“There’s nothing sci-fi about AI. I think it’s one of the biggest myths in the world today,” Mo Gawdat said.
Gawdat has worked for decades at IBM, Microsoft, and Google, and is now a prominent voice and author on AI safety.
Shortly after leaving his position as Google’s chief business officer in 2020, Gaudat made several predictions about artificial intelligence based on patterns he was seeing within the technology.
In a recent video interview with Business Insider, he said three of those predictions have come true and explained how they are starting to shape the social disruption that may come next.
Prediction 1: “The emergence of AI is inevitable”
“The emergence of AI is inevitable,” he said, adding, “There is no way to stop it.”
That momentum is already visible in how AI systems shape everyday behavior. “If someone is watching that video that we’re recording right now, it’s because the AI is recommending that video,” he says.
Once technology proved useful, competition ensured its expansion. Gaudat described an “arms race” in AI as countries and businesses move forward to keep up.
He said this dynamic could lead to a world in which more decisions are handed over to machines as systems grow faster than humans can manage.
Over time, he suggested, the changes could redefine how power, competition and cooperation work at the global level.
“This is the first time that an episode in history in which humans were the smartest beings on Earth ends,” he said.
Prediction 2: AI will be smarter than humans in every way
AI models are already outperforming humans in many specific tasks, from pattern recognition to strategic gameplay.
Gawdat referenced systems like AlphaGo Zero. AlphaGo Zero was able to play the game of Go without human input in 2017, outperforming its best-performing predecessor within weeks.
Gaudat argued that modern AI can “reason like humans,” using vast datasets and neural networks that reflect aspects of the human brain.
The result, he suggested, could accelerate progress in ways that are difficult for humans to track or control. Systems that can learn instantly, share knowledge and improve their own code could compress years of human work into microseconds, he said.
Over time, that change can change how expertise is defined.
As machines take over analytical and technical tasks, the remaining advantages for humans are likely to center on judgment, ethics, and interpersonal relationships. Goudat said it’s unlikely that AI will replicate it in the same way.
Prediction 3: Something can go wrong.
In fact, things are already looking up, with massive technology layoffs and power outages, including the loss of 120,000 Amazon orders. But he says this is just the beginning.
Mr. Goudat described the uncertain times ahead. He predicts that increasing automation will cause disruption to the labor market, resulting in “unemployment rates of up to 50% in certain sectors.”
He also warned about the erosion of shared reality. “We will experience an erasure of reality and the ability to recognize what is true and what is false,” he said.
The collapse could have ripple effects beyond the technology sector. When people struggle to agree on what is true, it can become more difficult to maintain trust in organizations, the media, and even personal relationships.
At the same time, Goudat suggested the disruption could force a broader reset.
As economic systems and information networks come under pressure, societies may need to rethink how work, value, and truth are defined in a world where machines can generate both production and influence at scale.
He linked the risk to human behavior rather than the technology itself. He said short-term risks come from how people use powerful systems for misinformation, surveillance and conflict.
He also warned of the erosion of a shared reality, making it difficult to tell what is real and what is not, AI-generated content.
Across all three predictions, Gawdat returns to the same theme. The challenge is not the intelligence itself, but the context in which the intelligence is deployed.
He said the end result will depend less on the technology and more on the decisions humans make as the technology evolves.
