How businesses can prevent an AI lost generation – and why it matters to them

Artificial intelligence (AI) is changing the way we work at an unprecedented speed. By 2030, nearly 1.1 billion jobs could be reshaped as technology and global trends open new possibilities across the labour market. Every organization is navigating this transformation, rethinking roles, workflows and strategies in real time. Handled well, this shift has the potential not only to reshape work, but to strengthen how early careers are built and supported.

As this shift accelerates, employers have a clear opportunity and responsibility: to help early-career professionals become, and remain, employable. This is especially urgent for a generation whose early work and educational experiences were disrupted by the COVID-19 pandemic. Many young professionals spent critical years in isolation, missing out on in-person learning, mentorship and exposure to complex environments.

Now, as organizations contemplate automating entry-level tasks and integrating AI into workflows, important choices come into focus. Efficiency gains are tempting, but the impact on those just starting out is often overlooked. And when early-career pathways disappear, industries lose the pipeline of skilled professionals needed for long-term growth.

If automation advances without careful oversight, we could see the emergence of a “lost generation” of early-career talent – an outcome that can be avoided with the right leadership focus and design choices.

Early signs of strain are already visible and present a warning sign and a clear moment for action. In the US, unemployment among early-career talent aged 22–27 stands at 7.1%, about three points higher than the overall workforce. This gap is fueling distress among new graduates; 19% of the class of 2026 report feeling “very pessimistic” about the job market. Together, these signals underline why early-career development needs to be more deliberate right now.

The challenges facing early-career professionals today are compounded. The pandemic upended experiences that built confidence and judgment. Now, AI threatens to add new pressures on job prospects, mental health and wellbeing. Employers and leaders have the chance to reset how we support this generation, because when we do, we will strengthen both their careers as well as our economy’s growth and resilience.

Entry-level roles are where many of us learned the ropes, built confidence and found mentors who shaped our careers. When these roles are automated or removed without thoughtful redesign, organizations risk losing the talent who bring energy to teams and ideas that fuel innovation. Longer-term, consequences can include slower skill-building, thinner leadership benches and reduced adaptability. In addition, the absence of a strong pipeline of young talent often forces organizations to rely on hiring experienced employees at a premium, significantly elevating labour costs over time.

Early-career erosion also risks undermining overall workforce trust in AI, which stands at 46%. When early-career roles are automated or eliminated, AI is more likely to be perceived as a threat – a view held by 59% of young Americans – rather than a tool for development. When early-career talent is asked to adapt to powerful technologies without confidence or support, trust in both AI systems and leadership decisions weakens.

Aon’s Resilience Quotient, a collaboration between Aon and Gallup, is yet more evidence of this risk, linking workforce disruption to gaps between the speed of AI adoption and workforce readiness. For entry-level employees still forming their professional identity and judgment, these gaps heighten uncertainty and slow adoption, creating a source of organizational risk that should be an organizational advantage.

Organizations that aspire to lead in the age of AI must move beyond the false choice between automating entry-level work and preserving traditional roles at the expense of innovation. The real imperative is to redesign entry-level roles and modernize early-career pathways in ways that strengthen long-term talent pipelines. This means separating routine tasks from development opportunities — automating repetitive work while preserving and enhancing essential early-career learning.

To truly lead, organizations must also re-center early-career development on the human skills that are core to AI-enabled work. As AI takes on more transactional activity, it is essential to emphasize analytical thinking, ethical reasoning, collaboration and accountability. Providing clear guidance on responsible AI use in real-world contexts reinforces trust and ensures that human oversight remains central to the adoption of new technologies.

Finally, leadership in this space requires investing in mindsets. Prioritizing and rewarding learning agility, curiosity and adaptability — traits that are among the strongest predictors of successful AI adoption — helps create a culture where early-career talent see change as an opportunity for growth. Supporting mental health and wellbeing must also be part of this equation. The pandemic showed us that when organizations prioritize connection, flexibility and access to support, early-career talent is better able to adapt and thrive, even in times of uncertainty.

When approached with care, AI can be a catalyst for a broader reset — one that not only transforms work but also places wellbeing and human connection at the centre of the future workplace. The choices made today will determine whether AI becomes a catalyst for stronger talent pipelines or a force that slows workforce development and long-term economic resilience. In the age of AI, the future of work depends on more than technology. Early-career pathways need to support growth and opportunity. Organizations that invest in reshaping roles and developing talent alongside innovation will be better positioned to sustain growth, resilience and trust, strengthening both their workforce and the broader economy.