From Novice to Expert: Mastering How to Use AI in Your Industry

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Unless you’ve been living under a rock for the past few years, you’ve probably heard a lot about AI and how different industries are using it to upscale, boost efficiency, and improve the customer experience. This holds true for everything from healthcare to finance and retail. 

With all this talk of AI making business easier and more effective, you may have wondered if it can help you in your industry. But if you’re new to AI, just jumping in can feel overwhelming. We get it, and we’re here to help. This article will guide you on your journey from AI novice to AI expert. By the end, you’ll understand how to start using AI in your industry.


Step 1: Get to Know AI

From self-driving cars to personalized recommendations, AI is already impacting many aspects of our lives. But to a novice, AI can be confusing, so let’s start with a broad overview of what AI actually is, how it works, and what it can do. 

What Is AI?

AI refers to machines that can mimic human thinking. One example might be a voice assistant like Siri or Alexa. These assistants, like humans, can hear, understand, and respond to voice commands. You can ask Siri to set a timer, play a certain song, or look up restaurants in your area, along with about a million other things. 

The fact that these assistants can perform tasks as commanded shows that they possess artificial intelligence (AI). Obviously, they aren’t actually human, but they’ve been programmed to simulate human thinking. Like humans, they understand speech, learn via experience, recognize patterns, and make decisions.

But AI can also do things humans can’t do, like process enormous amounts of data to identify patterns that might elude humans, and then make decisions based on that data. It can also work around the clock, remember and keep track of things a human might forget, and perform tasks faster and more efficiently, minimizing the risk of human error and bias.

How Does AI Work?

AI combines computer science, mathematics, and cognitive science to create intelligent machines. Broadly speaking, there are two categories of AI: narrow and general. Narrow AI can perform specific tasks like voice recognition or data analysis, while general AI aims to imitate human intelligence across a wide range of tasks.

AI can work in multiple ways, depending on which approach it’s based on. For example,  rule-based AI systems follow predefined rules and logic to perform specific tasks. In machine learning, AI systems are trained to recognize patterns and make predictions using large amounts of data. Deep learning, which is a subset of machine learning, focuses on creating artificial neural networks (another form of AI) inspired by the human brain.

What Is AI Used For?

Today, AI is used in a number of areas, including healthcare, finance, customer service, supply chain management, and manufacturing. Here are a few examples.


Imagine a faster, more efficient way to diagnose diseases—or maybe a more precise form of surgery that’s quick and minimally invasive. Thanks to AI, we’re closer than ever to achieving these outcomes. 

Here are a few ways AI is being used in healthcare:

  • AI analyzes medical images, such as X-rays and MRIs, to detect abnormalities and help doctors diagnose accurately
  • AI creates treatment plans tailored to individual patients based on their genetic makeup and medical history
  • AI-powered surgical robots perform complex, minimally invasive procedures


In finance, AI supports things like fraud detection, risk assessment, and investment portfolio optimization. Here are a few of the ways it’s being used:

  • AI analyzes large amounts of financial data to identify suspicious transactions and fraudulent activities
  • AI helps financial institutions assess the risks associated with lending money 
  • AI analyzes market trends and makes predictions to support better investment decisions

Customer service

One of the areas where AI has already had a huge impact is customer service. Here are a few of its applications in this still-evolving field:

  • AI chatbots interact with customers and provide immediate responses
  • AI gives personalized recommendations based on a customer’s history and preferences
  • AI reduces the workload on human customer service reps by answering queries 24/7

Supply chain management

In supply chain management, AI streamlines logistics and inventory management, supporting more efficient processes with less waste. 

Specifically, AI can:

  • Analyze historical data and real-time information
  • Predict demand
  • Optimize delivery routes
  • Minimize costs


Robots operating a production line may seem like something out of Star Wars, but it’s quickly becoming a reality. AI-powered robots perform manual tasks with greater speed and precision than human workers, reducing errors and making manufacturers more productive.

In manufacturing, AI is being used to:

  • Automate repetitive tasks
  • Monitor production lines
  • Ensure quality control 

As you can see, AI is quickly becoming indispensable for today's industries—largely due to its ability to automate tasks, analyze vast amounts of data, and make informed decisions. And stay tuned, because AI is just going to keep getting better, which means we’ll be using it more and more.


Step 2: Chart Your AI Journey

If you’re feeling overwhelmed at this point, don’t worry. AI may seem complicated, but with dedication and the right approach, anyone can learn it. Here are some concrete steps you can take in each stage of your journey to become a master of AI.

Beginner: Learn AI Fundamentals

As a beginner, the first step is mastering the basics of AI. Start by learning programming languages commonly used in AI, such as Python or R. These languages provide the necessary tools and libraries to work with AI algorithms and models.

Python, in particular, is widely regarded as the go-to language for AI, due to its simplicity and extensive libraries like TensorFlow and PyTorch. These libraries provide pre-built functions and tools that make it easier to develop and deploy AI models.

You may also want to take some online courses and tutorials. Platforms like Coursera, Udacity, and edX offer comprehensive AI courses taught by industry experts. Taking these courses will give you a solid foundation in AI concepts and techniques.

To truly master AI, you’ll also need to understand the math behind it all. Linear algebra, calculus, and probability theory play a key role in AI applications, and mastering these concepts will go a long way in helping you better grasp the inner workings of AI models and algorithms.

Intermediate: Build Your AI Skills

Once you have a firm grasp of the basics, it's time to explore more advanced AI topics. Dive deeper into machine learning algorithms like regression, classification, and clustering. Learn how to preprocess data, train AI models, and evaluate their performance.

Of course, reading will only take you so far. Nothing beats practical experience. So try taking on some projects that involve real-world data and problem-solving. Kaggle, a popular platform for data science competitions, offers datasets and challenges to test your skills, and allows you to collaborate with the AI community.

Speaking of which, collaborating with others in the field is one of the best ways to grow your AI skills. Join online forums, participate in AI meetups, and engage in discussions with fellow enthusiasts. Sharing ideas, asking questions, and receiving feedback from others will help broaden your perspective and improve your know-how.

Expert: Master Industry-Relevant AI Applications

With all that knowledge under your belt, you’re ready to tackle some AI applications relevant to your industry. Consider which specific challenges and opportunities you currently face that AI might be able to help with.

To keep up with AI and ensure you get the maximum benefit from it, stay updated on the latest research papers, industry trends, and technology advances. Attend conferences and workshops, and join AI communities to learn from professionals and researchers. 

If you’re truly serious, you might even consider getting a degree or certification in AI. A lot of universities and online platforms offer these programs to help you dive deeper into AI theory, research, and applications. 

At this point, you may be thinking: wait! I don’t want to dedicate years of my life to this, I just want to know how to use AI effectively in my industry. While getting a college degree in AI probably isn’t necessary, this is a developing technology that most of us still don’t know much about. Anyone who’s serious about incorporating AI into their daily processes will need to set aside some time to learn about and explore it. The good news is, we’ll all be doing it together.


Step 3: Implement AI in Your Industry

We’re not going to assume you’ve done everything we just discussed in the last step. (If you have, way to go, you’re super-fast.) But now that you know what AI is and how you can learn more about it, here are some pointers to help you implement it in your specific area of expertise. 

Look for Opportunities

Look for areas where AI can add value to your business processes. A good place to start is any task that’s time-consuming, repetitive, or requires complex data analysis. You might want to consider automating these tasks, using AI, to free up your team and make your business more efficient.

Talking to experts in your industry can also help. Try to get a feel for their pain points and requirements, then, you may be able to work together to develop AI solutions that address these challenges. Be sure to measure how well AI is working for you, and adapt as needed.

Anticipate Challenges

Implementing AI won’t be a piece of cake. Lack of data, concerns over privacy and ethics, and resistance to change can pose challenges. But proactively addressing these obstacles can help make AI implementation a lot smoother and less painful.

One of the best ways to set your AI systems up for success is to make sure the data they’re being trained with is accurate, unbiased, and high-quality. You’ll also need comprehensive data governance policies to ensure data privacy and security. 

When it comes to ethical concerns, you’ll need to be sure you’re following responsible AI practices and regulations. Collaborating with others who have used AI can help you figure out what does and doesn’t work here.


Step 4: Face Forward

The future of AI is very exciting, and scientists are constantly breaking new ground in machine learning, neural networks, and other AI-related areas. As an AI learner, whatever your level, you’ll want to stay up-to-date on these developments.

AI Predictions

So, where is the future of AI headed? Here’s what the experts predict:

  • AI adoption will continue to grow across industries
  • Machine learning algorithms will become more sophisticated, leading to better predictions and decision-making
  • Natural Language Processing (NLP) will advance further, improving customer interactions and language translation
  • AI will continue to power things like autonomous vehicles, healthcare diagnostics, and personalized marketing strategies
  • AI will be integrated with Internet of Things (IoT) devices to create improved, highly optimized smart systems 

Prepare for an AI-Driven Future

As you continue using AI to benefit your business and industry, keep an eye on emerging AI technologies, read research papers, and follow industry trends so you can always maximize your own use of AI.

As AI develops, your skills will have to follow. Try to collaborate with experts and organizations working on leading-edge AI projects. If you can’t work with them, at least follow their progress. Embrace lifelong learning as you continue adapting to the ever-evolving AI landscape. Stay curious and be open to new challenges. 

Remember, the journey from novice to expert is a continuous one, whether that’s in AI or any other subject. With persistence and dedication, you can hop on the AI train and be a part of the exciting progress in this revolutionary field.

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