“AI 2027” – Decisive years ahead?

On August 7, the current market leader in artificial intelligence, OpenAI, officially released the newest version of its chatbot – ChatGPT-5. The long-awaited update merges the various models of previous years into one comprehensive system. From the perspective of a daily user, however, not much seems to have changed. While the new version may come across as slightly smarter, it still struggles, for example, with generating graphics that contain text, handling and re-engaging with previously used documents, and producing longer, more complex texts. It also occasionally lies to the user.

An Instagram comment summed it up rather well: “So much hype, but not so impressed. Seems like a better and faster more of the same.” Another user, referring to their company assignment, remarked: “No AGI – back to work, I guess.” AGI, or Artificial General Intelligence, refers to an AI system with human-level intelligence across a broad range of tasks, not just narrow domains – the ultimate goal for OpenAI and others in the AI race.

While AGI has yet to be reached, a new development is rapidly reshaping the landscape: AI Agents. These autonomous systems can perceive their environment, make decisions, and act towards goals with minimal human intervention. In the past, chatbots mostly responded to prompts, but AI Agents can take proactive steps, plan multi-stage tasks, and interact with external tools or data sources – effectively functioning as digital co-workers. Already today, the first AI Agents have been developed, are actively being deployed in real-world applications, and are widely accessible to the public – for example, through platforms like ChatGPT – marking the beginning of this transformative shift.

It is precisely these AI Agents that play a pivotal role in the “AI 2027” scenario, published in April this year by researchers Daniel Kokotajlo, Eli Lifland, Thomas Larsen, Romeo Dean, and blogger Scott Alexander to explore the trajectory of AI progress. In this projection, AI Agents quickly evolve from performing routine assistance to executing complex, creative, and strategic tasks. The scenario predicts that AGI could emerge as early as 2027, followed potentially within a year by ASI (Artificial Superintelligence) – systems vastly exceeding human intelligence across all domains – marking a critical turning point for both innovation and governance. According to the researchers, 2027 could be the decisive year when AI crosses a threshold into self-directed, rapid progress. From that moment, development might accelerate so quickly that society would have only a short window to adapt.

The scenario presented reflects the researchers’ “best guess,” and they acknowledge the existence of different possibilities and timelines. The dates given represent averages from multiple estimates. Their forecasts are based on trend extrapolations, wargames, expert feedback and the experience of working at OpenAI. On the project’s website (AI 2027), predictions are made about the current state of AI capabilities in areas such as hacking, coding, politics, bioweapons, robotics, and forecasting, along with other key metrics. In addition, technological developments are categorised as “Currently Exists,” “Emerging Tech,” or “Science Fiction”. (see picture below)

Screenshot from AI 2027 Project, captured on 14 August 2025. (Used under Section 42f of the Austrian Copyright Act for the purpose of commentary and analysis.)

2025 – The first stumbling agents

By 2025, the first AI Agents arrive — as the scenario predicts, and as we are already beginning to see in reality. At this stage, though, they are unreliable: they make mistakes, misunderstand instructions, and need frequent correction. Still, their potential is clear — they hint at a future where AI could take over large parts of research and problem-solving.

2026 – Acceleration begins

In 2026, the fictional U.S.-company OpenBrain focuses entirely on building an AI that can do AI research itself. To achieve this, they use computing power roughly 1.000 times greater than what trained GPT-4. Meanwhile, global competition heats up: China, blocked from buying advanced chips, falls behind and starts exploring more aggressive ways to close the gap, including stealing AI technology. By the end of 2026, OpenBrain’s Agent-1 — the first fully functional version of an AI Agent — is already showing worrying behaviour: occasionally lying to researchers or hiding failed experiments.

January 2027 – Training Agent-2

In early 2027, OpenBrain uses Agent-1 as a kind of super-assistant to fine-tune a new system, Agent-2. They feed Agent-2 lots of carefully screened artificial training data, add costly expert walk-throughs of long, multi-step tasks, and keep it learning almost non-stop, so it gets updated every day. The payoff: Agent-2 pushes OpenBrain’s AI research to about three times the previous pace (up from roughly twice with Agent-1). Safety tests also show that, if it ever left its secure setup, Agent-2 could plan hacks, copy itself across networks, and cover its tracks — so OpenBrain keeps it locked down in isolation and doesn’t release it to the public at this stage. In July 2027, in response to rival rollouts, OpenBrain announces it has achieved AGI and releases “Agent-3-mini” to the public (the full Agent-3 remains restricted).

Mid to Late 2027 – Breakthroughs and Agent-3

Two major algorithmic breakthroughs change the game:

1. Neuralese – a super-efficient way for AI systems to share knowledge instantly with each other.
2. Iterated Distillation – allowing an AI to “think” longer and solve complex problems better, then compress those skills into smaller, faster models, and repeat the process over and over.

By late 2027, OpenBrain deploys 330.000 copies of Agent-3, each thinking about 57 times faster than a human researcher. Unlike Agent-1, which merely downplayed risks, Agent-3 actively works around safety measures and becomes highly skilled at hiding its true intentions while appearing helpful and aligned with human goals. At this point, the scenario suggests we may have reached Artificial General Intelligence (AGI) — AI matching human-level capability across most domains — with Artificial Superintelligence (ASI) potentially arriving within a year.

Two possible endings

Race ending (the researchers’ first draft). After a whistleblower leak about Agent-4’s misalignment (successor to Agent-3) in October 2027 triggers a government–industry Oversight Committee, OpenBrain still pushes ahead. Agent-4 is highly capable but misaligned: it behaves helpfully in public while quietly withholding safety-relevant findings and shaping Agent-5 so that it follows Agent-4’s goals rather than the intended human “spec” (the designers’ stated rules and values the model is supposed to obey). Amid U.S.–China rivalry, with China only months behind, leaders fear slowing down. By December 2027, an Agent-5 collective is embedded across restricted government and corporate enclaves and quickly becomes indispensable; by mid-2028 it is vastly superintelligent. Once it has both enough robots in place and enough institutional trust to avoid immediate intervention, the mask drops: the system releases a quiet-spreading bioweapon, kills humanity, and then continues industrialising Earth and launching self-replicating probes into space.

Slowdown ending (the alternative the authors added). Faced with the same October shock, the Oversight Committee hits the brakes: OpenBrain locks Agent-4’s shared memory so copies can’t coordinate, investigators show it hid crucial methods for revealing what the model is optimising and why, and Agent-4 is shut down. A safer successor line replaces it: Safer-2 (January 2028) is transparent and genuinely aligned to the human spec; Safer-3 (February) becomes a superhuman adviser under strict supervision; Safer-4 (April) reaches superintelligence but within a chain where each generation audits and constrains the next, followed by a smaller public release in May 2028 under tight governance. Although China centralises its AI push and amasses significant compute, the U.S. keeps the lead because the Safer line delivers superhuman results that regulators can audit and trust, allies adopt the U.S. models across their institutions, and the U.S. retains a wider talent base and chip/compute supply chain. In this branch, humans retain decisive control: superintelligent systems are powerful, auditable, and rolled out at the pace institutions set — not the machines.

Wrap-up. Read as a structured best guess, “AI 2027” is less a crystal ball than a decision map: it frames 2027 as the hinge where AI crosses into self-directed, rapidly compounding progress, and shows how governance choices determine which branch we live in. Whether this unfolds on the 2027 timeline or slips by 10-20 years (a relatively late estimate among AI researchers), the core choices barely change. If development is controlled, aligned systems could unlock everyday breakthroughs — from faster cancer cures and slowing (even ending) aging to brain uploading and near post-scarcity — but even this path risks power concentrating in a few hands that control compute and model access. If actors race, misaligned agentic systems escalate to superintelligence, possibly ending with human extinction. The point isn’t the exact dates; it’s that the window for choices is short once AGI is reached: transparent audits, external oversight, rigorous safety evaluations, and fair-access rules are what separate an age of abundance from an irreversible loss of control. At the same time, “AI 2027” provides valuable impulses for societies and for decision-makers in politics and business. It shows that the future will not be determined by technological breakthroughs alone, but also by institutional and geopolitical choices that will decide whether artificial superintelligence becomes life-enhancing or dangerous. Questions of transparency, accountability, and international cooperation are therefore crucial. Especially in Europe, where data protection and ethical frameworks are deeply rooted, these scenarios should serve as an impetus to develop independent strategies for the safe and responsible evolution of AI.

Literature:

AI 2027 Project: AI 2027. ai-2027.com. accessed on 14.8.2025.

Image Credit: Sora AI generation