack surfaces.
Many companies are still reliant on point solutions to secure their assets, like individual site firewalls and VPNs. These legacy approaches aren’t equal to the task of preventing the targeted, sophisticated AI-powered threats retailers are facing today, and leave inconsistencies and vulnerabilities that make compliance with standards like GDPR and PCI DSS difficult.
What’s Next for Retail Networking?
IT leaders, then are under pressure to achieve performance, responsiveness, and adaptability, and to do so consistently and securely across a wide variety of locations and territories – but networks are buckling under the stress of constant strategic and technological change.
In our next blog on this topic, we’ll explore what retailers should look for in their networks to meet the demands of this new environment, and to prepare for ongoing change in the future.