With 76% of HR leaders predicting that AI will become essential to organisational success, the proliferation of HCM, HRIS, and human resources tools leveraging large language models, predictive analytics, and machine learning should come as no surprise.
With the potential to dramatically increase efficiency, productivity and accuracy across multiple HR processes, AI stands to revolutionise how organisations manage people operations.
Understanding the nuances of specific technologies and their applications, however, is key to choosing the right tools for a business.
How AI is used in human resources
From increasing productivity through automation to streamlining compliance with enhanced document management, today’s HR professionals use AI to save time and cost with sophisticated HRIS and HCM solutions.
Recruitment
One of the first applications of machine learning in human resources, modern recruiting has evolved into an AI powerhouse. From sourcing talent and screening resumes to engaging with candidates and predicting headcount, generative and predictive tools have completely changed how organisations compete for talent.
Administrative HR tasks
Offloading repetitive tasks to tireless machines gives HR professionals time and energy to focus on substantive work that moves their organisation forward.
Data management is the perfect example. Businesses that accumulate large quantities of data can struggle to maintain it properly. Automating the data cleansing and updating process ensures that everyone makes decisions on the basis of correct information.
In addition, AI-driven payroll and HCM solutions can remove the stress of calculating payroll correctly and transferring employees who shift locations.
Employee performance management
Machine learning might not seem the most obvious tool for guiding, developing, and nurturing employees, but AI can provide significant support in the form of automated learning experiences that adapt to employee performance.
For example, AI may suggest additional learning activities or automatically enroll employees in related follow-up training based on a team’s aggregate score in a training module.
Benefits administration
Predictive AI tools can crunch the numbers on benefits usage and recommend adjustments to the organisation’s offering. On the employee side, automated enrollment removes the risk of missing annual deadlines.
Onboarding and offboarding
Saying hello to a new employee and goodbye to a departing one both entail a fair amount of paperwork. AI can smooth the experience by helping ensure everyone receives essential communication and documents as quickly as possible, enhancing the employee experience.
Benefits of using AI in HR
For companies struggling to make the most of limited time and budget resources, AI can fill some important gaps and provide much-needed support to employees.
Time efficiency
Many routine or manual HR tasks that take humans hours to complete can be done by machines in minutes, if not seconds. Instead of asking a talent specialist to sift through 500 responses to an open job description, tap an algorithm to help with the initial screening and free up valuable time to debate the merits of the most qualified candidates.
Reduced costs
Using AI allows HR and other professionals to leverage their creativity and strategic intelligence in ways that grow the business – all while reducing the amount of time required to complete manual tasks. Leveraging machines’ powerful pattern recognition and analytic capabilities can give HR leaders deep insight into how and where to deploy resources for maximum effect.
Better structured processes
Automating repetitive tasks like payroll, onboarding, or shift scheduling means consistent, timely performance with a reduced risk of error. Depending on the specific type of tool, an AI-powered solution may even suggest specific process improvements based on its analysis of your existing workflows.
The challenges of AI in HR
Like most business decisions, integrating AI into human resources comes with challenges as well as benefits. From legal risks associated with data privacy and bias in hiring to potential clashes with internal missions and values, HR leaders must carefully consider the implications of adding machine learning to the mix.
Data security risks
Machine learning tools improve performance by training with new data, and many of the most popular solutions rely on user-provided information to meet that need. But keep in mind that disclosing sensitive employee information to third-party solutions using generative AI runs the risk of violating laws designed to protect confidentiality. Before sharing company or employee data with a tool or platform that relies on artificial intelligence, review applicable data privacy laws, as well as company policies and procedures.
Loss of human expertise
AI can outperform humans in areas like pattern recognition, data analysis, and computation. When it comes to making complex, context-dependent decisions and exercising moral judgment, however, machines fall demonstrably short.
Over-reliance on AI in any part of a business can lead to strategic missteps and lost opportunities if leaders consistently sacrifice innovation in favour of efficiency.
Ethical issues
The scope of how, where, and when businesses can leverage AI in their operations remains an open question in many jurisdictions. Technology continues to advance rapidly while governments and other regulators rush to keep up with new developments. Staying informed, let alone compliant, can pose unique challenges, particularly for larger enterprises in sensitive industries operating in multiple locations.
The future of AI in HR
As large language models, automations, and predictive tools continue to develop, they’re sure to find new use cases and applications in people operations.
Contrary to doomsaying predictions, industry experts reject the notion that machines can replace humans altogether. Instead, analysts predict a future where AI supports HR professionals in becoming more data-driven and dynamic.
With the ability to analyse and interpret larger and more complex data sets and to automate time-consuming tasks, HR professionals of the future will prioritise strategic development and planning activities.
Rhiannon is an experienced Human Resources specialist with a demonstrated history of working in the consumer internet industry. She is skilled in full lifecycle recruitment across all disciplines, including business partnering, talent and change management, performance management (including onboarding), as well as global mobility and immigration.
