Artificial general intelligence is an artificial general illusion

Across the technology landscape, a new narrative is taking shape: the rise of artificial general intelligence (AGI) as the next revolutionary leap in artificial intelligence. If you follow the dominant cloud and technology vendors, you’ve probably noticed a surge in high-profile announcements, conference keynotes, and marketing campaigns hinting that AGI is no longer the realm of science fiction but is now a looming reality. In press releases and glossy brochures, AGI is framed as an inevitable future that will unlock limitless productivity, reimagine entire industries, and fundamentally transform our relationship with technology.

As enticing as these visions are, the marketing for AGI tends to blur the lines between aspiration and actual technological progress. The messaging often suggests that the underlying infrastructure is ready, and by investing today, enterprises can future-proof themselves for a coming AI revolution. However, beneath this polished surface, there is considerable ambiguity about what AGI truly means, how close we are, and what “being ready” actually entails. As the conversation intensifies, it’s crucial for business and technology leaders to distinguish between ambitious storytelling and substantive advancements, especially as AGI becomes a central pillar in the sales strategy of cloud computing.

Reality check: AGI is still a mirage

The real issue here—the elephant in the server room, so to speak—is that AGI doesn’t exist. Not in the sense that’s advertised. Every breakthrough that cloud platforms tout is still in the realm of narrow AI: systems exquisitely designed for specific tasks but with no true understanding. They don’t learn on their own in the open world, adapt to novel situations, or exhibit genuine reasoning or creativity the way humans do.

Even the most advanced language models, such as those behind today’s top chatbots, are fundamentally statistical engines, regurgitating patterns in data rather than actually understanding or reasoning. AGI, as broadly conceived in both science fiction and some academic circles, remains an aspiration rather than an imminent achievement.

Current marketing glosses over these hard realities. The message to enterprises is “invest now, or be left behind!” But invest in what, exactly? AGI’s arrival is uncertain, and there’s no guarantee it’s even possible within the frameworks we understand today.

Perhaps emboldened by these ambitious messages from their cloud vendors, a growing number of enterprises are now developing internal strategies for leveraging AGI. Some even publish vision documents outlining how their organizations will transform on the day AGI is real. Resources are dedicated to AGI-focused innovation teams, hackathons, and even pre-announced initiatives aimed at capturing the first-mover advantage in a post-AGI world.

This is, in many ways, a profound act of faith. It assumes that AGI is just around the corner, that existing investments in the cloud will seamlessly transition to AGI capabilities, and that vendor marketing is grounded in more than wishful thinking. What’s more, these efforts often border on the comical: Strategy teams debate the finer points of overseeing AGI governance, IT budgets allocate funds for future AGI readiness, and C-suite executives make bold proclamations about transforming their industries as soon as AGI arrives.

Skepticism is warranted

Here’s where I need to press pause and inject a healthy dose of skepticism. While it’s fashionable in tech to always be “future-ready,” there’s no escaping the fact that AGI—at least defined as an AI that can fully reason, learn, and act across diverse tasks with the adaptability of a competent human adult—may never arrive. Or, if it does, it could be decades away.

The gulf between what’s possible with today’s narrow AI and what’s imagined for AGI is not a matter of more compute or better algorithms alone. It’s a quantum leap that may well require fundamental advances in both hardware and, more importantly, in our basic understanding of intelligence itself.

It’s here that cloud providers’ AGI-related marketing starts to look less like a harbinger of progress and more like a bait and switch. It’s a classic example of vaporware: selling possibilities that don’t exist yet (and might never come to fruition as promised).

Enterprises: Don’t chase vaporware.

So, what should enterprises do in the face of the AGI marketing gold rush?

Focus on real, proven value: Leverage the powerful, genuine advances in narrow AI available today. Use data science, machine learning, and automation to solve real-world business problems. These are the true fruits of today’s AI revolution.

Stay skeptical: Always demand clear distinctions between what is being marketed and what exists. Ask cloud vendors tough questions, especially about timelines, capabilities, and dependencies.

Don’t overcommit: Building strategy, investing resources, and hiring personnel around AGI that is neither defined nor real is a risky bet. Vaporware, no matter how attractively packaged, is never a good use of resources.

Monitor developments and don’t bet the farm: Stay informed about genuine advances in AI, and structure technology investments in a way that allows them to pivot toward new capabilities if and when they emerge.

Ultimately, hope and vision are crucial, but so is grounding an enterprise strategy in provable reality. The AGI marketing blitz is, for now, more about fueling vendor revenue than delivering transformative general intelligence. Enterprises would do well to remember that you can’t build tomorrow on an idea that doesn’t exist today.