From chatbots to our streaming apps, artificial intelligence is already a big part of our lives. It's only going to become more ubiquitous in the years to come, but it can be difficult to understand and implement.
One of the best ways to use machine learning is for recruiting. It's growing increasingly popular in recent times. In fact, one study found that over 95% of HR managers believe AI tools have great potential to help in the right talent acquisition, and 55% said AI technology will become a regular part of recruiting within the next five years.
In this article, we'll explore the different ways that AI can be used in the recruiting process and how to integrate it into your business.
Once thought to be transient, sky-high employee attrition rates are now the new normal in today's business world. In order to maintain a competitive edge, companies are turning to AI-based solutions to help with their recruitment efforts.
There are many ways in which AI can be used in recruitment. For example, when it comes to actually scouting and identifying potential candidates, AI can be used to help sift through resumes and identify key patterns and keywords.
Job applications can easily number in the hundreds or even thousands. This is where AI can really help to speed up the process by reducing the amount of time needed for analysis.
In addition, AI can also be used to identify hiring process trends and generate leads. For example, if a company is looking to hire more engineers, AI can be used to help identify potential candidates and even suggest new avenues for recruitment.
Overall, AI can be a very powerful tool when it comes to recruitment. By helping to speed up the process and improve efficiency, AI can help companies save time and money while also improving their chances of finding the best candidates for the job.
If you're like most organizations, you're always looking for ways to improve your recruiting process. You want to find the best candidates quickly and efficiently, while also making sure you're making the best hiring decisions possible.
One way to do this is by using AI in your recruiting process. Here are four benefits of using AI in recruiting.
You can use AI to quickly and efficiently analyze large amounts of data - something that would take you far longer to do manually. This means you can spend less time sifting through resumes and more time interviewing the best candidates.
Suppose that your SME is hiring across multiple departments, with 15 open positions. The average corporate job opening is said to receive around 250 applications, which means that you’re looking at 3,750 resumes in total. Just reading and reviewing all these applications would swamp your hiring team, and take days or even weeks.
With an AI-powered recruiting automation solution, you could have all those resumes parsed in a matter of minutes. Beyond analyzing applications, you can also use AI to help you screen and schedule candidates. This means that you can spend less time on administrative tasks, and more time actually meeting and getting to know your candidates, so that your decision-making can be more strategic and meaningful.
For instance, with an AI system, you can create a digital assistant to take care of all the repetitive and time-consuming tasks in your recruiting process, like scheduling interviews or sending reminders. This would free up your team to focus on more creative tasks, like developing assessment criteria or coming up with questions that really help you get to know a candidate.
In addition to saving you time, using AI in your recruiting process can also help you make better decisions. Because AI systems can analyze large amounts of data, they can help you identify patterns that you might not be able to see yourself.
For instance, let's say you're looking at two applications with roughly the same qualifications and candidate experience. Which candidate would you hire?
With an AI system, you could input all the data you have on both candidates - including their certificates, work experience, education, and more - and the system would analyze it all to find the top talent for the job.
Of course, AI wouldn't be actually making any hiring decisions itself. That’s still up to HR professionals and hiring managers. But it would give you the data you need to make an informed decision about which qualified candidate is more likely to be a successful hire.
As your business grows, you'll need to find ways to scale your recruitment process quickly and efficiently. With AI, you can do just that.
Tools like Zapier can help you integrate your existing systems with an AI-powered hiring solution, so that you can quickly and easily scale your process without adding more people to your team. For instance, you could use Zapier to automatically add new applicants to your AI system, or to trigger an interview scheduling email as soon as a candidate is shortlisted.
In other words, AI recruitment technology helps automate repetitive tasks, so talent acquisition professionals can more easily find the right candidate from an ever-growing talent pool.
Finally, using AI in your recruiting process can also help you improve the recruitment, onboarding and overall employee experience. That's because AI systems are extremely efficient at predicting employee performance and churn.
With this data, you can identify bottlenecks in your process and make changes to improve the overall employee experience. For instance, you might use AI to identify which candidates are most likely to accept a job offer, so that you can focus your recruitment efforts on them.
Or, you could use AI to predict which employees are most likely to churn, so that you can take steps to improve retention. Maybe you'll find that employees who go through a certain onboarding program are less likely to churn, so you'll make changes to your process accordingly.
Some video interview platforms even make use of AI, including natural language processing and analyzing facial expressions, to help recruiters better understand job seekers. In short, using AI in your recruiting process can save you time, help you make better decisions, scale your business quickly and efficiently, and improve the overall employee experience. So if you're not using AI in your recruiting process yet, now is the time to start.
Just a few years ago, implementing AI in your business was a complex and costly process that required hiring data scientists and developers. But now, there are many tools available that make it easy to implement AI in your business - even if your recruiting teams don't have any coding or data science skills.
One of these tools is Akkio. Akkio enables you to build custom machine learning models in minutes, which can be used to automate any process in your business. For instance, you could use Akkio to automatically screen candidates for interviews, or to identify which employees are most likely to quit.
Akkio also has pre built models for marketing, sales, HR, and other common business processes. So if you're not sure where to start, you can simply use one of these models and get started right away. Check out our applications page or these 20 companies using machine learning to see some of the ways Akkio can be used in your business. Building your own custom model on your own dataset can be done in minutes without any coding skills required.
Lastly, Akkio is easy to use and you don't have to worry about breaking your site or needing to troubleshoot. Simply connect your data sources, select the KPI you want to predict, and let Akkio do the rest.
Akkio is a powerful tool that enables you to build custom machine learning models in minutes, which can be used to automate any process in your business. In this section, we'll show you how to use Akkio for better recruitment.
First, sign up for an Akkio account and connect your data sources. Akkio integrates with all major Applicant Tracking Systems (ATS) and CRMs through Zapier, or if you're more technical, you can use our API. Once your data is connected, you can simply select the column you want to predict and let Akkio do the rest. It's that easy!
Akkio is an automated machine learning platform, which means that it uses algorithms based on deep learning techniques like neural networks, recurrent neural networks, and reinforcement learning. These algorithms are used in conjunction with historical data from your ATS or CRM system to predict future employee performance based on past data. This allows you to make better hiring decisions faster than ever before.
In order to get the best results from using AI in your business, there are a few things you need to keep in mind. Here are four tips for getting better results using AI in your business.
There's a popular saying in the world of data science: "garbage in, garbage out." This means that if you're using dirty or inaccurate data, you're going to get bad results.
So how can you ensure that your data is clean? First, if you're collecting data manually (for example, if you're running a survey), make sure you collect it consistently across all sources. This will help to ensure that the data is accurate.
Second, make sure not to mix up different types of data. For example, don't mix up dates with numbers. This will confuse the model and give inaccurate results.
Before you start training your model, make sure you have enough training data available. Training requires lots of iterations before your model starts giving accurate results, so make sure you have enough patience while training your model.
With Akkio, you can easily select different training times to find the optimal training configuration for your data.
Make sure you test your model thoroughly before deploying it live - otherwise it could give inaccurate or even harmful results. Akkio will automatically provide error metrics after training so you can spot check for performance.
Don't just deploy models without understanding how they work or what they're predicting. Make sure you understand how your model works so that you can troubleshoot any issues quickly.
Additionally, make sure that predictions made by models are used correctly. For example, don't just use predictions as-is without further analysis. If a model predicts when candidates will close on an offer based on their average time between applying and closing on an offer, but then add more steps between applying and closing (like submitting their details via a form), the prediction will be inaccurate.
It’s also important to consider bias in machine learning. For instance, you’ll generally want to exclude demographic data, such as gender, from your training data. Including this data could inadvertently result in a model with gender biases.
In short, by following these four tips, you can ensure that you're getting the best results possible from using AI in your business.
In conclusion, using AI in your recruiting process can save you time, help you make better decisions, scale your business quickly and efficiently, and improve the overall employee experience. AI recruiting software isn’t meant to get rid of human recruiters, but simply to improve the talent acquisition process so HR teams can optimize their workflows and focus on the quality of hires.
Akkio is the best tool for using AI for better recruitment. It's easy to use, has no coding required, comes with built-time models that are ready to use out of the box, and allows you to build custom models if needed.
So if you're not using AI in your recruiting process yet, now is the time to start. Click here to sign up for an Akkio account and get started today.