What is machine learning?

Machine learning (ML) is a type of AI that identifies patterns using algorithms to make predictions based on previous behaviour. You’ve probably come across algorithms when using YouTube, Facebook or Netflix. These platforms make recommendations based on the content you’ve viewed in the past.

In recruitment, machine learning can train computers to do tasks that were previously done manually, such as comparing resumes and selecting top candidates. It uses data-driven insights to help you make smart decisions and hire people who can add to your company culture.

You can also use it to streamline the onboarding process and improve employee training, which improves the hiring process for your company and its future team members.

How managers and HR professionals can use machine learning in recruitment

Machine learning offers an effective way for your company to improve the hiring process while also potentially cutting costs. Below are five ways that machine learning and AI in recruitment could help you improve the quality of new hires:

1. Marketing job roles

Writing job descriptions and outlining roles and responsibilities can be time-consuming. Machine learning could help your company discover which locations and job boards are best to invest in, the best times of day to post jobs and how to optimize job descriptions to get the most out of the hiring process.

Using a tool such as ChatGPT can help you craft high-performing job posts and onboarding materials.

2. Sourcing candidates

Machine learning can potentially help you source candidates for your roles by analyzing online platforms, social media profiles and professional networks. Machine learning can also potentially analyze existing employee data and performance records to identify characteristics or attributes that correlate with success in a particular role.

Some AI tools might help you connect with candidates in real time when you need to, while others could use chatbots to screen candidates before moving on to the next stage of the hiring process. The chatbot can walk candidates through inputting their details and save you time and money on collating and waiting for paperwork to be filled out manually.

To get candidates who are an excellent match for your company, it’s important to have the right talent pool to draw from. Most recruiters spend a lot of time on sourcing alone, and machine learning can potentially help you find the right candidates faster.

3. Engaging candidates

Automated messaging systems and AI assistants could completely eliminate the need for a person to carry out repetitive conversations regarding scheduling and next steps. Chatbots are available at any time of day and can easily book interviews and send out reminders about upcoming appointments. Machine learning tools can even use market data to work out salaries and generate job offers.

4. Screening resumes

Machine learning can be used to quickly screen resumes and present you with what it determines are the most well-suited candidates. This resume scanning feature is often included with applicant tracking systems (ATSs). How does it work? Put simply, machine learning models can be trained on data to learn patterns and make predictions about the suitability of a resume for a particular job position.

It’s important to note that machine learning-based resume screening can be a great assistant in the recruitment process, but human review is still important for final decision-making.

5. Personalized outreach

Employees often have a lot of choices when it comes to job opportunities in the modern marketplace, and machine learning can help you create personalized messages that make an impact.

Sending out a customized message to every new hire is an excellent way to show prospective hires that you take them seriously, but it’s almost impossible to do for today’s busy HR and hiring managers. Machine learning can help you send out messages that make an impact without needing a person to write them.

Benefits of machine learning in recruitment

Let’s look at the main advantages of using machine learning in HR and recruitment:

Onboarding

Using ML and AI during the onboarding of new hires can make the process more cost-effective, time-efficient and personal. Algorithms can potentially take into account a new hire’s job role, strengths and past experience to create and deliver customized onboarding programs. This can increase engagement and help the new employee adjust to their role faster.

Efficiency and accuracy

Machine learning could speed up every element of the hiring process, including accelerating the creation of job descriptions, screening resumes, analyzing candidates’ work histories, delivering skills tests, scheduling interviews and informing hiring decisions.

Diversity and inclusivity

You can potentially use machine learning to pinpoint any biases that informed previous hiring decisions and determine the best solutions for avoiding them in the future. Having a diverse and accepting company culture helps to ensure that all employees can thrive and grow within your organization.

Employee retention

While not explicitly part of the recruitment process, retaining employees is essential for keeping turnover and attrition low. Hiring new employees can be very expensive, so employers may strive to retain employees wherever possible. Machine learning uses existing data to analyze trends and patterns in the reasons why people may be leaving your company, enabling your leadership team to address those issues.

Training and business planning

Machine learning lets you customize training programs for your business and every employee within it. You can use it to discover gaps in knowledge and recommend training to fill them. You can also use it to sort through training data to identify which team members need refresher training.

AI and ML can potentially go even further and analyze historical and current data on job roles, employee performance and training to help decision-makers allocate roles and responsibilities more effectively.

Potential risks of using machine learning in recruitment

Machine learning and AI are excellent tools, but you need to do the necessary training to ensure that you make the most of them. Some risks to be aware of include:

• Machine learning errors: Since machine learning models are trained based on available data, their performance can be influenced by the quality, quantity and representativeness of that data. For example, that means you could miss out on excellent candidates who are eliminated early on in the hiring process. One way you can help reduce errors is by using machine learning and human judgment together.
• Implementation and adoption: Introducing new technology to an existing team requires patience as they go through the learning curve. It’s important that you use change management best practices to support recruiters as they adjust to new ways of working and fully engage with the use of new tools.
• Unconscious bias: While you can use machine learning to determine biases in your hiring process, it’s important to remember that ML tools may still be subject to bias from the people who programmed them. It’s important to assess ML tools to see if they’ve incorporated existing real-world biases so you can take steps to avoid this.
• Drop-off: It’s important to balance AI communications with human interaction to ensure qualified candidates are engaged with the hiring process.

Machine learning and AI in recruitment are set to change the way every business finds candidates, analyzes resumes and hires new employees. To get the most out of new technology, be sure to do thorough research before selecting a machine learning tool and provide extensive training to the entire team before rolling it out.