If you’re an executive you’ve undoubtedly read or have been told, “There’s a talent shortage.” In many cases, whoever asserted this might very well be right. There are talent shortages in many job families, in many geographies, in many age cohorts, etc. On the other hand, the statement might be completely wrong. Much like the myth that Ai is transforming all jobs at similar speeds, this myth oversimplifies what’s truly going on. When decision-makers adopt a blanket narrative like “there’s a talent shortage,” they risk directing resources in ineffective ways, overlooking internal mobility opportunities, and entrenching hiring requirements that unnecessarily limit candidate pools.
Data from leading labor market intelligence platforms underscores this point. The reality is far more nuanced: some job families are under immense strain, with forecasted shortages growing more severe, while others have stable supply or even surpluses. Still others are evolving so quickly that titles and requirements haven’t caught up with the work itself. As a result, executives, talent acquisition functions, and hiring managers may miss people who are perfectly capable of thriving in new roles – if only given the chance.
The World Economic Forum’s Future of Jobs 2025 report makes the picture even clearer. By 2030, employers expect to create ~170 million roles and displace ~92 million, a net increase of ~78 million jobs worldwide. That’s churn at scale, not a simple shortage. The implication: not all roles are disappearing, not all roles are in demand, and not all shortages are inevitable.
Lightcast’s Speed of Skill Change shows that one-third of the skills for the average US job changed from 2021 to 2024, and in the top-quartile of roles, 75% of skills turned over. That’s why a “talent shortage everywhere” story collapses on contact with reality – the work itself is morphing underneath the titles.
Draup’s August 2025 research on role convergence finds Software, IT, and Data Science functions are blending – developers embed ML, data scientists run CI/CD, IT manages Ai-native cloud. The bottleneck isn’t “raw talent scarcity” as much as hybrid, cross-domain skillsets and targeted reskilling at pace.
Despite all the above, employers keep dialing up demand for durable skills (communication, problem solving, leadership). In Lightcast’s Aug 2025 update with America Succeeds, 76% of postings request at least one durable skill, and 47% request three or more – with strong growth even in technical fields. These capabilities travel across roles and cushion disruption.
BGI’s recent work likewise stresses that foundational skills endure – and that skills-first pathways are increasingly key for mobility, especially as credentials alone tell less of the story than they used to.
The platforms also converge on a simple idea: map the work and the skills, not just the jobs. TechWolf shows how Ai-inferred skill profiles (built from real work data in tools like Jira, Git, etc.) are more current and less biased than self-reported skills – fueling smarter internal mobility, reskilling, and workforce planning. Case studies point to large enterprises mapping skills across most of their workforce in months and reducing time-to-hire by double-digit percentages once skills signals are live in HCM.
And if you still need a macro nudge, BGI’s 2025 Skills-Based Hiring analysis finds many firms say they’ve dropped degree screens, but few have fully operationalized skills-based selection. The opportunity is to close that say-do gap.
Revelio Labs’ August 2025 outlook highlights broad cooling: active US job postings are ~45% below early-2022 levels. Posting declines are widespread, with entry-level opportunities hit hardest, even as unemployment stays relatively low overall. Healthcare remains one of the few net job-creating pockets, yet Revelio still sees declines in healthcare postings, a reminder that “demand” and “postings” don’t always move in lockstep.
BGI’s No Country for Young Grads (July 2025) adds a sobering layer: many entry-level knowledge tasks have been automated or re-bundled, creating structural underemployment for new grads. The report points to an Ai-powered “expertise upheaval” that strips out junior tasks, while employers staff leaner and hire more risk-aversely. Translation: the talent is there; the early-career work scaffolding isn’t.
The myth isn’t entirely baseless. In certain domains, the shortage is both real and severe.
Skilled trades. Across the US, demand for electricians, plumbers, HVAC techs, and construction workers is robust while experienced workers retire and pipelines lag. Regional dynamics matter (e.g., parts of the Midwest and South). The practical fix is long-horizon: scale apprenticeships, modernize training, and make these careers visible earlier.
Healthcare. The aging population keeps pushing up need for nurses, aides, and geriatric specialists. Even in a cooler posting environment, unit-level staffing, burnout, and geography create real access gaps. WEF’s 2025 outlook expects care roles among the most in-demand through 2030, reinforcing that “shortage” here is largely skills-and-capacity (not just headcount).
Ai-related roles. Demand is surging, but titles are squishy and requirements often unrealistic. Draup’s convergence research shows why: the needed portfolios are hybrid. Many candidates have adjacent skills but get filtered out by rigid postings (“3+ years LLM ops,” etc.). The fix lives in targeted upskilling and capability-based hiring.
At the same time, many administrative and entry-level knowledge roles (repetitive work in law, tech, marketing, customer support, finance) are seeing demand stall or decline. Revelio notes postings are down sharply overall – ~45% below 2022 levels – with entry-level hit hardest. BGI adds the structural lens: junior tasks are getting automated or bundled into higher-skill roles, so early-career pathways need redesign, not generic “shortage” rhetoric.
Importantly, many of these professionals aren’t “unskilled” – they’re mis-matched to where the work is going. That’s why a skills, tasks, and workflows view beats static job titles. Platforms like TechWolf help orgs see what employees actually do and how tasks are shifting, unlocking internal mobility and targeted training that job-based plans miss. This is also why students, early-career pros, and career-transitioners benefit from building task-based, Ai-enabled skills portfolios – portable proof of work aligned to durable skills.
To move beyond the myth of a universal talent shortage, leaders need a sharper lens on what work is being done, who or what is doing it, and how it connects to organizational priorities. Too often, workforce planning is reduced to a headcount exercise, when in reality it requires a broader, more systemic view. It’s not simply about having enough people – it’s about having the right capabilities, capacity, cost structures, constructs, and culture to sustain performance over time.
The visual below captures this challenge. As work shifts across employees, contractors, consultants, outsourcers, automation, and Ai, leaders must decide not just how many people they need, but where and how work is best done to deliver both competitive advantage and long-term sustainability.
With this in mind, here are Five Key Considerations for Workforce Planning, expressed through the lens of the 5 C’s:
Workforce planning is no longer just about filling roles – it’s about designing systems where skills, structures, and culture align with strategy and adapt as conditions shift. By applying these five considerations, leaders can move from reactive hiring to proactive workforce design. The real opportunity is not simply solving for shortages, but building an organization that learns, flexes, and evolves as work itself evolves.
Yes, some sectors face urgent and growing talent shortages – but the catch-all claim “there’s a talent shortage” (everywhere, all at once) is a myth. It obscures what’s really happening. We don’t just have a hiring problem. We have a workforce planning problem in organizations and, frankly, in our communities, states, and country. The good news: organizations can mitigate risk by leveraging relevant data, appreciating the nuances, and improving how they formulate, measure, and manage their workforce strategies.
It’s time to retire Myth 2 and replace it with a new mindset, one that seeks to understand the work, actively develops necessary skills, thoughtfully leverages Ai/technology, and ultimately builds an Adaptable Organization that flexes to meet the evolving needs of the future.
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.