The Game-Changing Role of Generative AI in IoT Development

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By Michael Rivera, PhD

Generative AI is all the rage nowadays, especially with the introduction and viral growth of ChatGPT. Although applying generative AI in IoT isn’t the hottest topic, there are still untapped potentials to explore.

Artificial Intelligence of Things (AIoT) is the term that describes how AI can be used to optimize the functionality of IoT systems. Here, we’ll discuss three key use cases that generative AI enables for IoT.

Code Generation for Innovative Applications

Large language models can be trained to generate, complete, or combine software code sourced from code snippets or natural language descriptions. This can be applied to various tasks, domains, and programming languages, allowing software development teams to build innovative applications.  

Interestingly, many integrated development environments (IDEs) have already integrated generative AI capabilities like code completion, suggestion tools, and intelligent code analysis.

However, this doesn’t mean developers will be out of jobs soon. Instead, generative AI is simply an additional tool in the code generation toolbox. Some popular generative AI tools in code generation include GitHub CoPilot, Tabnine, Kite, and CodeComplete.

Controlling IoT Devices

Generative AI models can also be used to revolutionize the control of autonomous IoT devices like robots. For example, motion data can be obtained from sources like humans or animals to generate control logic and robot commands.

Rather than manually programming specific movements for each leg, generative AI can generate intricate, interconnected steps that enable complex, realistic walking patterns. 

That’s not all.

With machine learning in generative AI models, robots can autonomously generate sub-tasks. This eliminates constant human intervention, even for complex tasks.

There have been a few examples of this AIoT application already. For example, Alphabet’s Deepmind demonstrated how human and animal motions were used to teach robots to dribble a ball and carry boxes. 

Making IoT Devices More Social

IoT devices allow users to analyze and visualize data from a platform. In most cases, users access predefined sets of information like asset health and usage statistics. 

However, what if we can personalize interaction with IoT devices by making device communication a bit social?

Generative AI can make this happen in three ways:

  • Allowing the device to answer a user’s question about the data. So, instead of seeing predefined information the IoT device interpreted from data, users can also ask complex questions and get answers.
  • Ensuring users can use voice to change device settings.
  • The device might also use generative AI to generate answers to questions.


Although generative AI applications in the Internet of Things are still an area of ongoing research and development, there’s a lot of potential to revolutionize IoT systems. That’s why whoever develops the first convincing application may gain a competitive advantage. Thinaer is helping organizations in several industries drive digital transformation through artificial intelligence and the Internet of Things. Do you have custom AIoT applications in mind? Schedule an exploratory call with our team today, and we’ll be happy to discuss how we can help!