The incredible truth about AI in IoT

Artificial Intelligence (AI) is revolutionizing how companies interact with the Internet of Things (IoT), enhancing industrial processes, optimizing resources, and improving decision-making. However, it’s essential to distinguish between true AI systems and other technologies often labeled as such, such as Large Language Models (LLMs), which, while powerful tools, are not AI in its fullest sense.

IoT generates massive amounts of real-time data through sensors, connected devices, and monitoring systems. This is where AI becomes crucial, offering advanced capabilities to analyze, predict, and automate processes based on these data streams. For example, AI can optimize energy consumption in industrial plants by automatically adjusting equipment usage according to historical patterns and live data, learning as it goes.

Practical applications of AI in IoT

The integration of AI with IoT has enabled the development of applications transforming sectors such as manufacturing, transportation, and energy. Some use cases in 2025 include:

• Predictive Maintenance: By analyzing sensor data from industrial machines, AI can predict failures before they occur, reducing downtime and repair costs.
• Inventory Management: IoT systems equipped with AI can automatically track inventory levels and place orders based on projected demand
• Smart Cities: AI and IoT are used to manage traffic, optimize energy consumption, and enhance security in urban environments.

The truth about AI in IoT

In recent years, many solutions marketed as “AI” have flooded the IoT platform market. However, not all meet the criteria of advanced artificial intelligence. A growing trend is the offering of tools that are actually chatbots based on Large Language Models (LLMs) rather than real AI systems, even though they’re marketed as such.

These tools are presented as intelligent assistants capable of transforming processes, but their functionality is limited to tasks such as answering FAQs or generating text based on pre-existing patterns — for example, based on temperature data already fed into your platform or wiki documentation about platform usage.

The confusion between these technologies and real artificial intelligence can lead to unrealistic expectations and misguided investments in systems that fail to meet the advanced requirements of the IoT industry. To fully harness the potential of this technology, it’s crucial to seek solutions that offer capabilities such as continuous learning, autonomous integration with IoT devices, and adaptability to changing scenarios.

How to Identify genuine AI solutions

To avoid falling into the trap of “fake AI assistants,” businesses must carefully evaluate the solutions on offer. Key indicators of a genuine AI solution include:

• Predictive Capabilities: The solution must analyze historical and real-time data to predict future behavior and make automated decisions.
• Continuous Learning: True AI learns and improves over time, adapting to new data and contexts without the need for constant reprogramming.
• Integration with IoT Devices: Authentic solutions should connect to sensors and devices in the IoT ecosystem to operate autonomously and efficiently.

Real AI in IoT is amazing

AI applied to IoT has immense potential to transform sectors such as manufacturing, logistics, and energy. However, this potential will only be fully realized when companies adopt genuine solutions that integrate advanced machine learning algorithms, real-time data analysis, and intelligent automation capabilities, not pre-packaged chatbots.

In conclusion, while LLM-based chatbots are useful tools, they should not be confused with true artificial intelligence applications.