Why AI is the missing piece in your IoT applications

The rise of AI as an essential technology in various industries is transforming how we interpret data, predict outcomes, and automate processes. Machine learning and generative AI have also taken the spotlight within the broader IoT ecosystem. Some of you have probably already heard the term AIoT, reflecting the convergence of AI and IoT.

As the demand for AI’s analytical power grows, so does the need for vast data sets, which is precisely what IoT can provide. AI models, especially machine learning and deep learning models require vast amounts of data to learn and improve their accuracy. This creates a growing need for real-time physical data from enterprises, driving demand for IoT systems that connect this data to AI models. In this situation, IoT becomes the data fuel that powers AI, driving better predictions and data-driven decisions. 

The future of IoT lies at the intersection of AI and IoT

If you aim to build smart solutions that remain valuable over time and resonate with diverse user needs, integrating an AI component into your IoT applications is going to be a must.

Let’s take a look at the different stages of IoT maturity. In the early days of IoT, connectivity technologies and basic data collection monopolized all the discussions. Later came the need for better technology standards, market consolidation, and generating business value from the IoT. 

AI in IoT, or AIoT, can be considered the latest stage of this evolution. 

We are now adding intelligence to IoT, moving simply from condition monitoring to predictive maintenance, anomaly detection, and adaptive environments. Moreover, generative AI and Large Language Models, popularized by recent innovations by OpenAI and the like, are changing how we interact with data, making it easier for a broader range of users to access data insights.

Making IoT more accessible with AI

Not all smart solutions need to be AI-augmented. There are still countless use cases that can perfectly rely on simple control loops supported by rule-based applications. Similarly, custom dashboards, signage screens, and case-specific applications will continue to have their use.

But there are also many areas where AI brings clear benefits. Generative AI, for example, opens new possibilities for data analysis to a broader, non-technical audience. The support for plain-language queries enables the transformation of complex data sets into direct insights.

Data analytics that needed to be performed by technical experts and data scientists can now be done directly by the data consumer. 

Let’s take the real estate industry: 

Imagine a building populated with various IoT sensors. The facility manager can now directly ask questions about the current and future energy consumption in the building, while an office manager can analyze the occupancy rate of the past month, all of this without being tied to multiple dashboards or data analysis tools.

Integrating an AI component into your product will not only make it more accessible to a larger audience and more adaptable, but it will also deliver a higher ROI by reducing development time. Instead of creating new data processing features for each client request, your AI-enabled solution can address a broader range of questions from the start.

Transform IoT data into insights with Genio

Genio accelerates insights, empowers your team of domain experts, and drives strategic decisions. It quickly answers complex questions about your data with blazing speed, enables non-technical users to explore data independently, and makes informed choices based on data-driven insights you can trust. No more time-consuming setups or complex try-and-error query building.

Building upon akenza's deep technical expertise in large-scale data pipelines, Genio leverages the latest advancements in large language models (LLMs) and a retrieval-augmented generation (RAG) architecture to provide accurate and actionable answers tailored to your specific use cases.

Ready to transform your data into actionable insights? Join our waitlist today and be among the first to experience the future of IoT data exploration.