In an era where productivity is critical, industries like logistics, healthcare, retail and manufacturing are increasingly turning to edge AI – a technology that merges the intelligence of artificial intelligence with the immediacy of edge computing.
Cliff Chang, Eastern Europe and South Africa Senior Regional Account Manager for CipherLab, explains: “Fast-paced environments demand instant decision-making. The longer it takes to process data, the greater the risk of delays, errors and lost productivity. Edge AI brings the power of data processing directly to the device, cutting out the constant back-and-forth with the cloud.”
Why edge AI matters
The explosion of IOT devices has put unprecedented pressure on traditional cloud-based architectures. Each sensor, scanner and connected device generates a constant stream of data, and sending all that information to the cloud for processing can lead to latency, higher bandwidth costs and privacy risks.
Chang says the difference between cloud AI and edge AI is simple. “Traditional cloud AI requires data to be sent to remote servers, processed and then sent back to the device. Edge AI processes data locally on the device itself. This enables real-time decision-making, reduces bandwidth usage and ensures data privacy because the information doesn’t leave the device. In industries where internet downtime is common, often owing to power outages – like here in South Africa – this is a game-changer because you don’t need an external network to transmit data.”
This localised processing is particularly valuable in scenarios where every second counts – such as warehouse picking and filling, gate security checks and retail inventory management.
The business impact
Take a warehouse floor operator who previously had to manually key in batch numbers. Now, with AI-powered scanning devices, they can simply scan a label or bar code, and the AI instantly retrieves the necessary information.
“We’re talking about eliminating multiple manual steps,” Chang notes. “That’s fewer errors, faster processing and a more productive workforce. By automating processes and reducing human error, businesses save time and money while improving accuracy.”
AI features such as real-time data capture, bar code recognition and intelligent automation free staff from repetitive data entry tasks, allowing them to focus on higher-value work.
Real-world use cases
AI-powered edge devices are already making an impact in:
- Supply chain optimisation – Scanning and verifying goods instantly, even when offline.
- Predictive maintenance – Analysing equipment performance in real-time to prevent breakdowns.
- Retail inventory management – Tracking stock levels accurately without manual intervention.
- Gate security applications – Instantly validating and recording credentials at entry points.
- Logistics – Equipping delivery drivers with tools to update shipment data on the spot.
In Taiwan, the technology is also used for automated ticketing of road users – capturing licence plate details instantly without the need for manual input, dramatically reducing processing time.
Integration and local support
A frequent concern for businesses is whether new AI-enabled devices can integrate with their existing, often legacy, systems. Chang stresses the importance of selecting hardware that can do just that: “Integration is a key factor. A device should be able to slot into your current workflows and systems without forcing a complete overhaul.”
CipherLab’s long-standing relationship with Kemtek – spanning over two decades – ensures South African customers get local sales, technical support and stock availability without delay. Training, demos and rapid deployment are all handled locally, backed by direct vendor support when needed.
Challenges to overcome
While the benefits are clear, Chang points out that businesses must plan for:
- Staff training – Ensuring users know how to get the most from the tools.
- Data security – Keeping devices updated with the latest security patches.
- Life cycle management – Replacing or upgrading devices when support ends.
“Edge AI is a powerful enabler, but it’s only as good as the people using it and the systems supporting it. Businesses that invest in training and life cycle planning will see the best returns.”
A future built on speed, accuracy and autonomy
For industries where time, accuracy and cost efficiency are critical, edge AI isn’t just a technological upgrade – it’s a competitive advantage. By keeping intelligence at the point of action, organisations can move faster, work smarter and remain productive even when connectivity is unreliable.
As Chang sums it up: “Edge AI allows you to collect, analyse and act on information instantly, right where it’s needed. That’s the future of real-time data processing – and it’s happening now.”
To find out more about edge AI technology in handheld devices, click here.
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