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In this modern, digital age, the terms ‘artificial intelligence’ and ‘machine learning’ are constantly thrown around, especially with the development of digital technology. You might think that both artificial intelligence and machine learning are one in the same, but you’d be mistaken. They’re actually two different  things. 

They can be used interchangeably, but they can also be used together. But in order to understand how and when they can be used, and why they’re beneficial for a wealth of industries, we first need to know what they are, together with the differences between the two. So what is artificial intelligence, what is machine learning and which industries count on them the most?


What is artificial intelligence (AI)?

Artificial intelligence (AI) refers to the development of computers and robots that are capable of behaving in a way, and also mimicking, the behaviour of humans and their capabilities. An AI-enabled programme will be able to contextualise and analyse the data needed to trigger actions without getting any humans involved, otherwise known as human interference. 

In this day and age, AI has become the beating heart for many industries who have become dependent on it, but there needs to be a balance between relying on AI and involving your human workforce. We have written an article about how AI and humans can work together to deliver exceptional results, more so in the case of marketing and content creation. 

Artificial intelligence literally means a computer that has a human-made thinking power. AI systems don’t need to be pre-programmed because they use algorithms that work with their own intelligence. A good example of this is when you go up against a computer when playing Chess online or when you use Siri as a tool. 

Based on the level of capability AI has, it can be grouped into three categories: weak, general and strong. At the moment, as a society, we’re dealing with weak and general AI systems as opposed to strong, at present anyway. But the thing to remember with AI is that one of its subsets is machine learning, hence why they can be used interchangeably or simultaneously.


What is machine learning (ML)?

Machine learning is often described as a pathway leading to artificial intelligence. It’s a subset of AI that uses algorithms to recognise and learn patterns. This is usually done through data input in order for it to learn and subsequently make better decisions in the future. It gets ‘smarter’ the more it ‘learns’, effectively. 

Much like AI, this too is divided into three different categories: supervised learning, unsupervised learning and reinforcement learning. No matter which type you use, you’ll be able to use machine learning in your business, regardless of the industry you work in, to do things like: sort images, forecast sales and analyse ‘big’ data.


What are the key differences between AI & ML?

Now we’ve discussed what each thing is, let’s delve into how they’re different from each other. Understanding this will help you to determine which one will work best for you and your business operations. For example, you might think that you need AI whereas you actually need ML, and vice-a-versa. For instance, with AI:

  • It can enable machines to simulate human behaviour
  • The goal is to allow a computer system to solve complex problems, so humans don’t have to
  • Machine learning and deep learning are both subsets of AI
  • AI has a wide range of scope
  • Ai is concerned with maximising the chances of success all round
  • AI is divided into three main types: weak, general and strong
  • AI includes reasoning, learning and self-correction
  • AI can deal with structured, unstructured and semi-structured data

ML on the other hand consists of the following differences:

  • ML is a subset of AI, allowing a machine to learn, automatically, from past data without explicit programming
  • The goal is to enable machines to learn from data to provide a more accurate output
  • People “teach” the machines how to perform a certain task using data
  • Deep learning is a subset of ML
  • ML has a somewhat limited scope
  • ML has the ability to create machines that can perform specific tasks, but only the ones they’re trained for
  • ML is concerned more so patterns and accuracy 
  • ML applications includes, but is not limited to, Google search algorithms and Facebook friend tagging suggestions, for example
  • Can be divided into three types: supervised, unsupervised and reinforcement learning
  • ML, as the name would suggest, learns and can self-correct
  • Can deal with both structured and semi-structured data


Which industries use AI and ML?

There are many different industries who count on both AI and ML today. It enables organisations and companies alike to transform their operations into something that’s more efficient, cost-effective, productive and, most of all, automatic. Company owners are looking for ways to reduce their employees’ workloads so they can focus on other tasks that are more valuable and that need to be done by a human worker. 

As there are many different levels of ML and AI, as already discussed, there are a wealth of things that they can do to benefit the business, no matter how simple or complex the task might be. With this in mind, both AI and ML are used by the following industries and sectors, including digital marketing agencies, like us here at Kumo:

  • Banking and finance
  • Schools and education
  • Manufacturing
  • Healthcare
  • Warehousing
  • Legal and law
  • Police
  • Military
  • Marketing



Kumo is a dedicated digital marketing agency with over two decades of experience in the industry. We are pleased to provide a wealth of marketing services, including SEO, PPC, content writing, website design, graphic design and more. For more information about how we can help you today, get in touch with a member of our professional, specialist team today – we’re proud to offer marketing services to customers across the UK, so no matter where you’re based in the country, you can count on us to propel your business into the spotlight.


Author Biography


As an experienced Copywriter, Lorna enjoys creating varied content for an abundance of different industries and sectors. From detailed, informative articles to creative infographics, she's always looking to inject originality into the work she produces. When she isn't working, Lorna runs her own lifestyle blog, plays the guitar and loves to take part in charity runs.