Last week, Amsterdam-based tech company Bird laid off 90 employees within the space of just seven minutes. By using AI, the remaining 80 percent of the workforce would still be able to get things done just as efficiently as before. Major layoffs have become commonplace within the tech industry over the past year. It raises the question of whether or not the situation at Bird is illustrative of Big Tech. Is AI primarily a way for companies to ‘slim down’ by laying off staff?
The framing of business AI adoption as a ‘slimming down’ process is not of our own making. Marketing expert Scott Galloway compared the impact of AI in conversation with Fortune with the supposed dieting miracle drug Ozempic. Not everyone tends to specify what kind of AI they’re really talking about, but many executives see it as a productivity game changer. Companies can choose whether to reap the AI rewards by either firing people or by making them do more.
Bird knew which option to choose. The company fired 90 of its well-paid sales people “in an unadulterated American fashion”, as Computable describes it. They were no longer needed, CEO Robert Vis had concluded. While Galloway suggests that AI will be a silent job-cutter, Bird loudly carpet-bombed 90 jobs that are alleged to have become redundant because of AI.
In any case, the move is entirely in line with IBM CEO Arvind Krishna’s prediction mid-last year that white-collar employees are the first to risk losing their jobs because of AI. He estimates that IBM could get rid of 30 percent of its current workforce in the next few years, which in raw numbers amounts to 7,800 jobs. Other companies such as language platform Duolingo and financial service provider Klarna also point to AI as a possible job replacement.
Layoffs and vacancies
Whether Bird’s choice is the right one remains to be seen. It is not the only company that seems to see AI as an alternative to human beings. Google, which has long shied away from major rounds of layoffs, is also a year into a drastic course correction that will cost thousands of jobs. The main aim is to be able to spend more money on developing AI. It makes it crystal clear what the cuts aim to accomplish: the financing of new jobs that will enable more staff reductions in the long run.
Job openings for AI-related positions are now plentiful, at Google and other companies. To fund payroll costs for such positions, tech companies are cutting jobs in “non-strategic” areas that do not directly contribute to technological innovation. In that case, then, we’re not really talking about AI directly replacing jobs, but people having to complete the same work with fewer colleagues. This is nothing new.
It ensures that AI currently plays an ambiguous role in the labour market, as Fabian Stephany of the Oxford Internet Institute estimates. The advance of AI may indirectly lead to layoffs by redistributed budgets, but no one is immediately replaced by an algorithm. Speaking with Business Insider, he observes, “Fighting against robots is a nice cover story. But if you have a closer look, it’s often old school, simple economic dynamics like outsourcing or lead management cutting costs to increase salaries in other places.”
A good excuse
For now, AI seems mostly a good excuse to lay off employees as usual, as Meta CEO Mark Zuckerberg also suggests. According to him, companies have simply inflated themselves too much (they have “overbuilt” themselves, to use his parlance) to maintain all their employees.
The magic word is efficiency, which is usually a go-to argument for companies in the face of economic headwinds. The global economy is expected to grow by a very slander margin in 2024, so tech companies, and others, are rather cash-strapped. Significant cost reductions are therefore strongly rewarded by Wall Street investors. This does raise the question of when to stop laying people off, because for obvious reasons you can’t do it indefinitely.
IT teams squeezed
That salaries need to go up elsewhere to make AI a real success is repeatedly shown. Red Hat research shows a lack of AI knowledge is one of the biggest pain points according to IT managers. 72 percent of those surveyed see it as a problem, making it almost as likely to cause headaches as a lack of strategic thinking within a company (73 percent).
A striking pairing, since these two issues seem more intertwined than ever. After all, AI should now be the innovation where an organization can create a lasting advantage against the competition. IT teams are meant to enable exactly that, but are held back from such initiatives. An overly heavy workload, budget constraints and a constant need to keep up with change all undermine IT success, the same research shows. A talent shortage only makes the AI revolution harder to attain.
More employees needed
AI tools need better implementation to reach their potential. Paradoxically, then, more workers are needed elsewhere to enable a smaller workforce. That new manpower must focus on using AI as effectively as possible. That means setting clear frameworks around allowable resources, leveraging enterprise data for more useful AI insights and the ability to keep innovating in this area. So in principle, these kinds of AI implementation jobs would not be temporary. But that’s not what Bird was talking about, with them instead suggesting that AI is already far enough along the way to eliminate jobs. There is no evidence for that.
There is still much to be gained for organizations in this area, with Zscaler finding that only 39 percent of organizations see AI above all as an opportunity rather than a threat. On top of that, the average employee has a lot less favourable things to say about AI than executives. Instead, 47 percent of them point to CEO tasks that can be largely automated. There is clearly a sentiment within organizations that people need to do something with AI, but there is no clear notion of what exactly it will, and should, do. For now, true AI success is still a long-term aim for most organizations, even if they are already using GenAI tools.
Made redundant?
Numerous experts have high hopes for AI in the long run. The expected earth-shattering change is quite often compared to the industrial revolution or the invention of the printing press in the late Middle Ages. But the potential real impact that AI will have in the long run is much greater. Generative AI, that is, AI that can generate something that didn’t yet exist, is still very young. LLMs have only been commonplace for a year, and Big Tech has only had mature GenAI platforms available for a few months. Organizations have barely had time to adapt and develop strategies that work over the longer term.
And yet AI is already leading to the mass sackings of employees? All while remaining employees are at best only marginally more productive thanks to the same AI that makes their colleagues lose their jobs? It seems more likely that AI is simply being used as an excuse for ordinary cutbacks.
AI can only really be utilized when there is enough expertise in-house to implement it. Initially, that’s something that will cost money – potentially a lot, given the constrained AI talent pool. Given that’s the case, nobody should pretend that their mundane round of layoffs is actually an advance on all sorts of spectacular AI upheavals. In fact, companies don’t yet know whether those “redundant” workers are actually going to be as redundant as currently imagined, because most companies and organizations just don’t know enough about it yet.
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