General Artificial Intelligence: Concrete Examples and Strategic Stakes
Artificial General Intelligence (AGI) refers to a system capable of performing any human cognitive task, without being limited to a specific domain. Unlike today’s AI, which is specialized in a single function, AGI would reason, learn, and adapt autonomously to entirely new contexts. It doesn’t exist yet. But it’s already shaping the strategic decisions of major organizations.
Narrow AI vs. Artificial General Intelligence: The Core Difference
When a Moroccan company integrates AI into its procurement processes, as recently reported by LesEco.ma, it’s deploying narrow AI. A tool trained to analyze tenders, compare suppliers, or detect invoice anomalies. It does that very well, and only that.
AGI is something else entirely. It’s a system that would read that same tender, understand the geopolitical context of the supplier, anticipate legal risks, draft the counter-proposal, and explain its reasoning to your team. Without having been taught each of those things separately.
The difference isn’t one of degree. It’s one of nature.
As I explained in my article on the 4 types of artificial intelligence, even the most sophisticated current systems remain narrow AI. GPT-4, Gemini, Claude: remarkable tools, but specialized in language processing. They operate through statistical prediction, not understanding.
Concrete Examples to Understand What AGI Would Look Like
No operational AGI exists today. But several projects are moving in that direction, and theoretical use cases help illustrate what it would change.
OpenAI’s Q* Project
In late 2023, reports emerged about an internal OpenAI project called Q*. According to these unconfirmed reports, the system showed reasoning capabilities on novel mathematical problems. This isn’t AGI. But it’s a signal: generalization capacity is progressing.
DeepMind and AlphaCode 2
DeepMind’s AlphaCode 2 solves competitive programming problems with notable flexibility when facing situations it hasn’t encountered before. Still narrow AI, but with an adaptability that begins to resemble something broader.
The Agricultural Use Case in Africa
At the Connected Africa Summit 2026, Josué Yassarandji and his Agri AI project won the best AgriTech innovation award. This type of system combines satellite image analysis, weather data, and agronomic recommendations. Still specialized. But the stated ambition of several African players is to move toward systems capable of reasoning across multiple domains simultaneously: soil, market, logistics, financing.
That’s where AGI becomes a strategic question for the continent, not just an academic curiosity.
What AGI Would Change for an Executive
Let’s ask the question directly: if AGI existed tomorrow, what would it change in your organization?
First, the nature of delegable decisions. Today, you delegate repetitive tasks to AI. With AGI, you could delegate complex, multi-variable decisions in ambiguous contexts.
Second, your team structure. Profiles recruited for their cross-functional analytical capacity would be the first to redefine their value in the face of more autonomous systems. This isn’t a critique of current recruitment: it’s an observation about the evolution of roles.
Third, AI governance. If a system can reason autonomously on topics it wasn’t explicitly taught, current guardrails become insufficient. The question of accountability shifts fundamentally.
I’ve built a 6-dimension diagnostic framework to assess an organization’s AI maturity, including its capacity to absorb increasingly autonomous systems. Download the Board Pack AI 2026.
AGI and the Moroccan and African Context
The AI:Casablanca conference, as reported by SNRTnews and Challenge.ma, raised the question of the future of work in the AI era. That’s the right question, but it’s still framed around narrow AI.
The real strategic question for Morocco and Africa is: how do you position yourself in a world where AGI becomes possible?
Two concrete stakes. First, data sovereignty. AGI will require massive volumes of contextualized data. Countries that have structured their national, sectoral, and linguistic data will have an advantage. Second, talent development. Not just AI literacy in the sense of knowing how to use a tool. But the capacity to design, evaluate, and govern autonomous systems. I covered this in my analysis of the best AI training programs for French speakers.
The Kaspersky study relayed by Le Matin.ma and cio-mag.com is telling: 42% of enterprise users in Morocco import complete documents into uncontrolled external tools. If that’s the maturity level with today’s specialized tools, AI governance with more autonomous systems becomes urgent.
What We Know, What We Don’t
The most serious researchers, including those at DeepMind and Anthropic, estimate we’re still far from operational AGI, even as progress accelerates.
We know current systems are moving toward greater generalization, not less.
We don’t know when. Or whether it’s a matter of years or decades.
What an executive can do now: structure AI governance to be extensible. Don’t build AI policies that become obsolete as tools evolve. Think in principles, not in tools.
If you want to structure this approach for your organization, request a free diagnostic.
FAQ
Does artificial general intelligence exist today?
No. No operational system meets the definition of AGI. Even the most advanced current tools remain specialized in a domain or type of task. AGI remains a research objective.
What’s the difference between generative AI and artificial general intelligence?
Generative AI, like ChatGPT or Midjourney, produces content from training data. It’s specialized in generating text, images, or code. AGI would be capable of reasoning about any problem, including entirely new situations, without prior specific training.
When will AGI be available?
Estimates vary considerably among researchers. Some suggest 10 to 20 years, others several decades. There is no scientific consensus on the timeline. What is certain: progress toward greater generalization is real and measurable.
Which African sectors would be most impacted by AGI?
Agriculture is the sector where concrete projects, such as Josué Yassarandji’s Agri AI recognized at the Connected Africa Summit 2026, already show ambitions for multi-domain reasoning. Beyond that, any sector combining complex decisions in variable environments, logistics, energy, public services, would be directly affected by the emergence of more autonomous systems.