Published on 30th April 2025
Within the greater workforce AI adoption revolution, we’ve recently seen an interesting HR trend—employers are ramping up AI literacy and training efforts, as well as operations themselves, by bringing in contingent or temporary workers to train permanent employees to use these new tech tools.
The reason is fairly straightforward: Many companies simply lack in-house AI expertise. And regulatory requirements are forcing companies’ hands as well—in Europe, for example, the EU AI Act is pushing companies to improve AI literacy, with the broad acknowledgment that not enough people have the necessary knowledge to keep up with the pace of digital transformation.
Consequently, many companies are bringing in contingent workers—whether temporary, outsourced or project-based—because they need people with this specialized expertise. This is especially common in digital and tech fields, where talent shortages become all the more pronounced as technology evolves.
For these AI and tech specialists, being hired on an ad-hoc basis aligns well with their working preferences. Many of them prefer flexible, nontraditional work arrangements rather than being tied to a single employer. We’ve seen that they tend to prefer open environments and flexible hours—they don’t want to be locked into one company. Many choose to work as contingent workers, whether through agencies or their own project-based contracts. (At least in the EU, agency workers often receive additional benefits and support from the staffing firms that employ them; therefore, many workers prefer this arrangement over freelancing because it provides more security while still offering flexibility.)
As a result, this free-floating, unattached workforce—whether contracting through agencies or as individual “guns for hire”—currently holds a disproportionate amount of the AI expertise that companies need.
The Business Case For Contingent Workers
Though many people assume that cost savings are the main reason companies use contingent workers, that’s not necessarily the case. The real benefit is access: In a world where AI and tech expertise is scarce, businesses need a way to bring in high-level talent with rarefied skill sets exactly when they need them. And access to a truly global talent pool—whether through agencies or direct hiring—gives companies the flexibility to bring in exactly the right people for each project.
But beyond filling temporary roles, there’s also a major workforce upskilling aspect. In Italy, for example, we see a strong focus on continuous re-skilling. Ideally, companies would handle this internally, but many don’t. That’s where agencies play a key role; many of the largest staffing firms invest heavily in training funds, education programs and upskilling initiatives to ensure their workers stay at the cutting edge of their industries and are ready to enter companies and begin disseminating high-level skills.
Best Practices For Companies In Need Of Skills
For any growing company today, developing a talent strategy is crucial for growth. Traditionally, companies focus on their product—but a major challenge now is making sure they have the right people to execute that vision. Particularly as AI tools advance relentlessly, both in implementation and in sophistication, more and more companies will be looking to recruit the skilled professionals they need—both to complete complex projects and to assist in leveling up the rest of their workforce.
But where to start?
A strong talent strategy requires visibility. You need data on your current workforce: where the gaps are and how those gaps align with your business goals. Experience tells us that companies need a mix of permanent employees and flexible talent. The key is understanding where flexibility makes the most sense. Larger companies with strong in-house HR might think they can manage this themselves, especially now, with AI-driven recruiting tools. But what those tools can’t do is provide a strategic, forward-looking approach.
A lot of times, job descriptions don’t actually capture what a company really needs. That’s where industry partners such as specialized agencies come in—not just to help fill these roles, but to offer support in designing the best talent strategy.
Take the automotive industry right now—it’s in complete transformation, and there aren’t enough engineers to meet demand. Car companies want to be at the cutting edge of innovation, but they can’t afford to have every type of specialist on staff. So they partner with agencies or outsource key R&D functions. When household-name luxury car brands need, say, a new brake system, it’s not actually their in-house engineers developing it; the engineers at the helm are part of specialized firms that supply the auto industry. That’s the working model we’re seeing more and more—companies relying on external experts to drive innovation.
Interestingly, these experts often have experience across multiple companies—including competitors. So when you bring them in, you’re not just getting an individual—you’re benefiting from a collective knowledge base of best practices.
Ethical Considerations At The Forefront
Ethics around hiring and AI use are a key differentiator between well-regulated industry players and those operating in a gray area. When there are bad actors, they hurt the reputation of their industry as a whole.
Enterprise-level organizations benefit from using renowned agencies to vet workers, ensuring they meet ethical standards. When AI is involved—whether in hiring, workforce management or product development—these ethical considerations must be nonnegotiable.
AI products, in particular, need diverse input. If you’re building an AI-driven tool but only testing it on a homogeneous group (say, young white male engineers), the end result will be flawed. Companies need diversity in their development teams and in the data used to train AI. And from a product perspective, it’s simple: If you don’t test across a diverse population, your AI won’t work properly.
Some user companies will already have their own ethical AI policies. If they don’t, global oversight confederations like ours can help, and big firms will often partner with workforce solution providers to develop these frameworks. Microsoft, for example, has strong ethical AI policies and partners with several agencies. Co-creation is the goal, but at a minimum, companies should prioritize ethical hiring and AI development.
Some Final Thoughts
The effort to obtain and implement the exact right talent for the moment sometimes stymies organizations; they may balk at costs, be unsure what kind of talent they need or have lingering confusion about how best to implement precision skill sets within their company and workforce.
True expertise and rarefied technical skill come at a premium because they are scarce commodities—and their value cannot be overstated. Simply put, the alternative is stagnation; if you don’t bring in the right talent at the right time, you risk falling behind on innovation.
First published by Forbes, April 2025
