What are AI, ML, and IoT?

This article was completely revised and updated May 8, 2025

Find out the meanings behind the buzzwords AI, ML, and IoT.

Artificial intelligence and IoT – Use cases & applications

The dramatic evolution of artificial intelligence (AI) and its widespread deployment across companies and industries of all types and sizes is changing the way we do business forever.

Tech futurologists love to talk about it as a revolutionary, paradigm-shifting force, and both specialist tech media and the mainstream media are full of AI thought pieces, op-eds, and news stories. Often, its transformational power can seem overwhelming. However, the technology is also extremely exciting.

At the same time, the Internet of Things (IoT) is also expanding and incorporating more and more of our everyday personal and professional lives. With improved connectivity, businesses can streamline, automate, and eradicate repetitive tasks, increasing efficiency and reducing costs. For businesses operating in highly competitive markets, this is essential.

While AI and the IoT are fascinating technologies in their own right, they are even more powerful when used together. Integrating AI technologies into IoT networks can make us smarter and faster by enabling us to collect and analyze the vast amounts of data IoT networks generate. AI-enabled IoT networks will give us more detailed insights into the surrounding environment - whether that’s a manufacturing facility or a hospital - and allow us to optimize processes, respond instantly and automatically to changes, and make more informed decisions.

What is Artificial Intelligence?

IBM defines AI as the 'technology that enables computers and machines to simulate human learning, comprehension, problem-solving,  decision-making, creativity, and autonomy' (IBM). AI technologies can be adapted to an almost endless range of applications. They can identify objects in images, interpret human language, and communicate back. And they can analyze enormous amounts of data, extract insights, and automate responses.

As such, AI technology has already revolutionized search engines, quality inspection tasks, manufacturing facilities, robotics, and medical image analysis. It is far more capable of harnessing the power of complex data than humans, making it a powerful automation, optimization, and advisory tool.

What is the Internet of Things?

The IoT is a network of sensors and devices embedded in physical objects that collect and share data. The smart home is probably the context in which 'IoT' is best known. It's the technology that connects thermostats, fridges, washing machines, TVs, and wearables in the home and enables individuals to collect, centralize, and control that data and those devices remotely.

But the smart home isn’t the only example of the IoT in action. IoT technology can be deployed in any environment where multiple components work together or interact. For instance, IoT technology is used in agriculture to monitor and adjust environmental conditions in greenhouses and control machinery. It is employed in the manufacturing environment to streamline processes and guarantee quality standards are met. It features in healthcare systems, where it assists with patient monitoring. Today, we’ve moved far beyond the relatively small-scale smart home concept and have extrapolated the idea to smart cities.

What is the relationship between Artificial Intelligence and IoT?

AI and IoT are supplementary and synergistic. By their very nature, IoT networks generate large amounts of data. AI is the technology best suited to processing, understanding, and leveraging that information. AI integration improves IoT networks because it enhances our ability to interpret data and automate intelligent responses. Together, AI and IoT technologies result in the creation of truly smart ecosystems that benefit from real-time decision-making (e.g. self-driving cars), process automation and optimization (e.g. supply chain logistics), and predictive maintenance (e.g. in manufacturing facilities).

The benefits of AI integration into IoT

Integrating AI into IoT has clear and measurable benefits for businesses. Many of these benefits are complementary. For instance, improved efficiency often results in cost reductions. When planning and implementing AI IoT projects, companies must consider the specific business problem they are trying to solve, and which benefits are most important to their project:

Increased efficiency: As IoT sensors can monitor conditions in real-time, they provide an always accurate account of environmental conditions and process performance. AI can analyze this data and make adjustments to optimize performance and improve efficiency.

Cost reductions: By optimizing performance, AI-enabled IoT networks drive significant cost reductions. Whether predicting equipment failures before they occur and taking action to prevent damage or optimizing resource and energy use, the technologies can drive impressive savings.

Optimized routine processes and tasks: Many of the routine tasks employees are asked to perform are easily automated by IoT and AI systems. This both speeds up the processes and frees up human employees to focus on tasks that maximize their value to your organization.

Human error reduction: At the same time, IoT systems that leverage AI also reduce the scope for human error, improving accuracy. For data-intensive tasks in industries like manufacturing and logistics, this can have a significant impact on performance, productivity, and efficiency. In sectors like healthcare, it can mean improved patient safety and health outcomes.

Reduced risks: AI's predictive capabilities and IoT networks' capacity for large-scale data collection mean the technologies work extremely well to minimize risk. While predictive maintenance can improve safety in a manufacturing environment, the technology could also be used to improve situational awareness and identify potential hazards.

Increased revenues and added business value: With more data at their disposal and smarter AI insights, businesses can improve existing offerings and open up new revenue streams. This can be achieved by enhancing product personalization to meet customer needs better or by creating more advanced products and services that leverage AI's predictive potential.

Better predictions of customer preferences: However, AI-enabled personalization isn't only relevant to product development. It also has applications in marketing and purchase recommendation systems. Insights gleaned from IoT sensors can be used to hone and refine customer communications, upselling, and cross-selling possibilities.

Real-world use cases: AI and IoT examples

Organizations can implement AI-integrated systems in any environment where large amounts of data are available, and there is the potential for AI-driven optimization. This means the technology's potential scope is enormous. With this in mind, we compiled four example use cases.

Smart cities

Modern cities already feature an extraordinary number of sensors. However, AI could enable us to harness the power of that data better and create smarter cities that adapt to changes in the environment in real time and optimize the urban experience. For instance, IoT sensors can collect traffic, energy usage, waste levels, and air quality data. AI could then analyze that data and automate responses that ease traffic flow, reduce energy consumption, or even improve emergency response times.

Quality control in construction and manufacturing

AI-enabled IoT networks will play a critical role in guaranteeing products, buildings, and other infrastructure meet the required standards. By collecting data throughout the assembly or construction process, sensors can provide AI with the data required to identify issues, inconsistencies, and deficiencies. This will ensure organizations can reduce quality control costs while improving safety standards.

Smart retail

AI-powered IoT devices can be used in retail to facilitate real-time inventory tracking and optimize the consumer experience. Smart shelves and RFID tags can monitor stock, while AI can use that information to inform product placement and identify and predict trends. The technology could also be used to enable dynamic pricing and bespoke shopping experiences.

Preventative maintenance

Preventative maintenance is an increasingly influential concept in manufacturing. It aims to optimize service costs while maintaining machinery health and ensuring a safe environment for humans. Using AI algorithms, we can accurately forecast failure and determine which part of the machine will be affected. This allows us to estimate better when repairs/servicing should be performed and prepare the specialist experts and equipment required.

Challenges in Integrating AI with IoT

While the benefits of AI-enabled IoT networks are widespread, businesses must also overcome a series of potential challenges. These include:

Cost

Initial project design and implementation can require significant investment. As such, businesses need to ensure they select an appropriate use case with the potential for significant ROI.

Integration

AI-enabled IoT networks bring together diverse systems to create a unified solution. As a result, these projects often require integration expertise and assistance from digital specialists.

Integration

As IoT networks collect large amounts of data, businesses must ensure they have robust data security protocols. Failure to do so can result in compliance issues and -potentially - hefty financial penalties.

Identifying appropriate PoCs

The success of digital projects often depends on an organization's ability to select an appropriate Proof of Concept that will demonstrate the technology's value and justify its rollout. Selecting the most suitable PoC is a complex process in its own right and requires a clear understanding of critical business challenges and how the proposed technology is best used to resolve them.

Data quality concerns

AI solutions require high-quality data to achieve results. In many cases, businesses struggle to provide that data because their systems are siloed or data is compromised in some other way. One of the first steps in any AI project is ensuring the required data is readily available.

Talent shortage

Digital, AI and IoT technologies are evolving so rapidly that few businesses can maintain the internal expertise required to implement solutions. Consequently, more and more organizations are turning to third-party experts and specialists to provide that knowledge.

All these challenges can be overcome by working with expert AI and IoT specialists with experience in delivering complex digital projects that solve real business problems.

You need an optimized IT estate

One important fact to remember is that if your business has ambitions to exploit AI and IoT, you will need to automate more services, collect and analyze more data, and streamline more processes.

This is another way of saying you will need to make digital transformation and cloud migration the cornerstone of your business strategy.

Modern AI and IoT applications are dependent on cloud-based IT infrastructure. SoftwareOne can help you reshape your IT infrastructure to leverage big data's potential fully.

• We are a global leader in IT and digital transformation services and operate the world’s largest independent cloud economics practice.
• We have deep technical expertise combined with a consulting practice that meets our customers’ operational and strategic demands.
• We enjoy strong vendor relationships, giving us a detailed and comprehensive understanding of all major global technology platforms: Microsoft, AWS, Alibaba, Oracle, and IBM.
• We are the premier data experts. We know where the data is, how to obtain key insights on that data, and how to manage those insights.

These attributes solidify our position as a leader in emerging business technologies and the best choice to lead your AI and IoT projects.

Our AI and IoT practice is a global leader

SoftwareOne has invested heavily in developing its AI Centers of Excellence and bringing deep data science and AI consulting capabilities to our clients worldwide.

Our exceptionally talented team comprises individuals from various educational backgrounds, including computer science, mathematics, physics, biomedicine, statistics, and chemical engineering.

Our work has been recognized by the wider industry, with SoftwareOne (formerly as Crayon) receiving the AI & Machine Learning Partner of the Year Award for 2019 at Microsoft's annual Partner Awards. SoftwareOne (formerly as Crayon) is highly respected for our ability to adapt to rapidly evolving market demands, as well as our forecasting capabilities. The company has demonstrated this versatility with our work with generative AI technologies like ChatGPT and other platforms, most notably AWS and Google.

Finally – and perhaps most important - we have invaluable operational  experience, having completed more than 300 cross-industry applied AI and IoT projects around the globe over the last 11 years.