You’ve probably heard of Machine Learning and you have most likely interacted with it. But before diving into the subject of how to automate tasks with this technology, we have to start slowly by giving a definition and a brief overview of how it works. Machine Learning (ML) is a branch of artificial intelligence (AI) that focuses on teaching computers to learn without the use of explicit programming. At its core, Machine Learning is about creating algorithms that can analyse data and improve their performance on a given task over time. If you want a simpler explanation, this is it: Humans can identify correlations between one or a few variables, but ML algorithms can analyse hundreds of variables and identify correlations that we cannot even imagine exist.

How does learning from data happen?

Learning from data is a process divided into four steps:

  1. Data feeding: The algorithm receives large amounts of task-relevant data. This data can be labelled (where the desired output is already known) or unlabelled (where the algorithm has to identify patterns on its own).
  2. Pattern recognition: The algorithm analyses the data to identify patterns and relationships between different pieces of information.
  3. Model building: Using the identified patterns, the algorithm creates a mathematical model that can be used to make predictions or decisions.
  4. Testing and refining: The model is validated using new data to determine its accuracy. If performance isn’t perfect, the algorithm is tweaked and fed more data to improve the model.

Now that we’re on the same page, let’s look at how Machine Learning is transforming task automation and optimising workflows for your business.

What are some key applications of Machine Learning for task automation?

Machine learning (ML) offers a powerful toolkit for automating business processes, freeing up valuable employee time and improving overall efficiency. Here are some key applications of machine learning for task automation:

You know that businesses generate vast amounts of data. Your business probably does that too and you need to navigate those mountains of data to gain valuable insights that might help you in the decision-making process. Machine Learning might become your best friend in this process. ML algorithms can identify repetitive tasks and workflows by sifting through this ocean of data. By analysing historical data and user behaviour, ML can identify tasks that follow a predictable pattern, making them easy to automate.

  • Task Classification:

Machine Learning algorithms may act as intelligent sorters, automatically sorting tasks based on a variety of parameters such as complexity, skill requirement, and urgency. 

Machine Learning can categorise tasks according to the skills required, enabling more efficient resource allocation. Repetitive tasks can be automated, allowing skilled employees to focus on more strategic work.

  • Predictive Maintenance:

Machine Learning has the potential to go beyond automating operations and actually prevent them. Predictive maintenance is an advanced technique in which machine learning (ML) analyses sensor data from equipment to identify probable breakdowns or process difficulties.

If you do this, you can anticipate problems before they emerge and you can adopt proactive maintenance actions, reducing downtime and associated expenses.

What are some more specific examples of how Machine Learning is used in business?

We’re here to provide a more practical approach, so it’s easy to imagine how machine learning can be applied in specific businesses. Here are two examples:

  1. Classification: Let’s say you have a catalogue of 1 million products and wish to organise them into categories. Instead of completing them all, you can perform some of them and then use machine learning to understand those patterns and categorise them all automatically.  Or, let’s imagine you are a dermatologist and you need assistance with classifying moles from images. Machine Learning can help you tell, by analysing a picture, if the mole in it is malignant or benign.
  2. Regression: Let’s suppose you’re a real estate company with a large number of listings and new flats entering the system. You’re not sure what price to set them at. ML can see all of the links and correlations that influence the sale price and estimate what the sale price will be for those apartments based on the data you provide.

Automating tasks with Machine Learning leads to improved business efficiency

Based on what you’ve read until now, you probably guessed some of the ways in which automating tasks can improve your business’s efficiency. While you’re reading the next section, I invite you to imagine what are some specific areas in your business that Machine Learning could improve.

The automation of tasks with machine learning results in improved business efficiency. Here’s how it can help:

  • Increased Productivity: Repetitive operations that slow down employees can be automated with ML. This frees up important human resources for higher-value activities like innovation, problem-solving, and strategic thinking. Do you have any tasks in mind that may be automated with ML to benefit your employees? 
  • Reduced Costs by minimizing human error. Manual processes are subject to error, which in turn can lead to rework and waste of resources. Machine Learning algorithms, on the other hand, can perform tasks with extreme accuracy and consistency. This reduces errors and ensures high-quality results. This leads to fewer changes, faster turnaround times and ultimately lower operating costs. You can also reduce costs by streamlining operations. Machine Learning is your best buddy, here as well. Automating processes improves workflows by reducing needless steps or delays. This not only shortens work completion times but also decreases the need for human intervention and monitoring, thereby saving money on payroll and resource allocation. What are some processes that can be automated with Machine Learning in your company?
  • Improved decision-making: As we said before, by analysing massive amounts of data, Machine Learning may detect patterns and trends that people may overlook. Imagine how much you can improve your business strategy by finding the right insight. 
  • Improved customer experience: Machine Learning can automate tasks such as customer service questions and product recommendations, freeing up human agents to handle more complex interactions. This can result in shorter response times, improved customer satisfaction and potentially higher customer retention rates.

Final Thoughts

It’s clear that Machine learning (ML) offers a powerful toolkit for automating business processes. It frees up valuable employee time and improves overall business efficiency. It can become your best buddy if you know when and how to use it. Sounds complicated? Don’t worry, we have a team of experts that might help you in this journey. Let’s explore together how Machine Learning can benefit your own business!