The first work week of 2025 is behind us, and I’ve encountered several intriguing labor market trends. These include the rise of Agentic AI, HR’s evolving strategies toward “power workers” or “super workers,” the rewriting of job descriptions to delineate human and AI workloads, and an increased focus on root skills to create clear pathways for learning essential digital tech stacks.

One of the most fascinating concepts I encountered during a webinar was “World Modeling.” DeepMind’s World Modeling initiative aims to develop AI systems capable of accurately simulating physical environments. This concept has exciting implications for enterprises: by maintaining a model of all operational locations, including the associated workloads and roles, organizations can unlock powerful tools for managing business continuity and responding to potential disruptions and changes. 

I reflected on how we can adapt AI and other tools to cater effectively to each specific job role. When you think about it, this is an incredibly daunting task. It requires a deep understanding of the unique nuances, responsibilities, and workflows associated with a wide array of job roles across an increasingly broad and diversified workforce. Each role has distinct demands, skill requirements, and operational contexts that must be considered to ensure AI tools are not only useful but also truly impactful. This adaptation process involves mapping out granular details of tasks, identifying areas where AI can augment human effort, and determining the skills needed to work effectively alongside these tools. Moreover, it also requires a strategy to account for variations across industries, organizational structures, and the evolving expectations of both employees and employers in a rapidly transforming job landscape.

In this email, I would like to present the Future of Work in the Age of AI (FWAI) Framework.

This framework presents a foresight methodology that outlines the dynamic interplay between human agency and artificial intelligence (AI) across various roles and time horizons. By analyzing the evolving capabilities of AI and their impact on human work, the framework identifies opportunities for:

1. Stable Roles with Incremental AI Changes: These roles face incremental AI advances and depend on how fast the enterprise moves into AI.
2. Roles Adapting to Productivity Tools (Power Worker or Super Worker):These roles leverage AI tools to enhance productivity and efficiency.
3. Leapfrogging with Generative AI (Power Worker Plus or Superworker+):These roles experience significant transformation through the use of generative AI technologies.
4. Roles Facing Redundancy and Reskilling: These roles risk redundancy due to AI-driven automation but offer reskilling opportunities.
5. Roles Disrupted Beyond Reskilling: These roles face significant disruption and may require extensive reskilling or alternative career paths.
6. Emerging Roles in the AI Ecosystem: New roles emerge to support and manage AI technologies and their integration into various domains.

The element of time is critical to this framework, as it allows for the observation of how roles evolve in response to AI advancements. This evolution is not immediate but rather unfolds over a period, with different roles experiencing varying degrees of transformation at different times. The framework emphasizes the importance of proactive planning in navigating these changes. By understanding the projected impacts of AI on different roles, individuals and organizations can make informed decisions about reskilling, role transitions, and strategic AI adoption. This forward-thinking approach enables stakeholders to harness the potential of AI while mitigating the risks of job displacement and disruption.

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