Artificial General Intelligence: Hype or Future Reality

I recently heard Yann LeCun state that he doesn’t believe current AI technology can get us to Artificial General Intelligence (also known as AGI). Gartner estimated that the hype surrounding generative AI has just passed its peak and is on the downswing.

On the other hand, Google DeepMind CEO Demis Hassabis said he thinks artificial general intelligence, or AGI, will emerge in the next five or 10 years.

While generative AI is already transforming how we manage and tackle basic tasks, the promise of AGI is far greater than that.

It assumes that AI will continue to develop more complex cognitive abilities, such as reasoning, planning, and enhanced decision-making, in the coming years.

The potential of AGI is what science fiction movies have long envisioned. Imagine a world where virtual and physical machines possess human-level learning, cognitive, and reasoning capabilities.

The questions remain: Can the promise of AGI truly materialize? What does the timeline look like?

First, what is AGI?

AGI refers to the hypothetical intelligence of a machine that can understand or learn any intellectual task that a human can. Unlike current AI systems, which specialize in more narrow tasks, AGI aims to mimic humans’ cognitive abilities.

While current-day AI can handle task automation, process optimization, and content generation, AGI will handle more advanced reasoning, problem-solving, and proactive decision-making at or above a human level.

If and when realized, AGI will revolutionize industries, governments, economies, science, education, and daily life with these abilities.

How could AGI transform industries and life?

• Business: AGI-powered consultants could strategize, negotiate contracts, and drive corporate decision-making with real-time economic and market insights.
• Science: AGI could autonomously generate hypotheses, conduct experiments, and make groundbreaking scientific discoveries.
• Manufacturing: Self-optimizing AGI-driven factories could eliminate waste and inefficiencies by reconfiguring production lines based on demand and resource availability.
• Personal: AGI virtual assistants could anticipate your needs, act on your behalf, provide emotional support, and offer expert-level advice in any domain.
• Healthcare: AGI could accelerate drug discovery, reducing costs and improving patient outcomes.

What will it take to make AGI a reality?

We still need to develop key abilities for AGI to become a reality. Applying knowledge across fields, learning independently and from less data like humans do, and understanding the physical world are just a few examples of what the technology needs to accomplish.

AGI will require more technology, processing power, and energy than current AI uses. It will rely on these developments to become more human — no simple feat.

• Continuous learning: Today’s AI models are one-and-done, but the world around us continually evolves, so AI will also need to continuously learn.
• Emotional intelligence: AI doesn’t understand emotional context, which limits its ability to converse with nuance, explore more creative outputs, and use intuition for problem-solving. It’s not yet clear that digital intelligence can ever mirror biological intelligence, at least when it comes to EQ vs IQ.
• Sensory awareness: While robotics might bring AGI physically into the world, it will require a deep understanding of its surroundings. As we’ve already seen with autonomous vehicles, it takes tremendous amounts of data and training for AI to function in the physical world. It will need to develop a model of the world much like humans do, and have a deep understanding of space, gravity, smells, sounds, shifting landscapes, etc.
• Energy-efficient infrastructure: The processing power and energy needed to supply this next-level intelligence are not available today, so new technologies and energy infrastructures will need to be developed.

Who is betting on AGI’s future?

Major tech giants and startups alike are driving AGI innovation, including:

• Safe Superintelligence Inc.: Developing safe artificial intelligence systems
• Thinking Machines: An artificial intelligence research and product company focused on building multimodal systems that work with people collaboratively
• OpenAI — Known for GPT models and deep reinforcement learning research, OpenAI aims to develop AGI that “benefits all of humanity.”
• Google DeepMind — DeepMind has made AGI-relevant breakthroughs, like Gemini 2.5 models capable of “reasoning through their thoughts before responding.”
• Anthropic — Founded by ex-OpenAI researchers, Anthropic focuses on AI safety and alignment, developing models like Claude 3.7 Sonnet, their “most intelligent” AI model yet.
• Microsoft Copilot — Partnered with OpenAI, Microsoft is deeply invested in AI research and infrastructure via Azure.
• Meta AI — Meta is developing open-weight models like Llama and conducting fundamental AGI research.
• xAI — The company’s product Grok is focused on blending reasoning with knowledge.
• DeepSeek — Owned and funded by High-Flyer, this company is disrupting the industry with its low-cost, open-source large language models.

What discussions should we be having about AGI?

Regulation and ethical concerns

The rapid advancement of AGI may outpace the development of robust safety measures, making it challenging to ensure its safe and responsible deployment. Key players are taking steps to address these:

• Government & policy: Countries like the U.S., China, and the EU are investing billions in AI governance to prepare for AGI’s societal shifts.
• AI safety regulations are in the early stages, with the EU AI Act and U.S. executive orders aiming to balance innovation with safeguards. The EU AI Act assigns applications of AI to three risk categories. First, applications and systems that create an unacceptable risk, such as government-run social scoring of the type used in China, are banned. Second, high-risk applications, such as a CV-scanning tool that ranks job applicants, are subject to specific legal requirements. Lastly, applications not explicitly banned or listed as high-risk are largely left unregulated. Tools like these are works in progress and will continue to evolve as AI does.
• Anthropic submitted AI policy recommendations to the White House. The company’s suggestions included preserving the AI Safety Institute, directing NIST to develop national security evaluations for powerful AI models, and building a team within the government to analyze potential security vulnerabilities in AI.

Labor and income

One of the most surprising outcomes of AGI may be its disruption of high-skill jobs. While AI has traditionally been seen as a disruptor of routine, repetitive jobs, an unexpected shift is emerging.

High-skill professions — such as legal, medical, and financial roles — are increasingly at risk of AI-driven automation. AI’s ability to analyze legal documents, assist in medical diagnoses, and optimize financial decisions may lead to faster-than-expected disruptions in these industries.

This rapid transformation is sparking urgent conversations about regulatory frameworks, workforce adaptation, and the potential need for Universal Basic Income (UBI)–a government-provided financial program that guarantees all citizens a fixed, regular payment–as a safety net for displaced professionals.

An alternative approach is cooperative AGI ownership, where AGI-driven profits are collectively shared rather than solely given to the capital owners. Progressive AGI capital taxation could distribute AGI-driven wealth accumulation to mitigate economic inequality.

The rise of AGI marks a shift in the fundamental balance between labor and capital that has shaped our societies for centuries.

Planning for AGI

The rapid development of AGI can be thrilling and concerning. It is critical to understand the risks and opportunities from a balanced viewpoint.

Overall, I see most businesses waiting to see AGI’s full potential before considering it in their current investment decisions.

When we realize its full potential, AGI can enhance human labor, improve productivity, and preserve a degree of shared economic power. We have previously faced transformations like these when offices moved from the Industrial Age to the Information Age.

Printers, photocopiers, and digital printing presses replaced mimeographs. Machines performed bookkeeping, and Dictaphones were transformed into computer applications.

But new industries and professions were born–computer manufacturers, UX designers, IT managers, and more.

Preparing for an AGI future will force governments, businesses, and individuals to rethink organizations, determine ethical considerations, and develop social frameworks.

We need to ask ourselves now what we want from these intelligent systems and how they can align with our future needs and our expectations of trust and accountability.

This could be our most significant technological advancement yet. How are you preparing for it?