'The Singularity is Already Here': How to Prepare for the AGI Era

Sam Altman, CEO of OpenAI, recently declared that the singularity is already here — a statement that repositions the discussion about Artificial General Intelligence (AGI) not as a distant future scenario, but as something that managers and organizations need to prepare for now.

Strategist Eran Gefen, author of the new book 'Strategy with a Scratch: How to Win in the AGI Era', suggests reading this change less as another technological upgrade and more as a business and social revolution. For companies and managers, the period between 2026 and 2030 is now, Gefen explains. The timelines of industry leaders are not yet uniform: Elon Musk bets on 2026, Altman estimates it will happen within two years, Demis Hassabis, CEO of Google DeepMind, points to 2030, while Yann LeCun, Turing Award winner, claims the road is still very long. In Gefen's view, the debate over the exact year is less important than the need to start moving.

Three Stages of Intelligence

To understand the landscape, Gefen distinguishes between three stages:

Narrow AI — systems that perform specific tasks well (what we know today).
AGI (Artificial General Intelligence) — systems supposed to be better than the most expert human in any field, from law to science.
ASI (Superintelligence) — the stage where the machine will be smarter than the sum of all humanity combined.

According to Gefen, AGI is not an accidental product of technological development, but the goal for which companies like OpenAI were founded. Unlike narrow AI, the human brain knows how to move between social, mathematical, and creative intelligence and connect them. This is exactly the connection that AGI is trying to replicate. Breakthroughs in multimodality are a sign that the field is no longer just a game of predicting the next word.

An Economic Earthquake

The crucial importance of AGI depends on the fact that humanity is currently making a double bet on this future. Trillions of dollars are being invested in physical infrastructure — data centers, chips, memory, and energy. If this value does not materialize, the global economy will suffer a severe blow. Therefore, managers must prepare in advance for extreme scenarios and develop assets that will protect them in both possible futures.

To imagine the magnitude of the change, Gefen returns to the electricity revolution. In 1893, at the World's Fair in Chicago, no one could have predicted the chain of social and economic consequences that would follow. Just as electricity took away a large part of hard physical labor, artificial intelligence is now taking parts of brain work. Therefore, it will not only change existing professions but also the concept of work and the definition of ownership.

The 'Reason Behind the Reason'

Gefen introduces the principle of 'the reason behind the reason'. During the electricity revolution, gas companies struggled because they defined themselves as 'gas companies'. Those who realized they were in the 'lighting business' survived and founded companies like Con Edison, which provides electricity to New York to this day. The lesson is that a company should not define itself through its product, but through the value it gives the customer. A lawyer who understands that they are selling security and peace of mind, rather than just a contract, will be able to adapt to the new era.

To bypass the fear of change, Gefen suggests the 'Tomer test': ask yourself what a respected colleague would do if they replaced you tomorrow morning. This exercise clarifies the depth of the required changes in traditional industries like insurance or academia.

Human Skills in the AGI Era

Gefen does not suggest rushing to study code. In a world where knowledge is eroded quickly, he emphasizes human skills:

A value backbone and personal taste.
Psychological resilience and critical thinking.
Empathy and face-to-face communication.
Self-learning and the ability to find knowledge in real-time.

Gefen's final message is to embrace your 'scratch'. In a world where AGI turns standard work into a cheap, replicated commodity, the competitive advantage lies in uniqueness that cannot be copied. The goal is to find this uniqueness and turn it into an asset that cannot be replaced.