The retail industry, like most other sectors, is charging full steam ahead on AI – looking to harness AI’s promised transformative power to stay ahead of the competition. Retailers that survived the pandemic are no strangers to dramatically shifting business operations and adopting technology to meet evolving customer demands. Now, retailers in Asia-Pacific are increasingly turning to AI to gain a competitive edge as customers’ expectations shift yet again. In fact, IDC has forecasted that retail will be among the top five industries in APAC to spend the most on AI between 2022 and 2027.
The key to delivering seamless customer experiences in today’s retail world is having efficient, optimised, and secure IT networks. Emerging within the AI innovation space is AI networking. This falls under the broader concept of AI for IT operations (AIOps), which is crucial for enabling retailers to improve the efficiency and security of their networks.
What are AIOps and AI networking?
AIOps (or AI for IT operations), a term coined by Gartner in 2017, is a solution that uses big data and machine learning (ML) to automate and streamline IT operations processes such as anomaly detection and causality determination.
It refers to the broader infrastructure managed by information and operations teams. AI networking, on the other hand, is a term defined by Gartner in 2023 and is specific to the broader IT infrastructure related to wired, wireless, and WAN networks. While AI networking supports Day 0 and Day 1 functions, it is primarily considered to be a more efficient way to manage Day 2 network operations, through troubleshooting, optimisation, and enhancing IT administrative efficiency.
How AIOps and AI networking are changing the game for retailers
Today’s modern retail networks are supporting more users, cloud-based services, and IoT devices than ever before. This poses multiple challenges for IT teams, from ensuring seamless and secure connectivity across dispersed physical locations to providing timely troubleshooting support for networking issues and delivering optimal user experience while saving on costs and IT resources. AIOps and AI networking will be critical in helping retailers tackle these challenges by offering intelligent automation and AI-driven insights to help IT and networking teams to work faster, more efficiently, and with greater cost-effectiveness.
- Remote management of multiple stores. Today, it’s common to see centralised IT teams managing dispersed locations. With this in mind, AI networking features offer near-real-time visibility into network activity wherever it is taking place. This capability allows for the identification of connected devices, pinpointing sites experiencing LAN or WAN issues, and the automatic collection of essential data logs. IT teams benefit from AI-powered alerts that assist in triaging the most urgent troubleshooting issues.
- Accurate identification of issues. Just as ML models are adept at identifying patterns of behaviour and deviations from them, AI networking insights and alerts are instrumental in uncovering wireless, wired, and WAN gateway issues that traditional tools might miss. For instance, AI networking can identify the difference between a device that’s misbehaving due to a hardware failure or something intermittent that a firmware upgrade can fix.
- Improved user journeys. Modern customers expect not only products that meet their needs but also high-quality in-store experiences. Consequently, IT departments are tasked with providing exceptional guest and employee access in environments where technical expertise may be limited and on-site troubleshooting challenging. Advanced AI networking features address this challenge by suggesting ways to enhance network performance without the need for costly upgrades, thereby meeting operational expectations and improving customer experiences simultaneously.
Considerations for choosing AIOps and AI networking solutions
While every AIOps solution provides a degree of automation for IT efficiencies, the range of capabilities varies significantly across offerings. The most advanced solutions are equipped to handle Day 0 and Day 1 tasks, as well as Day 2 operations. Key features of a comprehensive solution for retail networking needs include:
- Intuitiveness and effectiveness. AIOps solutions should offer more than just a streamlined dashboard. Essential features include built-in natural language search for basic Day 0 activities, such as configuring a service set identifier (SSID) or setting up a guest network. For more complex requirements, better solutions automatically baseline the performance and behaviour of each location’s network without needing manual configuration of service level expectations. Essentially, retailers should look for a solution that enhances the efficiency of their entire team, from the most experienced members to newcomers.
- Ability to detect behavioural anomalies. Changes in behaviour are often precursors to device failures or security breaches. Retailers should seek an AI networking solution where the AI and ML are trained with data from thousands of deployments and millions of devices and endpoints. It should employ clustering technology to tailor insights based on the size of each location, the number of network devices, and daily client connections. By integrating external and internal data, an AI network tool might be able to provide precise insights to identify behavioural anomalies effectively.
- Actionable-insights generation. At its best, AI networking should go beyond basic number crunching and churning out lists of issues to resolve or opportunities to optimise. The best AIOps solutions present their findings as actionable recommendations. These might include adjusting Wi-Fi access point settings to reduce power usage or suggesting cable replacements to address wireless connectivity problems. Actionable insights like these will help retailers eliminate manual troubleshooting, guesswork, and lengthy forensics tasks.
- Full-stack zero-trust approach. The best solutions use AIOps and AI networking methods across the entire network infrastructure, enhancing both efficiency and security. AI-powered zero-trust features should provide detailed client information, monitor application access by IoT and guest devices, and detect behavioural changes. For instance, if a stationary point-of-sale (POS) device exhibits unexpected roaming behaviour, a premier AI networking solution would flag this as an anomaly, enabling IT teams to quickly identify and resolve the issue.
- AI built into the network architecture. The most effective AI solutions are integrated into the network architecture by vendors, covering everything from network devices to management platforms. This integration aims to reduce acquisition and maintenance costs, minimise manual configuration efforts, and shorten the time required for the organisation to develop proficiency. Integrated solutions are generally more effective in delivering valuable insights without additional costs.
In today’s retail environment, maintaining an always-on network offers a significant competitive edge. Retailers must consider how AIOps and AI networking can provide actionable insights, automate processes to liberate IT resources for strategic projects, and enhance overall business and competitive performance.