Hope your week 1 in 2024 went well.  The evolving landscape is leading to a situation where Human Resources (HR) departments are increasingly required to collaborate intimately with data science and technology teams.  This collaboration is essential to successfully initiating, experimenting with, and expanding the implementation of Generative AI (Gen AI) initiatives.  As these changes unfold, the integration between HR and tech-oriented teams becomes crucial for adapting to the technological advancements and harnessing the potential of Gen AI in various organizational processes.  

Draup’s vision suggests that Talent Acquisition (TA) and Workforce Planning (WFP) will become increasingly proactive and efficient in identifying the skills essential for organizational needs.  Instead of passively waiting for directives, TA and WFP are expected to increasingly play an advisory role, recommending the specific skills the organization should focus on acquiring or developing.  This shift towards a more anticipatory approach in talent management ensures that the workforce is aligned with evolving business goals and market demands.

Draup has developed a strategic framework to support this forward-thinking approach, conceptualized as a mapping of skills and Generative AI (Gen AI) applications across four quadrants.  This framework is designed to provide a clear and structured overview of how various skills intersect with Gen AI capabilities.

The Generative AI (Gen AI) use cases are segmented into four distinct categories, each representing a specific functional capability.  These categories are:

Summarization: This category focuses on the ability of Gen AI to condense large volumes of data or information into concise, comprehensible summaries.  It involves extracting key points, ideas, or themes from extensive datasets or long-form content, making it easier for users to quickly grasp essential information without delving into the entire data set.  This function is particularly useful in research, data analysis, and reporting.

Interpretation: Gen AI is employed in this category to interpret and make sense of complex data or information.  It goes beyond mere data processing to include understanding nuances, context, and implications.  

Cognition: This category represents the cognitive abilities of Gen AI, akin to human thinking processes.  It includes problem-solving, decision-making, and creative thinking.  Gen AI in this category can mimic human cognitive functions to a certain degree, enabling it to tackle tasks that require more than just data processing – such as strategic planning, innovative design, or simulating human-like decision-making processes.

Interaction: The final category is centered on the interaction capabilities of Gen AI.  This involves engaging with humans or other systems dynamically and responsively.  It includes conversational AI in chatbots, virtual assistants, and customer service applications.  

Superimposed on this matrix are the skills required across each quadrant.  (Both Tech Skills and Skills required for HR are depicted on this graph)

This perspective underscores the significance of several emerging HR skills, including proficiency in AI-powered tools, the development of innovative HR metrics, management of AI projects, adoption of human-centric design thinking, understanding of AI ethics and governance, among others. As the complexity of Gen AI use cases progresses, the demand for these advanced HR skills correspondingly escalates. This trend highlights the need for HR professionals to continuously evolve and acquire new competencies to effectively manage and leverage AI technologies in their organizational strategies and operations.