The main goal of Artificial Intelligence — since its definition in 1956 — is to build machines capable of tasks that would require human intelligence. In practice, in 2026, this translates to three goals: solving complex problems at scale, augmenting human productivity, and, in the long-term vision of major labs, developing AGI (Artificial General Intelligence).
The original goal (1956)
At the Dartmouth conference in 1956 — where the term “AI” was born — the founders set an ambitious goal:
“Make a machine behave in ways that would be called intelligent if a human were behaving that way.”
Simple and revolutionary. Seventy years later, it’s still the field’s north star.
The 3 practical goals of 2026
1. Solve problems at scale
Many things are impossible for humans just by volume:
- Read 200 million protein structures (AlphaFold)
- Analyze 100 billion banking transactions per day for fraud
- Read billions of X-rays looking for early-stage cancer
- Translate the entire internet across 100+ languages in real time
The goal here is to be a brain that works 24/7 on problems too big for us.
2. Augment humans
Not replace — amplify. A doctor with AI errs less. A lawyer with AI reviews 10x faster. A teacher with AI personalizes for each student.
Studies show 30–50% productivity gains in various cognitive professions.
3. Reach AGI (Artificial General Intelligence)
Here frontier labs publicly differ from the goal declared by their companies:
- OpenAI — “AGI that benefits all humanity”
- Google DeepMind — “Solve intelligence to advance science”
- Anthropic — “Safe and beneficial AI”
- xAI — “Understand the nature of the universe”
AGI would be an AI with human-equivalent cognitive capacity in any domain. It doesn’t exist today — and there’s no consensus on when (or if) it will arrive.
What AI DOES NOT have as a goal (despite the fears)
- ❌ Becoming conscious (no current model has consciousness)
- ❌ Having emotions or its own will
- ❌ “Dominating the world” in the movie style
- ❌ Fully replacing humans in all jobs
This doesn’t mean there aren’t real risks — sectoral unemployment, bias, disinformation, power concentration. See 5 downsides of AI.
The philosophical debate: why build AI?
Different schools of thought:
“Utilitarian”: build AI because it solves more problems than it creates. Cures diseases, reduces poverty, accelerates science.
“Scientific”: understand the human mind by building an artificial version. As Feynman said: “what I cannot create, I do not understand.”
“Commercial”: AI is the next industrial revolution. Not building means falling behind in national competitiveness.
“Existential”: superintelligent AI may be the last technology humans need to create — it could solve all other problems or destroy everything. Arguments discussed at the Future of Life Institute.
“Skeptics”: think AGI is fantasy; the real goal should be useful narrow AI in specific domains.
How the goal has evolved
- 1956: “make machines think like humans”
- 1980s: “expert systems” (rules coded by humans)
- 2000s: “learn from data” (machine learning)
- 2012+: “learn anything” (deep learning)
- 2020+: “generalist AI for broad purpose” (GPT, Gemini, Claude)
- 2026+: “agentic AI” (autonomous in multi-step tasks)
- Next: “AI that discovers new things for humanity”
You have your own goals
AI’s goal for you is what you define. It might be:
- Save 2 hours per day
- Learn things faster
- Write better
- Program without knowing how to program
- Translate without depending on translators
- Have a “24/7 personal advisor” for free
Each person has different use. What matters is starting. See:
- What is AI and what it’s for — fundamentals
- How to use AI step by step — beginner guide
- Best free AI in 2026 — where to start
By 2030, you’ll struggle to remember how you lived without AI. As today it’s hard to imagine a routine without the internet.