In today’s business world, IoT (Internet of Things) has moved from ‘nice to have’ to ‘must have’ due to the tremendous amount of data being captured from multiple sources, leading to a host of benefits, including improved processes, cost savings, streamlined operations, and increased customer satisfaction.

According to the International Data Corporation, the total data generated by 2025 is expected to be around 175 ZB, with roughly 80 ZB attributable just to IoT devices. This presents two challenges: 1) Not all data is created equal, meaning a fair amount of data collected isn’t useful, and 2) processing that data efficiently isn’t easy.

This is where AI (Artificial Intelligence) comes into the picture. AI, machine learning, generative AI – they all fall under the same umbrella of artificial intelligence. And by combining AI’s data analysis capabilities with IoT’s extensive data collection, organizations can make data-driven decisions, optimize operations, and improve efficiency across their business much more quickly and efficiently.

To put it simply: IoT collects and transmits the data, while AI has the power to unlock that data much faster than a human can. The combination of these two disruptive technologies creates and enables extremely powerful end results that have the potential to revolutionize industries, businesses, and economies:

Operational efficiency

AI takes the constant stream that IoT devices extracts and detects patterns and anomalies that devices are not capable of doing. Machine learning coupled with AI can predict operation conditions and detect parameters to be modified to ensure ideal outcomes. AI-enabled IoT offers insights into which processes are redundant and time-consuming, and which tasks can be fine-tuned to enhance efficiency. AI processes large volumes of data received by connected devices and identifies similarities in patterns faster and more accurately than humans. This means you can maximize time, resources, and effort.

Data preparation

While IoT devices collect and transfer data with no eye towards what is relevant and what is not, AI can sift through and select useful data, presenting relevant and insightful information, while leaving aside what isn’t useful. AI can also assist in optimizing data labeling – adding tags, labels, or names to raw data, which allows a machine learning program to better understand and utilize information.

Faster analytics

Bringing AI and IoT together means data has less distance to travel before it’s usable. This is because many large data centers are often situated in a different region than your business, which means your information has to cover a lot of ground between origin, processing, and application, which in turn gives you latency issues.

Better risk management

AI-enabled IoT helps businesses to both understand and predict a broad range of risks and automate a prompt response. The classic example of this involves employee safety. Equipping workers wearable smart devices connected to a database allows those devices to collect data on things like location, temperature, worker vital signs, etc. That data is then transmitted to a central point for processing and analysis. If a worker’s vital signs are reaching a dangerous level, AI-enabled virtual assistants can send an alert to the worker or management and avoid a potentially dangerous outcome.

Improved customer satisfaction

Prioritizing customers’ needs and keeping customers happy is at the heart of every business. Unfortunately, any number of factors can contribute to customer dissatisfaction. Today, though, more and more businesses are recognizing the value of AI by implementing chatbots to not just interact with customers and address their needs, but to also utilize enormous amounts of data offer a far more personalized experience based. There are two kinds of chatbots: the first is based on AI and thus is more complicated, with the ability to evolve, while the second is based on a fixed set of rules that mean limitations and the inability to grow on their own.

Conclusion

The scalability and adaptability of AI and IoT complement one another. Combining the two technologies offers immense potential for driving innovation and transformation in a variety of industries. The number of connected devices will continue to grow and with it the amount of data.

IoT provides the infrastructure and connectivity to collect and transmit data, while AI algorithms are ideal for handling the increased complexity and volume of data, extracting meaningful insights and making sense of it at scale. By leveraging the unique capabilities of AI and IoT and letting them work in harmony, organizations can unlock new levels of automation, efficiency, and decision-making. And as both AI and IoT evolve, both individually and in conjunction with one another, the impact will help shape future intelligent systems.

If you would like to learn more about the possibilities IoT and related technologies can bring to your business, please get in touch.