The GamesIndustry.biz HR Summit, held on October 1, brought together a wide range of industry professionals to debate the role of generative artificial intelligence in the modern games workplace. While many attendees acknowledged that AI tools can accelerate certain technical tasks—such as writing code snippets or handling repetitive, low‑value chores—the consensus was that the technology is far from the revolutionary solution some promoters claim it to be. In fact, the rapid adoption of AI is creating a host of new challenges for studios, from data‑security concerns to heightened employee anxiety, and even an unexpected increase in HR workload. One senior executive stressed that their studio has a strict policy of never allowing AI‑generated assets to appear in a shipped product.
The summit operated under Chatham House Rules, so the specifics remain confidential, but the speaker explained that while the company remains vigilant about protecting the final game’s integrity, it also recognises that AI can be useful in other, less visible parts of the business. "It’s a delicate balance," they said, noting that AI could streamline routine tasks that developers typically dread, such as asset naming conventions, basic UI layout, or simple script generation. Despite these potential efficiencies, employee fear is palpable. One manager recounted receiving late‑night emails from staff asking, "Are we using AI?
Does that mean I’m going to lose my job?" This anxiety is not limited to junior staff; senior leaders also expressed uncertainty about the direction AI will take and how best to plan for its integration. "We simply don’t know what the future looks like," admitted another senior figure, underscoring the strategic ambiguity that surrounds AI adoption.
Policy development is struggling to keep pace. At the previous year’s summit, only a small fraction of respondents said their companies had an AI policy. This year, a quick poll suggested most organisations now have some form of guidance, yet the speed of change is causing constant revisions.
One leader explained, "I drafted a policy two weeks ago, but a new prompt‑injection technique emerged yesterday, forcing me to rewrite sections immediately. The landscape evolves that quickly." Data leakage remains a top concern. Even when studios purchase enterprise‑grade AI models that promise not to use proprietary data for training, they have limited control over how individual employees might use consumer‑grade tools like ChatGPT on personal accounts. "Someone could paste confidential NDA‑bound information into a public model, and there’s little we can do to prevent that," a participant warned.
The consensus was that clear, enforceable guidelines about acceptable and prohibited AI use are the most pragmatic way forward. Confusion about AI’s purpose also hampers progress. "The biggest issue right now is that AI is presented as the answer, but people don’t really know what the question is," observed a speaker, describing several studios that want to "use more AI" without a concrete use‑case in mind.
The hype surrounding AI has led many to expect a panacea, yet the reality is more modest. One senior attendee bluntly stated, "I haven’t seen AI create anything genuinely fun.
It can replicate, sure, but it hasn’t produced anything entertaining on its own." The sentiment was echoed with a touch of humor: "You can crank out junk faster," another participant quipped. Regardless of personal opinions, the overarching message at the summit was unmistakable—ignoring AI is no longer an option. Companies that choose not to employ generative tools must still codify that decision in employee handbooks and enforce it consistently, while staying abreast of evolving capabilities and regulations. Understanding the current state of AI, aligning it with organisational values, and weighing both risks and opportunities were identified as essential steps.
As one speaker put it, "AI technologies are now encroaching on creative disciplines we didn’t even consider five years ago." The summit also mapped out a four‑stage maturity model for AI adoption. Most studios are still in the initial stage, experimenting with an enterprise licence for a model like Claude to let developers tinker with code generation.
Some larger studios have progressed to stage two, piloting AI in specific pipelines and measuring time savings against potential costs and liabilities. However, without firm governance, these pilots can backfire. One anecdote illustrated the dangers of unchecked AI use: an artist employed Gemini to generate shader code while a programmer was away. The resulting code violated the studio’s coding standards and AI policy, went unnoticed for weeks, and ultimately forced a build rollback.
In another case, a freelancer used AI to produce artwork that initially dazzled the community, but the hidden reliance on generative tools sparked backlash once discovered, negating any perceived time or cost benefits. These stories highlight a broader issue—many studio workflows rely on tacit knowledge held by individuals rather than documented procedures. When AI is introduced into such opaque systems, pilots often collapse because the underlying processes aren’t robust enough to accommodate automated outputs. From a human‑centred perspective, speed alone does not guarantee value.
Even if AI enables programmers to submit more code faster, the qualitative impact on the team’s experience matters. One speaker noted, "We can move faster, but the experience can be miserable when you spend hours shouting at an AI prompt that won’t do exactly what you need." HR professionals did identify some genuine advantages.
AI can help staff craft clearer emails or provide instant answers to routine queries about maternity leave, sick pay, or other policies. Yet the technology is also generating new burdens. Several attendees reported a surge in AI‑generated grievance letters—often lengthy, factually inaccurate, and littered with odd legal citations.
A legal advisor mentioned receiving roughly ten such letters each week, each demanding careful review despite their questionable content. HR teams are obligated to read and respond to these submissions, even when they contain nonsensical or incorrect information.
This adds to an already heavy workload. One participant recounted a nine‑page grievance that was largely incomprehensible, illustrating how AI can inflate the volume of paperwork without delivering substantive value. Banning AI‑written complaints outright isn’t a straightforward solution, as it could be perceived as discriminatory against employees who rely on assistance for writing. Some suggested practical mitigations, such as imposing a maximum word count on grievance letters or requesting specific details that AI would struggle to fabricate, thereby reducing the time legal teams spend deciphering them.
Overall, the consensus was that generative AI may be creating more work for HR departments rather than alleviating it. "We’ve seen HR teams shrink in headcount, but the amount of work has stayed the same or even increased," one attendee observed.
Moreover, relying on AI to answer employee questions can erode the human connection that is vital in sensitive situations. For example, an employee seeking clarification on maternity policy might also be dealing with IVF treatments and need empathetic support—something a chatbot cannot provide. The final takeaway was clear: AI can supply information, but it lacks heart, emotional intelligence, and the ability to read body language or sense underlying concerns. That human empathy remains the glue that holds the workplace together, and any AI strategy must respect and preserve it.