How IoT SaaS Platforms, Cybersecurity Facilitate Better AIoT Services

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Market research company, Research and Markets, has published a report on the global artificial intelligence of things (AIoT) market. The report estimates the AIoT market will reach $83.6 billion by 2027, growing at 39.1% CAGR.

AIoT is an important addition to IoT services. AI improves IoT through machine learning. It automates data processing systems and converts raw IoT data into useful information. Meanwhile, IoT complements AI through device connectivity, data exchange, and signaling. The fastest-growing segment within AIoT is the AI-enabled edge device market.

By 2027, AIoT solutions would have improved operational effectiveness and the value of machine data by up to 28%. AIoT key applications include data services, asset management, and immersive applications. It’s also used in process improvement, next-gen UI and UX, and industrial automation.

One of the key drivers of market growth is the increasing integration of AI in Information and Communications Technology (ICT). As AI continues to develop, experts believe that the technology will transform applications, communications, commerce, and content. With AI used in IoT, for example, organizations can have more organized information for data analytics. This could help in better decision-making and more effective implementation of smart cities in the future.

Another growth driver is “thinking” networks and systems. Analysts estimate that IoT devices will increase from 14.4 billion in 2022 to 27 billion by 2027. Businesses using IoT will not be able to manually monitor their IoT installations. So, they’ll need to rely on systems capable of automated monitoring and independent problem-solving.

With AIoT, AI is embedded in infrastructure components like chipsets, programs, and edge computing. Organizations can then use custom APIs to achieve interoperability between devices, apps, and systems. These thinking systems and networks focus on optimizing operations and extracting value from data.

IoT SaaS Platforms and Security Challenges

AIoT relies on an efficient IoT management system. This is where IoT SaaS platforms come in. IoT SaaS apps help facilitate communication between sensors, digital devices, and other web-based systems connected to the entire network. A good example is facility management software. Through sensors communicating with software, facility management apps are able to regulate lights and other utilities. When people start to leave a manufacturing or production area, for instance, sensors and apps communicate to down-regulate utilities; thus, lowering energy consumption and operating costs.

However, the improvements and efficiencies that come with AIoT and IoT also come with challenges. The top concern is data security. Security and IT teams will need to develop protocols on how to properly manage devices and access management.

As IT professionals said, SaaS misconfigurations are serious issues businesses need to address. The problem stems from a lack of visibility and too many departments with privileged access. Also, there could be employees using unofficial apps and devices (known as Shadow IT) that increase the risk of SaaS misconfigurations.

IoT SaaS platforms are also vulnerable to misconfigurations. Compromised endpoints can easily lead hackers into the system. Moreover, they could remain in the system for several days or even months without being detected. By the time security teams find out, the hackers have already exfiltrated large volumes of data. Breaches could happen without the security team even knowing that someone has already infiltrated their systems.

According to one study on cybersecurity, businesses need to leverage AI and automation in fighting hackers. These advanced features have helped businesses save more than $3.05 million on average in breach costs compared to companies that haven’t implemented them.