IoT devices generate vast amounts of data with significant potential value. AI can analyse this data across various environments, from cloud data centres to network edge locations, and even directly on the IoT devices themselves. Each approach offers unique opportunities to extract insights and drive value from IoT data.
When we talk about AIoT, we’re specifically referring to the deployment of AI use cases directly on IoT devices. Running AI at the source offers a range of benefits, such as faster performance, better compliance, enhanced privacy and security, and often lower operational costs.
The concept of AIoT does not exist in a vacuum, and AIoT capabilities are only ever deployed onboard an IoT device in support of an AI Use Case that the device in question is required to support. The chart below highlights the AI Use Cases that most frequently feature on AIoT devices in 2033, based on Transforma Insights ultra granular AIoT forecasts. The influence of consumer markets is clear with the most frequently featuring Use Cases being Natural Language Processing, Chatbots & Digital Assistance (both often associated with Smart Speakers) and Image Processing & Analysis (often associated with Smart TVs).
Many AI Use Cases do, however, find traction beyond the core IoT applications that the casual observer might naturally associate with the AI Use Case in question. For instance, whilst Natural Language Processing might most obviously be associated with (A)IoT applications like Smart Speakers and Headphones, the same Use Case will also find traction in environments such as Vehicle Head Units and Televisions (in both cases to support voice control, for example).
The chart below shows what might, from the perspective of a vendor of AIoT Natural Language Processing capabilities (either hardware or software, or associated functions), be regarded as different kinds of opportunity for the Natural Language Processing AI Use Case in AIoT contexts. From this perspective, ‘Primary Opportunities’ and ‘Extended Opportunities’ are defined as follows:
The chart also shows (on the right hand axis) the percentage of IoT devices supporting specific IoT Applications that have AI capabilities onboard, and so are AIoT. Overall, it is clear that the concept of AI deployed on board IoT devices has significant potential, and often in contexts beyond those that might seem like the most obvious opportunities. The fact that many IoT applications will be only around 10-40% penetrated with AI capabilities by 2033 further underlines the potential.
