When it comes to artificial intelligence (Ai), a dangerous oversimplification is making its way into boardrooms and executive strategy sessions: the belief that Ai is transforming all jobs at similar speeds and to similar magnitudes. It’s not.
Despite this, assumptions of worker productivity gains are being made with little understanding of the true implications Ai is having on the very nature of work in specific job families. The reductions in force we’re seeing in many organizations are thus adversely impacting the work experience of those who remain. This creates significant short-, mid-, and long-term costs, many of which are hidden before a crisis shows itself. Any recent stories come to mind?
To debunk the myth and move past it requires an appreciation of nuance that few leaders have the patience to understand. “We just gotta go,” they say. While I appreciate that leaders have to move fast in a fast-moving world, the question arises: When making quick decisions that’ll have big repercussions, what are you and your fellow leaders basing those decisions on? Hopefully, you’re setting up a process that provides the insights and ideas that will enable wise decisions – ones that reduce risk and increase the probability that the decisions reap the desired return. Have you?
If such a process is set up, it’ll undoubtedly address what I call the dimensionality of change. In essence, this means that change – for example, the impact of Ai – will be different in different job families, locations, and regions. Making broad assumptions does not appreciate this dimensionality. Particularly as we explore the impact Ai will have on humans at work, measuring, analyzing, and understanding the nuances down to the job family, role, and task is critical.
Just as no two roles are identical in scope, creativity, or context, no two roles are experiencing Ai’s impact in exactly the same way. Some job families – like those in data entry, customer service, or legal review – are being changed quickly and significantly. Others, such as roles in the trades, healthcare, and business strategy, are experiencing a slower, more subtle evolution. In such roles, day-to-day tasks are evolving rather than their work disappearing.
This reality matters. Leaders must stop asking, “What jobs will Ai eliminate?” and start asking, “How is Ai reshaping work within each job family, and how can we build a sustainable, adaptable organization that leverages Ai while honoring the human experience of our employees?”
A growing body of research – including studies from Stanford’s Digital Economy Lab and Revelio Labs – reveals that Ai is impacting early-career roles far more rapidly than others.
This disproportionate impact underscores the need for job-family-level visibility and role-specific planning.
According to Lightcast, demand for generative Ai skills has exploded:
However, these roles are concentrated in mid-to-senior tiers of the workforce. Early-career access to Ai-enhanced opportunities remains limited.
Contrary to the narrative that Ai only impacts blue-collar work, Revelio Labs and Draup data show:
Ai-related change is not just technical – it’s emotional.
According to Revelio sentiment data and the Worker Angst Index from Fractional Insights:
The World Economic Forum’s Future of Jobs Report 2025 forecasts:
The net gain masks a highly uneven disruption – one that demands more thoughtful analysis and planning.
What this all points to is a simple truth: there is no one-size-fits-all Ai strategy. Dimensional thinking recognizes that organizational change is not simple. Sorry leader, your job is to deal with complexity. Dimensional thinking appreciates this complexity, works to understand it and, in turn, helps make wise, well-informed decisions. With this in mind, from an executive level, there are four primary layers to consider when employing dimensional thinking:
|
Dimension |
What It Illuminates |
|
Task-Level Disruption |
What specific tasks within a role or job family are being augmented, automated, eliminated, or otherwise changed by Ai? |
|
Human Factors |
How is Ai impacting humans at work? Is Ai elevating productivity and value or is it creating more work and noise? |
|
Contextual Relevance |
How do industry, geography, culture, and regulatory environments shape the pace and direction of change? |
|
Decision Infrastructure |
Is there a cross-functional, leader decision-making process that uses timely, relevant, and actionable insight about Ai’s impact on the workforce? |
While People Analytics and Talent Intelligence can provide valuable macro-level trends, the richest insights often come from the people actually doing the work. What a thought, right? Listening to and learning from frontline employees, team leads, and functional experts will reveal where the friction lies, what tools are helping, hindering, or simply not relevant, and what is believed to be most helpful moving forward.
The takeaway: Understanding what’s happening at the job-family, role, and tasks levels is no longer a “nice to have” – it’s a strategic necessity.
To navigate this complexity amidst ongoing external change, forward-thinking organizations are going beyond People Analytics, Workforce Planning, Talent Intelligence, and EX/Employee Listening strategies. They’re bringing these together to do the following:
If you’re committed to building a future-ready, human-centric, adaptable organization in the age of Ai, then these five considerations are essential.
The truth is, Ai isn't impacting all jobs at the same speed – and pretending otherwise puts people, performance, and purpose at risk.
If your leadership decisions are based on generalities, you’re likely missing what matters most – the human-level reality of change. But when you lead with dimensional thinking, you create room for insight, agency, and growth. We’re not facing a single future of work. We’re facing an infinite number of futures, each shaped – if not outright created – at the intersection of technology, humanity, and leadership.
To learn more about the other Myths click here. And to learn how to assess your organization’s adaptive readiness and, in turn, build executive decision-making processes rooted in timely, relevant, and actionable insight, follow and connect with me here on LinkedIn. Finally, be sure to subscribe to the Future of Work Advisors Newsletter.