Biz: The brave new future of careers?

My thought process for this post started in an unexpected place: a BlueSky post comparing public sector wages across the Nordic countries.¹ The data presented a fascinating paradox. Contrary to the standard narrative of a bloated bureaucracy, Finland’s public sector spends significantly less on wages than its Nordic neighbors.

The conundrum got me thinking. If our public sector seems wasteful, but it’s not due to high personnel costs, what’s the real issue? The data suggests a few uncomfortable possibilities. We may have too few people, leading to an overworked staff producing subpar quality. Alternatively, we may lack the necessary skills, resulting in a constant and expensive reliance on external consultants and subcontractors to fill the gaps².

This public sector puzzle is a perfect mirror for a challenge I see across the private sector. Increasingly, we find ourselves at a peculiar crossroads, facing a profound failure of imagination. On one hand, we have roles we desperately need to fill—specialized, often highly paid positions. On the other, we have employees whose skills may be becoming less relevant³. The conventional response is to treat these as separate issues: hire for the new skills and, regrettably, fire for the old ones.

But what if, like in the public sector example, we’re misdiagnosing the problem? What if the actual, game-changing potential of Artificial Intelligence is not replacing knowledge work but fixing this deeper strategic misalignment? What if the winning formula is to use the Large Language Models (LLMs) not just to hire the best people but to build them internally?

If I’m onto something here, the idea isn’t just a theoretical win-win; it’s a practical one. It’s an actionable strategic imperative that could redefine how we approach talent, growth, and organizational stability by tackling one of the most significant hidden costs in business: employee turnover.

What if the winning formula is to use the Large Language Models (LLMs) not just to hire the best people but to build them internally?

Imagine taking employees who are facing role redundancy and offering them a direct, accelerated path to the very jobs you’re struggling to fill. By leveraging large language models (LLMs) as learning catalysts, we can create targeted training programs that build upon an employee’s existing knowledge and skills. These are people who already possess invaluable, often intangible assets: deep-seated cultural knowledge, an understanding of the business context, and the cultural imprint of your organization.

From an organizational engineering perspective, this is a genius move. You get a culturally aligned, highly skilled employee ready to contribute in a new capacity faster and more effectively than an external hire could. For the employee, it offers stability and career growth opportunities. For the company, it solves two problems at once. According to research from the World Economic Forum, nearly a quarter of all jobs are expected to change within the next five years⁴. If the prediction holds: continuous, embedded learning isn’t a perk; it’s a survival mechanism.

The Challenge Isn’t Technology, It’s Courage

While the logic is sound and the technology is increasingly capable, implementing such a strategy is far from simple. It requires confronting deeply ingrained business conventions and a level of leadership courage that is rare to find.

1. The Psychological Safety Net: You cannot ask an employee to undertake a challenging retraining journey if they are terrified of failure. Embarking on a new career path, even an internal one, is inherently risky. It involves admitting knowledge gaps, asking basic questions, and inevitably, making mistakes. This point was driven home for me recently when I was explaining the LLM-retraining concept to my spouse. She quickly pointed out that the psychological safety I take for granted in my progressive workplace is not a universal experience. It’s a profound exception. For this to work, organizations must cultivate a culture of profound psychological safety, where learning is celebrated, and failure is treated as a critical part of the process, not a punishable offense. For most companies, this isn’t a minor tweak; it’s a monumental cultural shift.

2. The Compensation Conundrum: This is perhaps the most significant hurdle. The roles we need to fill are often in high demand and, consequently, come with high market-rate salaries. The employees we consider for retraining can be in lower-paid positions. Are we, as companies, willing to retrain an employee for six months and then give them a 30%, 40%, or even 50% raise to match the market value of their new role?

Cold, short-term calculations might suggest it’s cheaper to hire externally. But this is where long-term vision is critical. The cost of turnover is staggering. Direct recruitment costs per hire are not that much, but the total cost of losing an employee—factoring in lost productivity, damaged morale, and knowledge drain—is estimated by SHRM to be six to nine months of their salary.⁵ Some analyses suggest it could be as high as twice their annual salary. Investing a fraction of that in the growth of a loyal, existing employee is a demonstrably better long-term investment⁶.

The question is: are we brave enough to try?

3. Leading with Data, Not Dogma: Ultimately, this strategy requires us to lead with actual data rather than relying on intuition or the pressure of a single financial quarter. We need to look beyond the immediate cost of a salary increase and measure the long-term return on investment (ROI). We must track metrics like employee retention, time-to-productivity in new roles, and innovation rates stemming from these internally mobile teams. Shift from viewing employees as an expense line item to seeing them as appreciating assets⁷.

The question, then, isn’t whether we can use LLMs to build lateral career paths. The technology is here. The question is whether we dare to challenge the organizational culture and financial models that block it. Are we brave enough to invest in the people we have, to pay them what their new skills are worth, and to build a truly agile, resilient, and knowledgeable workforce for the future?