HR-Led Role Redesign for Automation & AI

Welcome to HR-Led Role Redesign for Automation & AI, a comprehensive course designed to navigate the profound transformation Human Resource Management is undergoing due to advancements in artificial intelligence. As organizations move beyond buzzwords, HR professionals must understand how these technologies function as "prediction machines," streamlining decision-making and optimizing processes from recruitment to retention. This course moves past simple digitization to explore how the integration of machine learning and predictive analytics allows for objective, data-driven insights, freeing HR to focus on strategic, human-centric tasks.

The curriculum begins by dissecting the practical applications of AI across the employee lifecycle. You will examine how automation enhances specific functions such as talent acquisition, onboarding, performance management, and retention forecasting. We analyze the shift from intuition-based methods to predictive models that anticipate employee success and flight risks. However, with increased efficiency comes the critical responsibility to manage the design of work itself. A significant portion of the course is dedicated to Work Health and Safety (WHS), utilizing frameworks from Safe Work Australia to categorize psychosocial and physical risks—such as work intensification, surveillance stress, and the loss of job autonomy.

Beyond operational changes, this course equips you with the governance structures necessary to implement AI responsibly. We delve into essential ethical considerations, including algorithmic bias, transparency, explainability, and privacy. You will learn to apply practical decision-support tools, such as the "AI Canvas" for strategic alignment and the "AI WHS Scorecard" to assess and mitigate risks effectively. Through real-world research findings and case studies, we illustrate both successful outcomes and common barriers to adoption, ensuring you understand the capabilities and limitations of current AI tools.

Key learning outcomes include:

• Understand the distinction between automation and AI, and how they shift HR from manual administration to strategic augmentation.
• Analyze the use of predictive analytics in recruitment, learning and development, and performance management to reduce bias and improve efficiency.
• Identify and manage WHS risks associated with AI, specifically focusing on psychosocial hazards like loss of autonomy and algorithmic surveillance.
• Apply the "AI Canvas" to map out the utility, design, and operation of proposed AI tools within an organization.
• Utilize the "AI WHS Scorecard" to operationalize ethical principles and conduct robust risk assessments.
• Implement governance frameworks that ensure transparency, contestability, and the "human-in-the-loop" to prevent ethical lapses.

By the end of this course, you will possess the knowledge to redesign roles and workflows that leverage workforce data for strategic advantage while safeguarding employee well-being. Join us to learn how to lead this evolution responsibly, ensuring that the human element of human resources is amplified, not replaced, by technology.