"Digital Darwinism" and AI: An Interview with UC Berkeley Lecturer and Innovation Expert Gautier Vasseur

This year, at the invitation of AB Games, one of the most influential experts on AI innovation — Gautier Vasseur, lecturer and executive director of the Fisher Center for Business Analytics at UC Berkeley — visited Games Gathering 2025 in Lviv.

We spoke with Mr. Vasseur about the role of digital Darwinism in game development, the idea crisis, why AAA companies can learn from indie studios, and how Ukrainian developers can build healthy, successful businesses with the help of AI.

What is "digital Darwinism" and how does it apply to game development and production pipelines?

Digital Darwinism, a term coined by Brian Solis, describes the fate of companies that fail to adapt to digital technologies, particularly artificial intelligence. Essentially, those who don’t embrace these advancements risk becoming irrelevant very quickly.

In my classes, I highlight two major expressions of digital Darwinism. First, companies that do not use tools for faster and more accurate design and analysis inevitably fall behind. Those who deeply understand current trends gain a significant competitive edge.

The second concern is just as pressing: many companies waste too much time struggling with their data, trying to gather and manage information. That time would be better spent on research and innovation. One of my clients described this challenge well — he called it “dying from a lack of innovation.”

It’s not that these employees lack intelligence. Rather, they are trapped in daily routines, unable to look beyond them. Technology can help reclaim this time and redirect focus toward innovation — the kind of innovation that could have saved companies like BlackBerry and Nokia from irrelevance, or helped others better adapt to industry shifts such as the rise of electric vehicles.

Has the startup mindset become the new norm for all market players?

Absolutely. The principles of flexibility, continuous innovation, and a realistic mindset are no longer exclusive to startups. Large companies are trying to adopt startup thinking as they face increasing competition from indie brands, often amplified by social media.

Well-known companies must rediscover a mindset they may have long buried and learn to embrace it. This proactive approach is especially important now, with the rise of generative AI and the promises of large language models that are fundamentally transforming production and simplifying daily tasks.

What can AAA studios learn from indie teams, and vice versa?

Based on my extensive business experience, there is mutual learning potential here. AAA game companies can adopt indie studios’ innovation, rapid iteration, and ability to experiment and fail without needing massive investment.

Although AAA studios can afford to develop games over longer periods, they would benefit from more agile approaches. Tapping into the creative energy often found in indie studios can lead to valuable innovation.

Indie studios, on the other hand, can learn from larger companies — especially in terms of structure and processes. While some may see corporate processes as cumbersome, they are essential for balancing flexibility and effective management. Startups should consider involving experienced professionals with operational expertise while retaining their entrepreneurial spirit. Similarly, established companies should actively bring in young talent to energize internal practices.

Ultimately, fostering team diversity is vital — not as a checkbox for political correctness, but as a critical strategy for building dynamic and effective organizations. The ideal team combines experience and diverse perspectives that enable effective idea exchange.

Your No-Code AI course focuses on Python. What are your thoughts on tool accessibility for AI enthusiasts?

The accessibility of tools has greatly democratized the landscape. Python, designed for readability and user-friendliness, is revolutionizing how “non-programmers” interact with technology.

However, learning Python can still be challenging. Many business professionals may understand the concepts initially, but retaining them is difficult. Fortunately, the rise of generative AI is lowering traditional coding barriers. With AI, people can now express their ideas and receive code without needing extensive programming skills. This opens the door for non-coders to participate in development.

In the gaming industry, metrics analysis is crucial — and Python makes it easier to access complex insights. Tasks that once required direct coding support can now be automated using Python prompted by GenAI, allowing creators to focus on what they do best: asking the right questions and extracting meaningful insights from data.

Can AI help overcome the "idea crisis" and support innovation?

This challenge is widespread. Companies must innovate quickly, identifying industry disruptions — much like Uber and Airbnb reshaped their markets.

To use AI effectively, companies need to mine the vast amounts of data their games generate. Often, engineers handle this data without a clear understanding of market dynamics or user behavior. Empowering marketers and business developers with AI and natural language coding tools allows them to access valuable insights.

Additionally, generative AI offers new opportunities to create content, helping companies balance efficiency and innovation. If firms use the saved time and AI-generated ideas to develop a culture of creativity — walking, exploring, and discovering — they may unlock their next breakthrough.

AI equips us with tools to enhance creative processes, but we must not lose sight of the human experience. If we become complacent and simply substitute AI for genuine engagement, we risk stagnation.

How can creative professionals — artists, musicians, writers — benefit from AI rather than feel threatened by it?

This is a common concern among educators and creatives. As generative AI increasingly performs tasks traditionally done by humans, there’s a real fear of obsolescence. The key is to evolve actively.

Creative professionals should view AI as a tool to enhance their work, not replace it. Those who resist adaptation may be left behind, as AI’s capabilities are growing rapidly. Since AI can handle repetitive tasks, it gives artists the luxury of time to focus on the meaningful aspects of their work.

True creativity requires a human touch. While AI can assist with structure and content, it cannot replicate the unique perspective and emotional depth of a human creator. People must continually sharpen their skills and distinguish themselves by nurturing the very drive that leads to progress.

AI can greatly reduce the burden of routine work, allowing for more focus on meaningful production and creativity.

How do we embrace digital transformation without fearing that AI undermines creativity?

Often, we blame AI for shortcomings that result from human decisions. It’s inappropriate to scapegoat AI — it’s a tool governed by our intentions. For example, in France, when an AI-generated image caused controversy, the blame was unfairly placed on the technology rather than on those who created and published it.

When interacting with AI, ethical considerations must come first. If people remain transparent throughout the process and take responsibility for their choices, they can use AI confidently.

AI can enhance creativity, but it cannot replace our unique ideas, historical awareness, or ethical reasoning. Instead of demonizing AI for its potential flaws, we should cultivate a culture of responsibility and respect. By being transparent about how we use AI — for example, to create background art while prioritizing storytelling — companies can build trust and authenticity.

What would you advise developers who want to build a healthy and successful business environment?

First, prioritize transparency in your interactions with clients. While not all processes require full disclosure, openness that improves user experience is essential.

Second, remember that while AI is powerful, it has limitations. It learns from historical data and cannot foresee the future. Human intuition and creativity will always be essential drivers of innovation.

Finally, invest in efficiency by automating routine tasks. Though it may take effort upfront, the long-term productivity gains are worth it. Embrace your humanity — celebrate your creative ability and don’t get stuck in tasks that AI can handle.

The key is a mindset of constant learning and improvement. Regularly reflect on what you’ve learned and how you can adapt. In today’s fast-changing environment, complacency only hinders progress.