How is AI Changing the HR Analytics Landscape?
Are you reading this article on your phone, tablet, or computer? If so, you probably only think about AI - artificial intelligence - being a part of your everyday life. AI is changing virtually every aspect of our lives, from how we communicate to how we shop, travel and more. We ask Alexa to play our favourite songs or Google to search for the answer to a question and AI powers these technologies.
And its adoption in the corporate world is no exception, as McKinsey research highlights that 58% of the businesses surveyed confirmed using AI for at least one function in the workplace.
One key area where AI has significantly impacted is HR analytics, helping businesses to more effectively manage their human resources and better understand employee needs and preferences. Artificial Intelligence in human resource management allows companies to collect and analyze large amounts of data related to employee performance, engagement levels, and company culture, allowing them to identify areas where they can improve and make data-driven decisions about managing their workforce.
How Does AI Impact HR?
Through AI-enabled tools such as predictive analytics software and machine learning algorithms, companies can uncover insights about their employees that they would otherwise not have been able to access. This allows HR teams to make more informed decisions about managing their workforce. Here are just some ways that artificial intelligence supports the human resource management function:
Employee Experience
One major benefit of AI in HR analytics is that it can be used to help identify areas where companies can improve their employee experience.. By analyzing data on employee engagement levels, job satisfaction, and other key indicators, AI can identify potential issues or areas where employees are struggling. For example, AI might uncover that a lack of training opportunities is causing employees to feel disengaged, prompting the HR team to develop new employee development programs.
Learning and Development
AI is also transforming the way companies approach learning and development. By gathering information such as employee skills, career aspirations, and training needs, AI can help create development programs that are tailored to individual employees' needs. AI-enabled platforms can help match mentors with mentees based on factors such as skill sets and career goals and even provide real-time feedback on employees' progress.
Recruitment & Retention
On the recruitment and retention front, AI is used for various tasks, such as augmenting resume writing, sourcing and screening candidates, assessment tools, and even chat bots that keep candidates up to date with the progress of their applications. AI can also be used to analyze data on employee turnover rates and retention strategies, helping HR teams better understand why employees are leaving and how they can improve their recruitment and onboarding processes to attract and retain top talent.
Upskilling and Re-skilling
As AI continues to transform the workplace, many companies need more employees with the necessary skills to take on AI-related tasks. HR teams can use AI in HR analytics to identify areas where employees need support to upskill or reskill for future roles, identify well-positioned employees for these roles, and help develop a talent management strategy that supports employees in their career progression.
Artificial Intelligence And The Future of HR Analytics
AI in HR analytics has opened up a world of possibilities for businesses to manage their workforce better and identify areas where they can improve. AI-enabled tools can capture real-time insights about employee performance, engagement levels, job satisfaction, career aspirations, training needs and more. And AI algorithms can even predict employee retention, recruitment, and learning and development outcomes.
AI in HR allows for an automated approach to data gathering and data analysis. With various platforms talking together and coming together in one centralised platform, AI can analyse vast volumes of data in real-time and surface insights that would be difficult for humans to uncover.
But with that said, AI can only be as good as the data sources it relies on. If we are gathering inaccurate or incomplete data, AI will only be able to provide a limited view of the employee landscape.
Similarly, as we train AI systems to make decisions, we must be careful not to create AI systems that re-enforce existing biases and prejudices. For example, AI might theoretically be able to recommend ideal candidates for a job based on factors such as competencies, experience, and skills - but if those AI systems are trained using past hiring data that is biased or discriminatory in some way, then AI could end up perpetuating existing inequalities.
Therefore, HR teams must work closely with AI developers to ensure that AI systems are built using a diverse and well-rounded set of data sources and that AI systems are developed transparently to avoid any unintended biases or discriminatory outcomes.
Speaking on the Digital HR Leaders podcast, Anshul Sheopuri, Vice-President and Chief Technology Officer at IBM Workforce, introduces five pillars of trustworthy AI that HR teams should keep in mind as AI continues to reshape the future of HR analytics:
''The first is transparency. If you think about when you go and buy a beverage at your favourite coffee shop, you see the nutrition label, you see how many calories it has. What is that about AI? What is the help about AI, you should be able to see it, you should be able to delve into it as a user, not just as a data scientist, but as a user of the AI.
Explainability. Why is the AI giving me this recommendation? When you watch a movie it has some sense of the genre of movies that you like, what other viewers are watching, and why the AI is giving you a certain movie recommendation. The AI in HR, should also give you that same sense of the why behind the what. The ultimate decision is yours of course, but you should be able to understand the why behind the what.
The third pillar is fairness. This is all about bias identification and mitigation. So it is something you want to do upfront as part of the design of the AI. The fourth, robustness. Having the right guidelines and operational principles. And the fifth, privacy. This is something we have all been practising for a while, but it becomes even more important in the area of increased regulations in the space. People who have the need to know should know it and not others.''
As AI continues to transform the HR landscape, HR professionals must stay up-to-date on best practices and emerging trends in AI adoption. And by working closely with AI developers to ensure that their AI systems are built using a diverse and well-rounded set of data sources and that AI systems are developed in a transparent and bias-free way, HR teams can help ensure that AI continues to be a positive force for their organizations in the years to come.
To learn more about AI and HR analytics, check out our online course on An Introduction to AI in HR. We'll cover everything you need to know about AI and its impact on the future of HR and how HR can prepare for a world where AI is the norm. Sign up today and start your journey toward becoming an AI-powered HR professional!
ABOUT THE AUTHOR
Jasmine Panayides is a seasoned HR Writer and Editorial Lead on the Digital HR Leaders podcast. She writes about all things HR, from recruitment, HR tech, L&D, to people analytics. Jasmine holds qualifications in psychology and HR, and has a wealth of experience in the field. She is a firm believer in the power of data, and is passionate about educating and inspiring her audience to think differently about the future of work.
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