As technology continues to advance, AI has become an invaluable tool for enhancing HR processes, improving efficiency, and delivering data-driven insights. This glossary aims to familiarize you with key AI-related terms and concepts in the context of HR, providing you with a deeper understanding of the evolving landscape.
How can HR use AI?
There are many potential applications the HR function can support with AI tools. While in all cases human oversight will be required to ensure tools are functioning correctly, there is great potential for creating more efficient processes, improving service levels and delivering better performance:
Predictive Analytics - Predictive analytics uses AI algorithms and statistical models to analyse historical and real-time data, identifying patterns and trends to predict potential future outcomes. In HR, predictive analytics can be used to forecast possible employee turnover, anticipate hiring needs, and enhance workforce planning.
Recruitment Automation - Recruitment automation involves the use of AI-powered tools to streamline and optimize the recruitment process. AI can assist in resume screening, candidate shortlisting, and automated scheduling of interviews, reducing manual inputs and improving overall process efficiency of HR teams.
Chatbots - Chatbots are AI-driven conversational interfaces that interact with users in natural language. In HR, chatbots can be applied to employee onboarding, used to answer frequently asked questions, and provide assistance to employees regarding policies, benefits, and HR-related inquiries.
Employee Engagement - AI can contribute to employee engagement initiatives by assessing employee feedback, sentiment analysis, and social media data. By understanding employee sentiments and preferences, HR professionals can tailor engagement strategies, improve employee satisfaction, and foster a positive work environment.
Performance Management - AI-powered performance management systems use data analytics to evaluate employee performance objectively. These systems generate real-time feedback, identify skill gaps, and offer development recommendations for individuals, enabling HR to make data-driven decisions regarding promotions, training, and performance improvement strategy.
Bias Detection and Mitigation - AI algorithms can help identify and mitigate biases in HR processes, such as recruitment, performance evaluation, and promotion decisions. By reviewing historical data, AI can highlight potential biases and help HR professionals ensure fair and equitable practices are developed and implemented.
Employee Retention - AI can aid in predicting and addressing employee attrition by monitoring various factors such as job satisfaction, compensation, performance, and employee sentiment. This information enables HR to implement targeted retention strategies, such as personalized interventions or career development opportunities, to increase employee loyalty and reduce turnover.
Learning and Development (L&D) - AI-based L&D platforms offer personalised and adaptive learning experiences to employees. By looking at individual learning patterns and preferences, AI can recommend relevant training content, deliver microlearning modules, and track employee progress, enhancing the effectiveness of training programs.
Workforce Analytics - Workforce analytics involves the use of AI to collate HR data, such as employee demographics, performance metrics, and engagement surveys, to gain insights into workforce trends and patterns. These insights enable HR to make informed decisions regarding talent acquisition, workforce planning, and organisational development.
Employee Wellbeing - AI can assist in monitoring and promoting employee well-being by combining sentiment analysis, health-related survey responses and even data from wearable devices. By identifying patterns and trends, HR professionals can design interventions and policies to support employee well-being and create a balanced programme of automated and manual engagements to support individual mental, physical and financial wellbeing.
The Critical Role of Job Architecture in Organisational Effectiveness
It can be difficult to know where to start with a job architecture.
When faced with a chaotic picture of multiple job titles across various business areas and regions, the response can be to put this task into the “too hard” box or delay it for another year in the hope that it sorts itself out.
However, this approach can create issues, open organisations up to compliance risk, not to mention slow down strategic people initiatives.
RoleMapper’s Guide to Job Architecture offers practical insights and recommendations for HR professionals to design and maintain an effective organisational architecture.
You will learn:
The importance of a future-proofed and dynamic job architecture
Its benefits and the key steps to creation and implementation
The need for a job architecture to support job catalogue, job families and job levelling
What should HR do about AI?
AI will become an increasingly familiar part of working life over the next few years. HR teams should be thinking about how it can best support their day-to-day activities and provide support to all employees. HR leaders should be looking at mitigating potential risks by ensuring there is a clear understanding of how the AI applications that the HR team will use work, and prioritising monitoring and oversight.