If AI Feels Overwhelming, You're Probably Exactly Where You Should Be: The Five Stages of Adapting to Change

Sasha Melnova, HR Business Partner at SayGames

Over the past few years, all of us — both as individuals and as an industry — have had to adapt to an extraordinary amount of change. We lived through a global pandemic and the overnight shift to remote work. Many people had to leave their home countries because of war or political instability and rebuild their lives somewhere completely new. The games industry went through a prolonged period of uncertainty, with layoffs becoming part of the daily news cycle. And now we're facing yet another major shift: the rapid adoption of AI. Every time something like this happens, it feels unprecedented, as if we've never experienced anything similar before. But after years working in HR, I've started noticing something interesting: while the circumstances change, the way people respond to them is often remarkably similar.

When generative AI first entered the conversation, most of us were asking one question: Will it replace my job? Today, the challenge looks different. AI is already becoming part of how the games industry works. Teams are redesigning workflows, rebuilding pipelines and learning new tools, while expectations for speed — and especially quality — continue to grow. I hear the same concerns from colleagues, candidates and peers across the industry: Am I learning fast enough? Am I already behind? If you've been feeling that pressure lately, I want you to know that it doesn't mean you're failing. More often than not, it simply means you're going through a completely normal stage of adaptation.

Stage 1: We lose our sense of stability

One thing I've learned over the years is that people rarely struggle with change itself. They struggle with losing their sense of stability.

I've seen that happen many times. During relocations, some people had to leave their homes almost overnight and rebuild their lives in a new country. Others were trying to balance the uncertainty with families, children or responsibilities that couldn't simply be packed into a suitcase. The circumstances were different for everyone, but the feeling was often the same: the familiar rules no longer worked, and the new ones hadn't formed yet.

I remember colleagues calling us from airports asking what to do next. Not because they couldn't read a boarding pass or find their gate, but because stress has a remarkable ability to shut down even the simplest decision-making. In moments like that, people don't necessarily need someone to solve every problem. They need someone who can help them see the next step.

Looking back, that's what HR was able to offer during those periods — not certainty, because we didn't have it ourselves, but structure. We helped people focus on what they could control, make a plan for the next few days instead of worrying about the next few months, and remind them that they weren't going through it alone. Sometimes that's exactly what helps people regain their footing.

I think AI is creating a very similar feeling today. Most people aren't afraid of the technology itself. They're trying to find stability while the way they've worked for years is changing again. And that's why my first piece of advice is simple: don't expect yourself to have everything figured out immediately. Focus on the next step, not the entire journey.

Stage 2: We think everyone else is ahead

One of the most common concerns I hear today sounds something like this: "I feel like everyone else already knows how to use AI," or "I'm probably the only one who's still trying to figure it out." I completely understand where that feeling comes from.

We're surrounded by success stories. At SayGames, we have our AI Club, where colleagues share the workflows and automations that have worked for them. It's an initiative I'm genuinely proud of because it helps people learn from each other and keeps the momentum around AI adoption. Outside the company, LinkedIn and industry media tell very similar stories. Every day we see examples of teams becoming more efficient, building better tools and saving hours of work.

What we rarely see is everything that came before those success stories: the failed prompts, the experiments that went nowhere, the evenings spent trying to understand why something still wasn't working. When that part of the journey stays invisible, it's easy to believe everyone else has already adapted while you're somehow falling behind.

From where I sit, talking to people across different teams — and to candidates across the industry — I can honestly say that isn't true. Almost everyone is still figuring it out.

There's another reason why this transition feels so demanding. Learning AI isn't replacing the work we already have; it's happening on top of it. Our deadlines haven't disappeared. Our responsibilities haven't become smaller. We're expected to rethink workflows, experiment with new tools and learn new skills while continuing to deliver the same high-quality results. It's a difficult combination, and I think it's important to acknowledge that instead of pretending adaptation is effortless.

Sometimes that pressure can feel like it's coming from your manager or your company. In reality, it's much bigger than that. The entire industry is going through the same transformation. AI is becoming part of everyday workflows, hiring expectations and the infrastructure that supports how games are made. We're all responding to the same shift, and we're all learning as we go.

My advice at this stage is simple: don't compare your learning process to someone else's highlight reel. You're seeing their results, not the hundreds of small experiments that got them there.

Stage 3: We realize we're not alone — and we start talking

One of the first signs that you're adapting is realizing you don't have to do it alone.

Looking back, that's exactly what helped us through previous challenges. During relocation, people naturally came together. They shared information, helped each other solve problems and simply checked in on one another. Nobody had all the answers, but nobody had to figure everything out alone either. I think that's one of the biggest strengths I've seen at SayGames.

And don't hesitate to speak openly with your manager or HR if something feels difficult. Those conversations don't just help you — they help the company adapt too. If nobody talks about what's hard, it's easy to assume the problem doesn't exist. But once we understand where people are struggling, we can rethink processes, adjust priorities and create better support.

Stage 4: We begin experimenting

In my experience, adaptation really begins when we stop waiting to feel ready. We simply start trying, one small step at a time. You don't have to redesign your entire workflow overnight. Sometimes it's enough to automate one small task or learn one new feature. Every small success builds confidence, and that confidence makes the next step a little easier. It's a bit like eating a cake one piece at a time.

If experimenting at work still feels intimidating, start somewhere safer. That's something I've done myself. Use AI for a personal project, plan a trip, organize information or simply explore what it can do. Removing the pressure to get everything right makes learning much easier. That's how I approached vibe coding: I simply started experimenting, asking questions and figuring things out as I went. I still make mistakes, and I'm lucky to have colleagues who patiently explain why something isn't working instead of making me feel like I should already know the answer.

I've also found that curiosity is much more helpful than fear. When something feels unfamiliar, it's natural to resist it. But instead of focusing on everything that might go wrong, try approaching it with curiosity. Ask questions. Explore. See what happens. In my experience, that's a much better place to start.

Stage 5: We find our new normal

Looking back at the last eight years, I've stopped waiting for the moment when everything finally becomes stable. Every few years something changes — where we work, how we work, the market around us or the tools we use. Today it's AI. A few years from now, it will probably be something else.

That's why I think adaptation has become one of the most important professional skills we can develop. It doesn't mean change is easy, but it does mean we've already learned how to navigate it.

If AI feels difficult today, I don't think it means you're falling behind. I think it means you're going through the same journey we've already experienced more than once. And if the last few years have taught me anything, it's this: people are far more adaptable than they usually give themselves credit for.