AI is changing the way we hire employees
The recruitment process has come a long way since the days of paper CVs. Thanks to a decade-long digital transformation, online job sites, virtual portfolios, and even Skype interviews are now staples in global talent acquisition.
But could artificial intelligence (AI) elevate the hiring landscape and take the recruitment process one step further?
In recruitment, AI usually refers to various technologies used in the hiring process – from algorithms that match people to the right jobs and forecasting tools to smart automation and chatbots that increase candidate engagement.
When AI was first introduced into the world of recruitment, it wasn’t exactly welcomed with open arms. Not only because people believed it would take the jobs of HR personnel, but also because of the possibility that it would take away the ‘human’ element of HR.
However, AI can help recruiters analyse the job market, find the right candidates and speed up processes — enabling them to build up a strong talent pipeline. And thanks to the manybenefits AI offers both employers and candidates in the acquisition of global talent, many have now warmed to it.
Cut the bias
For candidates, AI can help to eliminate some of the most problematic human flaws in the recruitment process: hiring bias. Although often unintentional, stereotypes and personal prejudices are something which even the most conscientious recruiters can fall foul of. AI allows for blind applicant screening and levels the playing field.
Chatbots can also help to improve the candidate experience and engagement by offering immediate replies to inquiries or queries, simple job applications and ongoing assistance throughout the process.
Drop the pressure
Employers and HR personnel can benefit massively from AI, too. For starters, it can be used to scan CVs for certain keywords to shortlist the most suitable candidates intelligently.
Predictive analysis can even determine which candidates are more likely to succeed in the roles – helping to improve the quality of the hire and ensure only the most retainable talents are brought on board.
AI can also help companies reach passive candidates who aren’t actively seeking a new role – which can often be one of the best applicant pools. In the past, reaching these candidates involved poring through CV databases, lots of cold-calling and even more dead ends. AI takes away the hassle of searching for passive candidates by aggregating their profiles and recent activity from different sources to predict how receptive they will be to new job opportunities.
The focus on soft skills has also ramped up within the last decade. Before, recruiters would need to rely on facial cues and instinct to judge a candidate’s personality, communication and teamwork skills. But appearances can be deceiving, and many people will put up a good act during the interview. AI-based personality tests allow recruiters to get insights about candidates’ personalities and can help them make better hiring decisions
Get the best global talent
AI is not a magic program that eliminates the need for human decision-making or knowledge. Instead, it should be viewed as a powerful tool. A tool which can maximise outreach, reduce costs, streamline the hiring process and provide HR personnel with the valuable insights they need to ensure they hire the right person for the job. AI complements the work of hiring teams – making recruitment quicker and easier for companies seeking candidates in an overcrowded global job market, where talent acquisition can be even more of a challenge.
We know how time-consuming HR and recruitment can be. But if you want to find the bestglobal talent, it’s not something you can afford to neglect.
Paul Sleath is CEO at PEO Worldwide.
The advantages and disadvantages of AI in cloud computing
Cloud computing offers businesses more flexibility, agility, and cost savings by hosting data and applications in the cloud. AI capabilities are now combining with cloud computing and helping companies manage their data, look for patterns and insights in information, deliver customer experiences, and optimise workflows.
We take a look at some of the benefits and drawbacks of AI in cloud computing.
The benefits of AI in cloud computing
A major advantage of cloud computing is that it eliminates costs related to on-site data centers, such as hardware and maintenance. Those upfront costs can be restrictive with AI projects, but with cloud enterprises you can access these tools for a monthly fee, making research and development related costs more manageable. AI tools can also gain insights from the data and analyse it without human intervention, reducing staff costs.
AI is able to identify patterns and trends in large data sets. Using historical data, AI compares it to the most recent data, which provides IT teams with well-informed, data-backed intelligence. AI tools can also perform data analysis fast so enterprises can rapidly and efficiently address customer queries and issues. The observations and valuable advice gained from AI capabilities result in quicker and more accurate results.
Improved data management
AI enables extensive data management, and cloud computing maximises information security, making it possible to deal with massive amounts of data in a programmed manner to analyse them properly, allowing the business to leverage information that has been “mined” and filtered to meet each need. AI can also be used to transfer data between on-premises and cloud environments.
Businesses use AI-driven cloud computing to be more efficient and insight-driven. AI can automate repetitive tasks to boost productivity, and also perform data analysis without any human intervention. IT teams can also use AI to manage and monitor core workflows. IT teams can focus more on strategic operations while AI performs the mundane tasks.
With businesses deploying more applications in the cloud, security is crucial in order to keep data safe. IT teams can use different AI-powered network security tools which can track network traffic, they can flag issues, such as finding an anomaly.
The drawbacks of AI in cloud computing
Enterprises need to create privacy policies and secure all data when using AI in cloud computing. AI applications require a large amount of data, which can include consumer and vendor information. While some data can be anonymous and can't be tied to personally identifiable information, knowing who the data belongs to makes it more valuable. When sensitive information is used, data protection and compliance is a major concern.
IT teams use the internet to send raw data to the cloud service and recover processed data. Poor internet access can hinder the advantages of cloud-based machine learning algorithms, as cloud-based machine learning systems need consistent internet connectivity.
While processing data in the cloud is quicker than conventional computing, there is a time lag between transmitting data to the cloud and receiving responses. This is a significant issue when using machine learning algorithms for cloud servers, where prediction speed is one of the primary concerns.