The context
Generative AI has democratized since 2022 across pretty much every creative field. Gamification, still emerging but growing fast, is no exception. The challenges of AI-assisted creation are already well documented in graphic design or writing, but our line of work has its own specifics. It’s rooted in bespoke design, in service of a message, an event, or a precise client need. It relies as much on creativity as on adaptability.
Hence the real question, the one that’s been on my mind for a year at Albus Factory: are these tools a valuable aid for designing gamified experiences, or do they risk hollowing out their singularity?
What AI actually does in our projects
Right from the briefing stage, AI can analyze large quantities of content and surface the client’s key issues. On a recent project, I spent two full days reading and synthesizing internal documents to extract the top priorities. With a good prompt and careful filtering, I could probably have cut that time down to half a day.
For ideation, it’s useful for breaking through the blank page. When you want to challenge a first mechanic or broaden the range of proposals to present to a client, AI offers variants, angles, inspirations. Not enough to replace a real design phase, but enough to speed up the warm-up.
For content writing, it’s even more direct. Game prompts, facilitator notes, rule rewrites that need to fit on a client slide, document templates: all those long tasks AI unblocks in minutes.
On paper, the picture is enticing. Cost reduction, productivity gains, project clarity. But focusing too much on the immediate benefits, you risk losing sight of what makes the craft.
Where it really breaks down
The confidentiality problem. A lot of our projects involve data from listed companies, public organizations, or actors operating under strict rules (defense, banking). Feeding that content to a public-grade AI without a clear framework means exposing both the client and the production company to legal and reputational risk. No productivity gain justifies that.
The standardization problem. AI often suggests simple, unoriginal, generic mechanics. Logical: it builds on what already exists, so it reproduces the dominant patterns of its training data. In graphic design, an “AI aesthetic” is already emerging, recognizable at a glance. In gamification, it’s the same. An AI-generated mechanic stands out fast: flat, shallow, no strong link to the client’s universe or stakes.
The intellectual property problem. The legal framework is still fuzzy, but public perception isn’t. Even if a game mechanic isn’t legally protected, a client can find themselves exposed to plagiarism accusations if a mechanic resembles another one too closely. No legal fault, but a real reputational risk.
The meaning problem. A company wants to raise its employees’ awareness on environmental and social issues, and the game is largely designed by AI. Considering the ecological footprint of these technologies, that’s a contradiction. Even Sam Altman, OpenAI’s CEO, admits he doesn’t know how to measure this technology’s energy needs. What message does that send to the client, and beyond, to its players?
The real issue is the promise we make to the client
When a client invests in a bespoke experience, they’re buying a precise promise. That the game is designed specifically for their content, their message, their audience. The moment AI takes too much room in the chain, that promise cracks.
The difficulty is that most of our clients aren’t gamification specialists. They sense the potential but don’t always grasp the design costs behind it. Budget trade-offs therefore often land on the line items they understand least: game design, graphics, development. The difference between a basic mechanic and a thoughtfully designed experience isn’t always visible from the client’s seat. As long as the message lands and the visuals are clean, the depth question takes a back seat.
That’s the context in which AI can look like a practical answer. And that’s exactly where you have to stay clear-eyed.
Where I draw the line, today
At Albus Factory, AI is an occasional tool, never the main creative engine. In my own use, I lean on it to kick off ideation, proofread or rephrase content, simplify texts meant for facilitators or clients. But every time, I step back from what comes out. The right questions:
- Is this mechanic genuinely consistent with the client’s context?
- Will it stick with players, or will it just be functional?
- Will the experience hold meaning once it’s lived on the ground?
The most important line not to cross: no tool replaces a game designer’s ability to anticipate a mechanic’s emotional impact, a game’s systemic logic, or the intelligence of its progression. AI doesn’t see players’ faces. It doesn’t know what makes an experience stay in memory.
And tomorrow?
AI isn’t good or bad in itself. Our uses, intentions, and standards are what give it meaning, or strip it of any.
In gamification, two scenarios coexist. If clients become more aware of what a truly tailored experience looks like, bespoke design will keep its place. AI will stay there as a discreet assistant, a facilitator, never a driver.
If, on the other hand, budgets shrink and gamification becomes just another standardized, automated communication channel, then AI will take the lead, at the expense of creativity. And probably also at the expense of the actual effectiveness of these projects.
That’s why the game designer’s role stays essential. Not to reject AI, which is already part of our daily life, but to frame it, to defend a coherent design approach in the face of these tools, to explain to clients what they gain by investing in real bespoke work.
Personally, I’m convinced there will always be room for strong, well-thought-out experiences genuinely designed for their audiences.
One question remains: how much of the market will still leave that room a few years from now?
Sources & further reading
- IT for Business, Les principaux risques de l’IA générative et comment y faire face (FR)
- Reporterre, L’insoutenable coût écologique du boom de l’IA (FR)
- Growth Engineering, 19 Gamification Trends for 2022–2025
- 20 minutes, La gamification en entreprise, ça change vraiment quelque chose ? (FR)
- Spielecheck, AI in game design: future technology or hype?
- ITSOCIAL, Le shadow IA fragilise la confidentialité des données sensibles (FR)