The video game industry, like many others, moves in cycles—or so the conventional wisdom goes. A few tough years should be followed by a boom, and vice versa; growth leads to consolidation leads to growth.
In terms of hiring and firing, the industry has certainly had a tough few years. Many thousands of jobs were lost in a wave of layoffs and studio closures. Some companies grew during those years, but not enough to absorb all the laid-off staff. Overall, the industry has significantly reduced its workforce.
You might expect that as the cycle turns by this point, companies will begin to expand again and create new teams. If so, then employment survey released this week by InGame Job This is disappointing, but mostly just confirms what is already clear from looking at the industry: green shoots of new growth are few and far between.
While there will always be reasonable questions about the representativeness of a voluntary survey (not least because people who have experienced a career break may feel more inclined to respond to employment surveys that could introduce systematic biases into the data), the year-to-year comparisons offered by a survey are less prone to such problems and are very instructive.
They paint a picture of an industry in which more people are involuntarily unemployed and fewer people are voluntarily changing jobs compared to last year. The latter indicator, which shows that people prefer job security to career advancement, is a clear indicator of a climate of insecurity.
For those forced to look for work, it has become a hiring market. Despite long-standing concerns about the industry's skills shortage, the reality (at least in European countries) is that there are so few open positions and so many candidates that employers have been able to reduce wage offers for new hires and freeze pay increases for existing employees.
So why is this happening? Why didn't turning the wheel return us to the growth phase of the cycle?
First, we need to get to the bottom of why the industry faced such a catastrophic wave of layoffs and closures in the first place. The reasons here are primarily economic, which is not surprising, and the trigger was exogenous – a sharp rise in borrowing costs after years of interest rates hovering around zero.
Higher interest rates sharply reduce companies' appetite for risk, and few industries have been as vulnerable to the decline in risk appetite as the gaming business. This is due to the industry's longer-term economic challenges, namely rising development costs despite largely stagnant revenue per user for most games. For years, strong audience growth prevented this problem from being addressed, but now audience growth has also stagnated.
The result is an industry that is not just focused on hits (as it always has been), but also an industry in which games that aren't hits have a hard time making money at all. When risk appetite was high and credit was cheap, many companies were happy to pour money into projects and studios in hopes of creating the next Fortnite or the next GTA, and the financial failure of most projects was an acceptable price to pay. As interest rates were raised and risk profiles changed, the industry's fragile fundamentals came under threat.
So, in answering the question of why the cycle has not turned upward, we can take into account the fact that this basic situation has not actually changed over the past few years. If layoffs have slowed, it's because most companies have already scaled back to their bare minimum, not because the conditions that caused those layoffs have changed. Interest rates remain high. Risk appetite remains dull.
However, there is now another factor in the mix. It's no secret that generative AI technology is being experimented with widely across the industry, but attitudes toward its potential vary widely between creative corner developers and people in executive and management positions.
It's rare to find a developer who hasn't played with AI tools and tried them out in various parts of their workflow – the games industry isn't known for its Luddites, after all – but their assessment is almost always cautious, to the point of lethargic. It's not because they're afraid AI will steal their jobs. Their interests are more practical; they will be able to see how error-prone AI is even in the tasks for which it is best suited, such as code generation. In any field, the effectiveness of AI tools deteriorates rapidly, and errors become more common as the problem being solved becomes more specialized; a huge problem in such a highly specialized field as game programming.
Developer concerns about AI adoption tend to focus on these pitfalls and the very real possibility that large-scale and careless use of AI will simply create a huge workload of broken code and resources that will eventually have to be fixed by humans—a potentially slower and more expensive process than simply doing it manually. Meanwhile, the promised productivity benefits for professional creators and developers using AI as a “co-pilot” simply do not materialize in properly controlled studies.
Unfortunately, this caution is not always shared at higher levels in the industry – where many have been caught up in the infectious optimism of sales pitches from artificial intelligence companies, which are currently spending investment money at unprecedented levels (all that money that is pointedly not being invested in risky game projects still has to go somewhere).
AI companies are motivated solely by the desire to grow their numbers in order to secure the next tranche of venture capital investment, and have made outrageous claims to achieve this goal. They paint a picture of a nearly achievable future in which expert productivity will be boosted by orders of magnitude with the help of AI assistants, and all but the most complex tasks will require no experts at all. The gap between idea and implementation will be closed by the steps of an all-knowing AI.
AI tools will of course evolve and improve from where they are today, but the gap between what is actually possible now (marginal utility in specific scenarios with careful oversight by experts) and what is promised in the near future is incredible in the most literal sense of the word.
However, this is due to the difficult employment conditions in the industry, because in recent months I have repeatedly heard – directly or second-hand – of senior executives opposing hiring more employees on the grounds that they want to “wait and see how the AI turns out.”
This is by no means unique to the gaming industry – it happens in virtually every industry that involves people sitting in front of a computer in any context, and has an even greater impact in some other areas than gaming. However, it perhaps hurts more here because it comes after those years of mass layoffs; Every company that delays hiring out of fear that ChatGPT will be able to do its job by next year is another skilled worker sitting idle, reconsidering their career choice, and potentially lost to the industry forever.
I don't think AI can be blamed for much of the current employment situation – economic factors such as interest rates and fears of a spending-driven recession are much more directly responsible. However, the dream of AI-driven productivity leaps has certainly further dampened the appetite for hiring at many companies.
The consequences of this may be felt for many years to come. Games are developed in cycles that now last more than half a century in many cases, meaning that studios that make the wrong bets at this point in the cycle—for example, those that bet too much on AI revolutionizing development in ways that current data simply doesn't support—will likely be paying for those mistakes for a long time.
After the peak years of the COVID-19 pandemic, we noticed a delay in the game release schedule. Studios that were able to quickly adapt to things like remote work were able to release well-polished games on surprisingly tight release dates as other games faced huge delays. Some of the era's biggest commercial hits reaped just such rewards.
Likewise, bets made now—on generative artificial intelligence and on the growth of the industry as a whole—will pay off not today or tomorrow, but in three to four years. It appears that being prudently cautious about the future of AI will pay significant commercial dividends at this stage. There is no better way to start working on this than by developing recruitment policies that take advantage of the huge surplus of talent in the job market right now.
