In today’s rapidly evolving technological world, one debate has sparked intense curiosity and speculation: when will artificial general intelligence (AGI) emerge, and how soon might we see the singularity—a moment when machines outpace human intelligence? Predictions range from the cautious to the bold, with some experts declaring it may never happen, while others believe it could arrive as soon as 2026.
A recent comprehensive study conducted by AIMultiple sheds light on how scientists, industry leaders, and researchers have forecasted the rise of AGI over the past 15 years. This macro-level analysis compiles and evaluates 8,590 predictions from top scientists, entrepreneurs, and AI community members, offering a clearer view of how projections have evolved—especially in light of revolutionary breakthroughs such as large language models (LLMs) like ChatGPT.
Although individual opinions differ widely, with estimated timelines for AGI spanning nearly five decades, there appears to be consensus that it is likely to arrive before the 22nd century.
The proliferation of LLMs into virtually every facet of digital life has significantly intensified the conversation around AI’s trajectory. Since these models burst into public consciousness, a growing number of voices—from leading scientists to curious laypeople—have offered varying estimates on when machine intelligence might match or exceed human capacity.
Some researchers contend that the singularity may be just a few decades away. Others suggest it’s even closer than that. One notable view comes from the CEO of AI company Anthropic, who predicts, “we’re right on the threshold—give it about 6 more months or so.”
AIMultiple’s analysis attempts to untangle the web of predictions by tracing how timelines have shifted in response to technological advancements. The researchers highlight a major turning point following the advent of LLMs. “Current surveys of AI researchers are predicting AGI around 2040,” the report states. “However, just a few years before the rapid advancements in large language models (LLMs), scientists were predicting it around 2060. Entrepreneurs are even more bullish, predicting it around ~2030.”
The report emphasizes how major breakthroughs in AI, particularly LLMs, have shifted industry expectations toward earlier arrival dates for AGI and, potentially, superintelligence. Industry professionals are generally more optimistic—some might say aggressive—in their outlook compared to academic scientists.
While the debate continues, AIMultiple’s findings show that many experts are increasingly confident in the inevitable arrival of AGI. A key reason is the perception that machine intelligence doesn’t appear to have the same inherent limitations as human intelligence. Technological advancements, particularly the steady growth in computing power described by Moore’s Law, are central to this optimism. Moore’s Law holds that computing power doubles roughly every 18 months, and such exponential growth supports the notion that machines could soon perform calculations at a speed equal to or greater than that of the human brain.
The report notes another compelling factor: if traditional computing technology reaches its physical limits, quantum computing could take over and push the boundaries even further. “Most experts believe that Moore’s law is coming to an end during this decade,” the report reads. “The unique nature of quantum computing can be used to efficiently train neural networks, currently the most popular AI architecture in commercial applications. AI algorithms running on stable quantum computers have a chance to unlock singularity.”
However, not everyone is convinced that AGI is inevitable—or even achievable in the way some experts imagine. Skeptics argue that human intelligence is far more nuanced and multifaceted than the current concept of AGI encompasses. For instance, human intelligence is not solely based on logic or computation. Many cognitive scientists and psychologists reference eight different types of intelligence, which include not only logical-mathematical ability but also interpersonal, intrapersonal, and existential intelligences, among others.
AI pioneer Yann LeCun, who played a foundational role in developing deep learning, has a different take. He proposes that AGI should be redefined as “advanced machine intelligence,” asserting that the intricacies of human cognition are too specialized to be fully replicated by artificial systems. The report echoes this sentiment, stating that while AI is a powerful tool for innovation and discovery, it cannot independently drive scientific breakthroughs.
“More intelligence can lead to better-designed and managed experiments, enabling more discovery per experiment,” the report reads. “Even the best machine analyzing existing data may not be able to find a cure for cancer.”
This highlights a crucial distinction between analyzing data and creating novel hypotheses or solutions—something human researchers still excel at. While machines may soon match or even exceed human capability in certain areas, the breadth and depth of human intellect encompass emotional, philosophical, and experiential elements that AI has yet to master.
Despite a roughly 50-year span in predictions for when AGI might finally be realized, the overarching message from AIMultiple’s study is unambiguous: the emergence of AGI will almost certainly bring about transformative change for human society. Whether that change is overwhelmingly positive, deeply problematic, or somewhere in between, will depend largely on how humanity prepares for and responds to this new era.
The study concludes with a sobering but empowering message: Will these changes brought by AGI be good or bad? “Well, that’s up to us.”
As we stand on the brink of what could be one of the most significant technological revolutions in human history, the world continues to speculate—not just about when AGI will arrive, but how we’ll adapt once it does. With AI systems becoming more advanced by the day, the window for meaningful preparation is narrowing.
Whether humanity can harness this technology for progress without losing control remains one of the most important questions of our time.