You’ve heard lots about artificial intelligence as it pertains to mimicking human intelligence and that makes sense: in the recent past, there’s been more of a focus on how AI can work for humans and become more accurate when it comes to acting just like a human would, taking things like emotions, future expectations, and the past into account. But even though general AI research has taken off in recent years, there’s a smaller, more focused branch of AI called industrial AI that is also important to follow.
Industrial AI, instead of thinking about how to build AI systems that can act like humans like general AI, focuses on actually using this technology to solve problems that currently exist. Confused? Let’s break it down: industrial AI seeks to use advancements in AI to tackle specific problems without focusing too heavily on creating human-like AI systems.
Some of the most common applications of industrial AI are:
Moving and storing goods
Supply chain management
Advanced analytics
Automation
Robotics
The potential of AI is incredible and those who choose to center their efforts on industrial AI will find better results and more efficient processes. In this article, we’ll dive deep into industrial AI and its applications to help see if this is the right area for you.
Why Industrial AI?
The world seems to be locked in on general AI applications and creating human-like machines and tools, so why should we even entertain the idea of industrial AI? Well, it really is quite simple. Let’s check it out:
More technology-focused approaches are required: we know that AI has the potential to automate and streamline processes; this is precisely why industrial AI has the potential to become so powerful. As the next generation of employees heads into the workforce, they’ll be more technology-minded than previous generations and ready to apply the most powerful and transformative approaches to their work.
Data leads to better decisions: the best decisions are backed by data, but without effective and practical ways to analyze large amounts of data, your findings will be practically useless. Data analysis in industrial AI looks directly at the changes that could be made to better adopt the results from analysis and improve overall processes.
Staying competitive has never been more important: we can all agree that the potential for growth with the help of AI tools is vast and as more and more companies begin to adopt AI tools to help with their day-to-day processes, their competitors will be forced to keep up–or fall behind.
Applications of industrial AI
It’s important to remember that the importance of industrial AI is particularly prevalent in industrial settings (hence the name!) because of the following benefits:
Automated workflows: in addition to suggesting the most efficient way to reach the desired goal, industrial AI can automate entire workflows, saving time, money, and personnel from the tedious tasks required to bring a workflow from start to finish.
Enhanced safety: some industrial jobs are dangerous for humans due to large machinery, potential malfunctions, and human error. When robots take the place of humans on the floor, however, the risk of injury lowers significantly.
Better productivity: AI tools and machines don’t need to rest, eat, or take breaks and this contributes to more efficiency and productivity on the floor.
Larger overall view: with a global view of the company’s processes, personnel, productivity, and machinery status, decision makers can better tackle problems and become more efficient.
Some of the most common uses of industrial AI include:
Predictive data analysis: using AI tools to track the status of machinery and potential problems can help companies anticipate problems and have the correct steps in place to fix them when they arise, saving time, money, and resources when issues do occur. Automating servicing or repairs is also a huge time saver.
Performance alerts: when AI systems are trained to recognize ideal performance levels, they can alert humans as soon as performance drops below the ideal so that the problem is addressed immediately, before larger problems emerge.
Robotics: the introduction of robots on warehouse or supply line floors is not only more effective than hiring humans to do those roles, but also saves time, is safer, and is more cost-efficient in the long term.
Supply chain optimization: with the use of AI tools that can use large amounts of data to fully review and provide suggestions for improvement on supply chains, companies can benefit from increased efficiency and better performance.
Shifting to Industrial AI
If the aforementioned applications and benefits are of interest to you, you’re probably already thinking of how you can bring industrial AI to your company, or get involved in the field yourself. Let’s dive into both: championing industrial AI practices and becoming an industrial AI expert.
To promote industrial AI practices, companies should:
Provide thorough AI education: it’s no secret that lots of people are wary of AI, especially when discourse about AI stealing jobs is so profound. That’s why it’s so important to educate your employees on the benefits of AI and how it can help, giving them the space to ask questions and fully understand exactly what the introduction of AI tools and systems will mean for them–and their jobs.
Carefully choose their AI systems: there are AI tools and systems for practically everything these days and more are emerging constantly. Instead of jumping into the first you find, carefully evaluate your company’s needs and future goals and choose the one that’s best for you.
Shift their focus to data: to function properly, AI systems need large amounts of data and for many manufacturing plants, this will require quite the shift. You’ll need to start collecting data and set up processes for storing, analyzing, and protecting data to make the most of industrial AI.
Make their hiring AI-forward: you can teach an old dog new tricks, but you can also start to prioritize AI knowledge or experience in your hiring processes to ensure an even more seamless adoption of AI tools.
To become an expert in industrial AI, consider the following:
Refresh your theoretical AI knowledge: while lots of present-day AI tools are focused on evolving and becoming more adept at mimicking human intelligence, industrial AI is solution focused and to best suggest the right tool for the job, you’ll need a strong understanding of the basis of AI and exactly how each tool works.
Familiarize yourself with industry trends: to best know how to suggest the right AI tool, you’ll need more than an understanding of AI; you’ll need to fully understand the industry itself, its problem areas, and future goals so that you have the full picture.
The potential of AI in industrial fields is practically limitless; it will, however, take time for these systems and machines to be properly adopted and used to their full potential. That’s why now’s the best time to take advantage of what AI has to offer and transform your future career by diving deep into AI.
Is industrial AI the right field for you? Let us know and consider starting your AI journey with Ironhack.
