machine learning in the workplace

Machine Learning in the Workplace: its actual and future impact

How to Learn Machine Learning gives you the best information to learn about machine learning, one of the main drivers of the next technological revolution. Read more informative articles today!

Machine learning is a subset of Artificial Intelligence that relies on the use of algorithms and statistical models to analyze and draw inferences from data sets.

A key benefit of machine learning systems is that they do not need to be explicitly coded to complete tasks, rather they can ‘learn’ as they work and become better at assigned projects.

According to research by Finance Online, 51% of businesses have already adopted machine learning in the workplace in some capacity.

And the scale of its use is expected to increase in the coming years.

In this article, we explores the impact machine learning in the workplace, in domains like business operations and employee performance.

Machine Learning in the workplace’s 1st improvement: Process Mining-Based Workflows

machine learning in the workplace

A workflow is a series of tasks that are repeatedly followed in sequential order to achieve an expected result. Modern workflows are dominantly implemented through cloud-based apps, such as a customer relationship management (CRM) tool, social media management software, or more.

Over time it is normal for workflows to become less efficient, but given its digital nature, it can be tough to spot inefficiencies manually and fix them before it starts to majorly affect business performance. Here’s where machine learning-based process mining tools prove to be the perfect solution.

A process mining tool can be integrated with all software used across the organization, post-which it can start learning about your workflow and remove inefficiencies. Here’s how the tool works:

  • First, it reads data related to your work processes
  • Second, it converts the data into event logs
  • Third, it creates visualizations of your workflows which can then be used by relevant stakeholders to solve bottlenecks

Given the fact that the tool will interact with your workflow 24/7, the process of mining efficiencies increases the probability of promptly identifying and solving inefficiencies, leading to higher productivity and faster decision making.

This is similar to SEO and website performance statistics; by scrutinizing the information available to your business, you can capitalize on opportunities and alter or cut weak spots. 

The Artificial Intelligence Disruption: How to Adapt and Succeed in the Age of Intelligent Machines
  • Johnston, M.D. (Author)
  • English (Publication Language)
  • 243 Pages - 01/14/2023 (Publication Date) - Independently published (Publisher)

Higher Productivity Through AI Tools

There are various machine learning and AI-based tools used by businesses today that help employees achieve higher productivity numbers than ever before. Here are a few examples:

  • Writing Assistants: These are extensively used by creative professionals (writers, marketing professionals, sales agents) to frame messaging for specific audiences. Not only do they help achieve error-free writing but also provide insights on how to maintain a particular voice and tone.
  • Intranet Chatbots: Using these bots, employees can retrieve documents and files in a flash from the company’s knowledge base. This significantly reduces the time needed to access information, leading to fast and informed decision-making. 

By leveraging the power of machine learning, employees can now spend less time deliberating on their actions and achieve higher productivity levels daily. 

Accurate Performance Tracking

ai remote jobs

Workplace bias has been a prevalent problem in organizations across all industries. Research conducted by Deloitte shows that 68% of employees report that workplace bias harms their productivity, and 84% report that these biases affect their level of happiness and self-confidence even beyond the workplace.

While it is difficult to completely remove bias from the workplace, it can now be severely minimized through the use of machine learning-based performance management systems.

Rather than managers being given the responsibility to track the performance of individual employees, it can now be placed in the hands of unbiased algorithms which accurately track daily performance, compare it to set metrics, and provide on-demand reports for any given time frame.

These reports can then be used for appraisals, promotions, and contract renewals. 

The number one benefit of these systems will be the transparency it provides as employees can request reports themselves as well. 

The Machine Learning era is already upon us. Sooner rather than later, you can expect machine learning tools such as process mining software and chatbots to become commonly used in your workplace.

But, rather than viewing them in a negative light, learn to embrace them as tools that will help you achieve greater productivity and develop a fair and transparent work environment. 

Thank you very much for reading How to Learn Machine learning, as always keep leaning and have a great day!