Edge AI: Changing How We Interact With Our Smartphones

In the fast-paced world of mobile technology, Edge AI is starting to become more prevalent. As portable devices become more powerful, with organisations like Apple starting to embed AI into its offerings, the technology in use is starting to revolutionise how people use and interact with their devices.

Edge AI contributes to this, as a combination of artificial intelligence (AI) and edge computing that exists to enable devices to process data locally - without relying on cloud servers. It has been touted by leading organisations like NTT Data as making things like augmented reality games to real-time language translation faster and more efficient than before.

Likewise, NTT Data views Edge AI as opening up new possibilities for mobile-driven industries, from smart cities to mobile health apps.

In this interview with Paul Bloudoff, Senior Director of Edge Services at NTT Data, he explains what Edge AI is, what it means for the future of mobile technology and how it can make smartphones even smarter.

What is NTT DATA Edge AI?

NTT DATA’s Edge AI is the first fully managed service platform that includes all the systems, tools and capabilities required to enable AI at the industrial edge.

It addresses data discovery, collection and normalisation, integration, computational power, seamless connectivity and AI model management.

This innovative platform delivers smaller, task-specific AI models using real-time data collection and AI processing directly at the data source, speeding delivery and increasing efficiency of insights at the edge, reducing the connectivity and computation costs and complexity of competing AI solutions.

It breaks down Information Technology (IT) and Operation Technology (OT) silos by integrating all the systems, tools and capabilities required to deploy AI applications at the edge.

How is this different from AI platforms offered today?

While Generative AI (GenAI) and Large Language Models (LLMs) offer great capabilities, these technologies are impractical for industries – such as manufacturing – that require real-time, local decision-making.

Rather, NTT DATA Edge AI delivers smaller, efficient, task-specific AI models at the data source, speeding insights and increasing efficiency, reducing complexity, connectivity demands and computation costs.

Edge AI’s industry specific solutions allow for applications like predictive maintenance, digital twin and machine vision by enabling instantaneous and secure data processing and analysis.

Edge AI breaks down silos between IT/OT allowing for greater insights across the enterprise.

It can identify and begin collecting data from siloed data sources to feed dynamic AI models that drive insights from digital twins and give operators a better understanding of their unique production environments in real-time.

Why is Edge AI needed?

The edge is becoming vital in IT infrastructures for making real-time decisions in OT environments, particularly when a business needs to analyse large amounts of data with ultra-low latency.

For example, in industrial settings, organisations apply sensors to mechanical assets for continuous monitoring and algorithms detect anomalies to drive for predictive maintenance insights and digital twins.

On-premises compute resources are also being leveraged to keep systems safe from cyberattacks. 

All these factors are driving the industry to adopt Edge AI solutions.

In manufacturing, Edge AI solutions on the factory floor determine the health of a machine in real-time before a failure occurs, helping with predictive maintenance.

Drones and robotics for industrial operations are other areas that Edge AI can optimise.

Smart cities are also using Edge AI solutions to monitor safety and security, optimise traffic flows, and track environmental factors.

These real-time use cases are only enabled when the data collection and analytics are brought to the edge.

Is there a market need for this technology? 

Edge computing is becoming the next big battleground in AI driven by the need for real-time insights to proactively plan and solve challenges.

Interest in Edge AI is growing as industries discover new ways to automate business processes and unlock new opportunities for innovation, all while addressing concerns such as latency, security and cost reduction.

Additionally, analysts predict that worldwide spending on edge computing is expected to be US$232bn in 2024, an increase of 15% over 2023, according to a March 2024 forecast from IDC.

Combined enterprise and service provider spending across hardware, software, professional services and provisioned services for edge will sustain strong growth through 2027, the IDC report said, when spending will reach nearly US$350bn. 

Meanwhile, the 2023 Edge Advantage Report, which surveyed 600 enterprises across multiple industries, found that nearly 70% of enterprises are leveraging edge to solve critical business challenges, and eight out of 10 organisations expect their dependency on third-party edge services to grow over the next two years.

However, nearly 40% of those planning edge deployments are concerned that current infrastructure capabilities won’t be able to support the promise of edge.

Why are organisations struggling with AI at the edge and automation?

Companies are turning to Edge AI as it brings reliability and the power of AI models to where it is needed.

Edge AI provides task-oriented AI capabilities that can be completed at the edge without latency constraints enabling real-time decisions for efficient operations.

The number of sensors and IoT connected devices is growing, and this is driving the need for real-time analysis and data processing at the edge.

It complements existing GenAI and cloud computing infrastructures with actionable intelligence.

Companies investing in digital transformation solutions should look at how Edge AI solutions process data to get information to decision makers for proactive, efficient management of operations. 

What benefits can customers experience with Edge AI? Is it worth their time and investment?

Industries such as manufacturing, healthcare, transportation and logistics, energy and utilities and financial services are leading the charge in adopting AI at the edge.

These industries require real-time decision making based on data.

The ability to support automation, AI and the growing number of IoT devices are among the top reasons to use Edge AI.

With the real-time data processing and automation done at the edge and on the factory floor, enterprises see increased operational efficiency, enhanced security and improved sustainability compliance.

Therefore, it enables companies to be more agile in meeting operating needs while also expanding collaboration and data processing.

How is NTT DATA poised to capture this market opportunity?

NTT DATA is poised to capture significant market share through its dedicated IoT consulting and services business, which brings together 1,000 industry experts, hundreds of use cases from predictive maintenance, fleet management, connected factories, energy consumption monitoring and sustainability and has already trained over 500 sales experts globally to accelerate its Edge AI go-to-market efforts.

NTT DATA’s Edge AI deployment approach also allows clients to take advantage of a free 30-day discovery and diagnostic of their IT and OT environment.

The software auto-discovers assets with its vast library of pre-built OT interfaces.

After this initial stage, Edge AI software generates a comprehensive diagnostic report inventorying assets and data streams, including identifying security risks and vulnerabilities.

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