Lecture on AI Impact on Human Capital Management (HCM)

Introduction

• Presenter: Don McCon, Director in Barretts Technology and Services Group
• Sector: Human Capital Management (HCM)
• Colleagues: Brett Shock, Andy Ladaro, Seb Diller, Simon Pearson, Helen Jones
• Three Core Verticals in HCM:
  • Talent Acquisition
  • Talent Management
  • Workforce Administration
• Barrett's Expertise: Extensive expertise in services, tech-enabled services, and software.
• Topic: How AI will impact the human capital sector.
• Panelists:
  • Steve Ctz, HR Transformation Service Leader, Ernst & Young
  • Jamal Justice, Ernst & Young, People Advisory Services
  • Dr. Eve Alexander Mona, AI Thought Leader, Associate Professor, Imperial College London

AI Advancements in the Past Two Years

Deep Learning Revolution

• Key Points:
  • Availability of data and computing power allows models to learn directly from raw data.
  • Models can transfer knowledge between tasks.
  • Dramatic improvements in production capabilities.
  • Useful across businesses, including HCM.

Generative AI

• Key Points:
  • Focuses beyond prediction to content generation.
  • Can generate text, images, audio, video, synthetic data.
  • Transforms how models are built and their applications.

AI Impact on Businesses

• Three Main Areas:
  • New insights and forecasting
  • Automation of tasks for efficiency
  • Creation of new products and services
• Applications in HCM:
  • Automation in consumer services, HR functions, and job matching.
  • Enhancing productivity and freeing up human talent.
  • Improved consumer experience and risk management.

AI in Talent Acquisition, Management, and Workforce Administration

Talent Acquisition

• Applications:
  • Automating monotonous tasks: screening resumes, scheduling interviews.
  • Generating job descriptions and removing bias.
  • Predicting hiring trends and staffing needs.

Talent Management

• Applications:
  • Personalized employee experiences: Learning and development, benefits plans, communication styles.
  • Optimizing talent allocation.

Workforce Administration

• Applications:
  • Automating routine tasks: timesheet management, leave tracking, compliance reporting.
  • Predictive models for smarter workforce planning.
  • Skills identification and future workforce needs.
• Payroll Processing:
  • Automating data entry tasks and predicting payroll costs.

Implications for HCM

• Generative AI:
  • Facilitates moving from low-value to high-value tasks.
  • Enhances proactive, predictive, and personalized functions.
• Competitive Considerations:
  • AI can provide significant advantages or disadvantages.
• Risk Management:
  • Importance of responsible AI deployment.
  • Examples of missteps in AI usage.

Practical Applications and Current Efforts

Personalization in Learning and Development

• Content Creation: Generative AI in developing personalized learning content.
• Digital Workforce: Side of desk AI utilities for discrete functions like recruitment.

Worker Productivity

• Chatbots and Virtual Assistants:
  • Facilitating onboarding and answering employee questions.
  • Analyzing structured and unstructured data for payroll and benefits queries.
• Content Generation: First drafts of communications, ideation of interview questions.
• Predictive Modeling: Attrition prediction and model maintenance.
• Bias and Risk Management: Awareness and adjustment of biases in AI models.

Lessons and Challenges in AI Implementation

Corporate Strategy and Alignment

• Importance: Ensuring alignment between AI efforts and overall strategy.
• Data Readiness: Solid foundation in data structure and governance.
• Governance Structure: Top-down governance intersecting all areas of AI implementation.

Agile and Incremental Approach

• Methodology: Proof of concepts and prioritized use cases.
• Organizational Readiness: Assessing talent and culture readiness for AI adoption.

Final Thoughts

• Technological Advancement: Rapidly accelerating and reshaping business operations.
• Competitive Risk: Importance of adapting to AI to avoid being left behind.
• Operational Foundations: Need for continuous improvement and alignment with AI capabilities.

Conclusion

• AI's Future: Continues to evolve and impact the HCM landscape.
• Thank You: Appreciation to panelists and viewers for their participation.